Cloud computing in medical imaging.

Science.gov (United States)

Kagadis, George C; Kloukinas, Christos; Moore, Kevin; Philbin, Jim; Papadimitroulas, Panagiotis; Alexakos, Christos; Nagy, Paul G; Visvikis, Dimitris; Hendee, William R

2013-07-01

Over the past century technology has played a decisive role in defining, driving, and reinventing procedures, devices, and pharmaceuticals in healthcare. Cloud computing has been introduced only recently but is already one of the major topics of discussion in research and clinical settings. The provision of extensive, easily accessible, and reconfigurable resources such as virtual systems, platforms, and applications with low service cost has caught the attention of many researchers and clinicians. Healthcare researchers are moving their efforts to the cloud, because they need adequate resources to process, store, exchange, and use large quantities of medical data. This Vision 20/20 paper addresses major questions related to the applicability of advanced cloud computing in medical imaging. The paper also considers security and ethical issues that accompany cloud computing.

High-contrast imaging in the cloud with klipReduce and Findr

Science.gov (United States)

Haug-Baltzell, Asher; Males, Jared R.; Morzinski, Katie M.; Wu, Ya-Lin; Merchant, Nirav; Lyons, Eric; Close, Laird M.

2016-08-01

Astronomical data sets are growing ever larger, and the area of high contrast imaging of exoplanets is no exception. With the advent of fast, low-noise detectors operating at 10 to 1000 Hz, huge numbers of images can be taken during a single hours-long observation. High frame rates offer several advantages, such as improved registration, frame selection, and improved speckle calibration. However, advanced image processing algorithms are computationally challenging to apply. Here we describe a parallelized, cloud-based data reduction system developed for the Magellan Adaptive Optics VisAO camera, which is capable of rapidly exploring tens of thousands of parameter sets affecting the Karhunen-Loève image processing (KLIP) algorithm to produce high-quality direct images of exoplanets. We demonstrate these capabilities with a visible wavelength high contrast data set of a hydrogen-accreting brown dwarf companion.

Feeding People's Curiosity: Leveraging the Cloud for Automatic Dissemination of Mars Images

Science.gov (United States)

Knight, David; Powell, Mark

2013-01-01

Smartphones and tablets have made wireless computing ubiquitous, and users expect instant, on-demand access to information. The Mars Science Laboratory (MSL) operations software suite, MSL InterfaCE (MSLICE), employs a different back-end image processing architecture compared to that of the Mars Exploration Rovers (MER) in order to better satisfy modern consumer-driven usage patterns and to offer greater server-side flexibility. Cloud services are a centerpiece of the server-side architecture that allows new image data to be delivered automatically to both scientists using MSLICE and the general public through the MSL website (http://mars.jpl.nasa.gov/msl/).

CLOUD DETECTION OF OPTICAL SATELLITE IMAGES USING SUPPORT VECTOR MACHINE

Directory of Open Access Journals (Sweden)

K.-Y. Lee

2016-06-01

Full Text Available Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012 uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+ and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate

Cloud Detection of Optical Satellite Images Using Support Vector Machine

Science.gov (United States)

Lee, Kuan-Yi; Lin, Chao-Hung

2016-06-01

Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM) is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA) algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012) uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate the detection

Accelerating statistical image reconstruction algorithms for fan-beam x-ray CT using cloud computing

Science.gov (United States)

Srivastava, Somesh; Rao, A. Ravishankar; Sheinin, Vadim

2011-03-01

Statistical image reconstruction algorithms potentially offer many advantages to x-ray computed tomography (CT), e.g. lower radiation dose. But, their adoption in practical CT scanners requires extra computation power, which is traditionally provided by incorporating additional computing hardware (e.g. CPU-clusters, GPUs, FPGAs etc.) into a scanner. An alternative solution is to access the required computation power over the internet from a cloud computing service, which is orders-of-magnitude more cost-effective. This is because users only pay a small pay-as-you-go fee for the computation resources used (i.e. CPU time, storage etc.), and completely avoid purchase, maintenance and upgrade costs. In this paper, we investigate the benefits and shortcomings of using cloud computing for statistical image reconstruction. We parallelized the most time-consuming parts of our application, the forward and back projectors, using MapReduce, the standard parallelization library on clouds. From preliminary investigations, we found that a large speedup is possible at a very low cost. But, communication overheads inside MapReduce can limit the maximum speedup, and a better MapReduce implementation might become necessary in the future. All the experiments for this paper, including development and testing, were completed on the Amazon Elastic Compute Cloud (EC2) for less than $20.

Identification of clouds and aurorae in optical data images

CERN Document Server

Seviour, R; Honary, F

2003-01-01

In this paper we present an automatic image recognition technique used to identify clouds and aurorae in digital images, taken with a CCD all-sky imager. The image recognition algorithm uses image segmentation to generate a binary block object image. Object analysis is then performed on the binary block image, the results of which are used to assess whether clouds, aurorae and stars are present in the original image. The need for such an algorithm arises because the optical study of particle precipitation into the Earth's atmosphere by the Ionosphere and Radio Propagation Group at Lancaster generates vast data-sets, over 25 000 images/year, making manual classification of all the images impractical.

Featured Image: A Molecular Cloud Outside Our Galaxy

Science.gov (United States)

Kohler, Susanna

2018-06-01

What do molecular clouds look like outside of our own galaxy? See for yourself in the images above and below of N55, a molecular cloud located in the Large Magellanic Cloud (LMC). In a recent study led by Naslim Neelamkodan (Academia Sinica Institute of Astronomy and Astrophysics, Taiwan), a team of scientists explore N55 to determine how its cloud properties differ from clouds within the Milky Way. The image above reveals the distribution of infrared-emitting gas and dust observed in three bands by the Spitzer Space Telescope. Overplotted in cyan are observations from the Atacama Submillimeter Telescope Experiment tracing the clumpy, warm molecular gas. Below, new observations from the Atacama Large Millimeter/submillimeter Array (ALMA) reveal the sub-parsec-scale molecular clumps in greater detail, showing the correlation of massive clumps with Spitzer-identified young stellar objects (crosses). The study presented here indicates that this cloud in the LMC is the site of massive star formation, with properties similar to equivalent clouds in the Milky Way. To learn more about the authors findings, check out the article linked below.CitationNaslim N. et al 2018 ApJ 853 175. doi:10.3847/1538-4357/aaa5b0

Cloud classification using whole-sky imager data

Energy Technology Data Exchange (ETDEWEB)

Buch, K.A. Jr.; Sun, C.H.; Thorne, L.R. [Sandia National Labs., Livermore, CA (United States)

1996-04-01

Clouds are one of the most important moderators of the earth radiation budget and one of the least understood. The effect that clouds have on the reflection and absorption of solar and terrestrial radiation is strongly influenced by their shape, size, and composition. Physically accurate parameterization of clouds is necessary for any general circulation model (GCM) to yield meaningful results. The work presented here is part of a larger project that is aimed at producing realistic three-dimensional (3D) volume renderings of cloud scenes based on measured data from real cloud scenes. These renderings will provide the important shape information for parameterizing GCMs. The specific goal of the current study is to develop an algorithm that automatically classifies (by cloud type) the clouds observed in the scene. This information will assist the volume rendering program in determining the shape of the cloud. Much work has been done on cloud classification using multispectral satellite images. Most of these references use some kind of texture measure to distinguish the different cloud types and some also use topological features (such as cloud/sky connectivity or total number of clouds). A wide variety of classification methods has been used, including neural networks, various types of clustering, and thresholding. The work presented here uses binary decision trees to distinguish the different cloud types based on cloud features vectors.

A holistic image segmentation framework for cloud detection and extraction

Science.gov (United States)

Shen, Dan; Xu, Haotian; Blasch, Erik; Horvath, Gregory; Pham, Khanh; Zheng, Yufeng; Ling, Haibin; Chen, Genshe

2013-05-01

Atmospheric clouds are commonly encountered phenomena affecting visual tracking from air-borne or space-borne sensors. Generally clouds are difficult to detect and extract because they are complex in shape and interact with sunlight in a complex fashion. In this paper, we propose a clustering game theoretic image segmentation based approach to identify, extract, and patch clouds. In our framework, the first step is to decompose a given image containing clouds. The problem of image segmentation is considered as a "clustering game". Within this context, the notion of a cluster is equivalent to a classical equilibrium concept from game theory, as the game equilibrium reflects both the internal and external (e.g., two-player) cluster conditions. To obtain the evolutionary stable strategies, we explore three evolutionary dynamics: fictitious play, replicator dynamics, and infection and immunization dynamics (InImDyn). Secondly, we use the boundary and shape features to refine the cloud segments. This step can lower the false alarm rate. In the third step, we remove the detected clouds and patch the empty spots by performing background recovery. We demonstrate our cloud detection framework on a video clip provides supportive results.

The Application of the Technology of 3D Satellite Cloud Imaging in Virtual Reality Simulation

Directory of Open Access Journals (Sweden)

Xiao-fang Xie

2007-05-01

Full Text Available Using satellite cloud images to simulate clouds is one of the new visual simulation technologies in Virtual Reality (VR. Taking the original data of satellite cloud images as the source, this paper depicts specifically the technology of 3D satellite cloud imaging through the transforming of coordinates and projection, creating a DEM (Digital Elevation Model of cloud imaging and 3D simulation. A Mercator projection was introduced to create a cloud image DEM, while solutions for geodetic problems were introduced to calculate distances, and the outer-trajectory science of rockets was introduced to obtain the elevation of clouds. For demonstration, we report on a computer program to simulate the 3D satellite cloud images.

Multi-provider architecture for cloud outsourcing of medical imaging repositories.

Science.gov (United States)

Godinho, Tiago Marques; Bastião Silva, Luís A; Costa, Carlos; Oliveira, José Luís

2014-01-01

Over the last few years, the extended usage of medical imaging procedures has raised the medical community attention towards the optimization of their workflows. More recently, the federation of multiple institutions into a seamless distribution network has brought hope of increased quality healthcare services along with more efficient resource management. As a result, medical institutions are constantly looking for the best infrastructure to deploy their imaging archives. In this scenario, public cloud infrastructures arise as major candidates, as they offer elastic storage space, optimal data availability without great requirements of maintenance costs or IT personnel, in a pay-as-you-go model. However, standard methodologies still do not take full advantage of outsourced archives, namely because their integration with other in-house solutions is troublesome. This document proposes a multi-provider architecture for integration of outsourced archives with in-house PACS resources, taking advantage of foreign providers to store medical imaging studies, without disregarding security. It enables the retrieval of images from multiple archives simultaneously, improving performance, data availability and avoiding the vendor-locking problem. Moreover it enables load balancing and cache techniques.

Self-Similar Spin Images for Point Cloud Matching

Science.gov (United States)

Pulido, Daniel

based on the concept of self-similarity to aid in the scale and feature matching steps. An open problem in fusion is how best to extract features from two point clouds and then perform feature-based matching. The proposed approach for this matching step is the use of local self-similarity as an invariant measure to match features. In particular, the proposed approach is to combine the concept of local self-similarity with a well-known feature descriptor, Spin Images, and thereby define "Self-Similar Spin Images". This approach is then extended to the case of matching two points clouds in very different coordinate systems (e.g., a geo-referenced Lidar point cloud and stereo-image derived point cloud without geo-referencing). The use of Self-Similar Spin Images is again applied to address this problem by introducing a "Self-Similar Keyscale" that matches the spatial scales of two point clouds. Another open problem is how best to detect changes in content between two point clouds. A method is proposed to find changes between two point clouds by analyzing the order statistics of the nearest neighbors between the two clouds, and thereby define the "Nearest Neighbor Order Statistic" method. Note that the well-known Hausdorff distance is a special case as being just the maximum order statistic. Therefore, by studying the entire histogram of these nearest neighbors it is expected to yield a more robust method to detect points that are present in one cloud but not the other. This approach is applied at multiple resolutions. Therefore, changes detected at the coarsest level will yield large missing targets and at finer levels will yield smaller targets.

RESEARCH OF REGISTRATION APPROACHES OF THERMAL INFRARED IMAGES AND INTENSITY IMAGES OF POINT CLOUD

Directory of Open Access Journals (Sweden)

L. Liu

2017-09-01

Full Text Available In order to realize the analysis of thermal energy of the objects in 3D vision, the registration approach of thermal infrared images and TLS (Terrestrial Laser Scanner point cloud was studied. The original data was pre-processed. For the sake of making the scale and brightness contrast of the two kinds of data meet the needs of basic matching, the intensity image of point cloud was produced and projected to spherical coordinate system, histogram equalization processing was done for thermal infrared image.This paper focused on the research of registration approaches of thermal infrared images and intensity images of point cloud based on SIFT，EOH-SIFT and PIIFD operators. The latter of which is usually used for medical image matching with different spectral character. The comparison results of the experiments showed that PIIFD operator got much more accurate feature point correspondences compared to SIFT and EOH-SIFT operators. The thermal infrared image and intensity image also have ideal overlap results by quadratic polynomial transformation. Therefore, PIIFD can be used as the basic operator for the registration of thermal infrared images and intensity images, and the operator can also be further improved by incorporating the iteration method.

Evaluation of a cloud-based local-read paradigm for imaging evaluations in oncology clinical trials for lung cancer

International Nuclear Information System (INIS)

Sueoka-Aragane, Naoko; Kobayashi, Naomi; Bonnard, Eric; Charbonnier, Colette; Yamamichi, Junta; Mizobe, Hideaki; Kimura, Shinya

2015-01-01

Although tumor response evaluated with radiological imaging is frequently used as a primary endpoint in clinical trials, it is difficult to obtain precise results because of inter- and intra-observer differences. To evaluate usefulness of a cloud-based local-read paradigm implementing software solutions that standardize imaging evaluations among international investigator sites for clinical trials of lung cancer. Two studies were performed: KUMO I and KUMO I Extension. KUMO I was a pilot study aiming at demonstrating the feasibility of cloud implementation and identifying issues regarding variability of evaluations among sites. Chest CT scans at three time-points from baseline to progression, from 10 patients with lung cancer who were treated with EGFR tyrosine kinase inhibitors, were evaluated independently by two oncologists (Japan) and one radiologist (France), through a cloud-based software solution. The KUMO I Extension was performed based on the results of KUMO I. KUMO I showed discordance rates of 40% for target lesion selection, 70% for overall response at the first time-point, and 60% for overall response at the second time-point. Since the main reason for the discordance was differences in the selection of target lesions, KUMO I Extension added a cloud-based quality control service to achieve a consensus on the selection of target lesions, resulting in an improved rate of agreement of response evaluations. The study shows the feasibility of imaging evaluations at investigator sites, based on cloud services for clinical studies involving multiple international sites. This system offers a step forward in standardizing evaluations of images among widely dispersed sites

Introducing two Random Forest based methods for cloud detection in remote sensing images

Science.gov (United States)

Ghasemian, Nafiseh; Akhoondzadeh, Mehdi

2018-07-01

Cloud detection is a necessary phase in satellite images processing to retrieve the atmospheric and lithospheric parameters. Currently, some cloud detection methods based on Random Forest (RF) model have been proposed but they do not consider both spectral and textural characteristics of the image. Furthermore, they have not been tested in the presence of snow/ice. In this paper, we introduce two RF based algorithms, Feature Level Fusion Random Forest (FLFRF) and Decision Level Fusion Random Forest (DLFRF) to incorporate visible, infrared (IR) and thermal spectral and textural features (FLFRF) including Gray Level Co-occurrence Matrix (GLCM) and Robust Extended Local Binary Pattern (RELBP_CI) or visible, IR and thermal classifiers (DLFRF) for highly accurate cloud detection on remote sensing images. FLFRF first fuses visible, IR and thermal features. Thereafter, it uses the RF model to classify pixels to cloud, snow/ice and background or thick cloud, thin cloud and background. DLFRF considers visible, IR and thermal features (both spectral and textural) separately and inserts each set of features to RF model. Then, it holds vote matrix of each run of the model. Finally, it fuses the classifiers using the majority vote method. To demonstrate the effectiveness of the proposed algorithms, 10 Terra MODIS and 15 Landsat 8 OLI/TIRS images with different spatial resolutions are used in this paper. Quantitative analyses are based on manually selected ground truth data. Results show that after adding RELBP_CI to input feature set cloud detection accuracy improves. Also, the average cloud kappa values of FLFRF and DLFRF on MODIS images (1 and 0.99) are higher than other machine learning methods, Linear Discriminate Analysis (LDA), Classification And Regression Tree (CART), K Nearest Neighbor (KNN) and Support Vector Machine (SVM) (0.96). The average snow/ice kappa values of FLFRF and DLFRF on MODIS images (1 and 0.85) are higher than other traditional methods. The

An Uneven Illumination Correction Algorithm for Optical Remote Sensing Images Covered with Thin Clouds

Directory of Open Access Journals (Sweden)

Xiaole Shen

2015-09-01

Full Text Available The uneven illumination phenomenon caused by thin clouds will reduce the quality of remote sensing images, and bring adverse effects to the image interpretation. To remove the effect of thin clouds on images, an uneven illumination correction can be applied. In this paper, an effective uneven illumination correction algorithm is proposed to remove the effect of thin clouds and to restore the ground information of the optical remote sensing image. The imaging model of remote sensing images covered by thin clouds is analyzed. Due to the transmission attenuation, reflection, and scattering, the thin cloud cover usually increases region brightness and reduces saturation and contrast of the image. As a result, a wavelet domain enhancement is performed for the image in Hue-Saturation-Value (HSV color space. We use images with thin clouds in Wuhan area captured by QuickBird and ZiYuan-3 (ZY-3 satellites for experiments. Three traditional uneven illumination correction algorithms, i.e., multi-scale Retinex (MSR algorithm, homomorphic filtering (HF-based algorithm, and wavelet transform-based MASK (WT-MASK algorithm are performed for comparison. Five indicators, i.e., mean value, standard deviation, information entropy, average gradient, and hue deviation index (HDI are used to analyze the effect of the algorithms. The experimental results show that the proposed algorithm can effectively eliminate the influences of thin clouds and restore the real color of ground objects under thin clouds.

3D Point Cloud Reconstruction from Single Plenoptic Image

Directory of Open Access Journals (Sweden)

F. Murgia

2016-06-01

Full Text Available Novel plenoptic cameras sample the light field crossing the main camera lens. The information available in a plenoptic image must be processed, in order to create the depth map of the scene from a single camera shot. In this paper a novel algorithm, for the reconstruction of 3D point cloud of the scene from a single plenoptic image, taken with a consumer plenoptic camera, is proposed. Experimental analysis is conducted on several test images, and results are compared with state of the art methodologies. The results are very promising, as the quality of the 3D point cloud from plenoptic image, is comparable with the quality obtained with current non-plenoptic methodologies, that necessitate more than one image.

Images from Galileo of the Venus cloud deck

Science.gov (United States)

Belton, M.J.S.; Gierasch, P.J.; Smith, M.D.; Helfenstein, P.; Schinder, P.J.; Pollack, James B.; Rages, K.A.; Ingersoll, A.P.; Klaasen, K.P.; Veverka, J.; Anger, C.D.; Carr, M.H.; Chapman, C.R.; Davies, M.E.; Fanale, F.P.; Greeley, R.; Greenberg, R.; Head, J. W.; Morrison, D.; Neukum, G.; Pilcher, C.B.

1991-01-01

Images of Venus taken at 418 (violet) and 986 [near-infrared (NIR)] nanometers show that the morphology and motions of large-scale features change with depth in the cloud deck. Poleward meridional velocities, seen in both spectral regions, are much reduced in the NIR. In the south polar region the markings in the two wavelength bands are strongly anticorrelated. The images follow the changing state of the upper cloud layer downwind of the subsolar point, and the zonal flow field shows a longitudinal periodicity that may be coupled to the formation of large-scale planetary waves. No optical lightning was detected.

Using Deep Learning Model for Meteorological Satellite Cloud Image Prediction

Science.gov (United States)

Su, X.

2017-12-01

A satellite cloud image contains much weather information such as precipitation information. Short-time cloud movement forecast is important for precipitation forecast and is the primary means for typhoon monitoring. The traditional methods are mostly using the cloud feature matching and linear extrapolation to predict the cloud movement, which makes that the nonstationary process such as inversion and deformation during the movement of the cloud is basically not considered. It is still a hard task to predict cloud movement timely and correctly. As deep learning model could perform well in learning spatiotemporal features, to meet this challenge, we could regard cloud image prediction as a spatiotemporal sequence forecasting problem and introduce deep learning model to solve this problem. In this research, we use a variant of Gated-Recurrent-Unit(GRU) that has convolutional structures to deal with spatiotemporal features and build an end-to-end model to solve this forecast problem. In this model, both the input and output are spatiotemporal sequences. Compared to Convolutional LSTM(ConvLSTM) model, this model has lower amount of parameters. We imply this model on GOES satellite data and the model perform well.

Reflective all-sky thermal infrared cloud imager.

Science.gov (United States)

Redman, Brian J; Shaw, Joseph A; Nugent, Paul W; Clark, R Trevor; Piazzolla, Sabino

2018-04-30

A reflective all-sky imaging system has been built using a long-wave infrared microbolometer camera and a reflective metal sphere. This compact system was developed for measuring spatial and temporal patterns of clouds and their optical depth in support of applications including Earth-space optical communications. The camera is mounted to the side of the reflective sphere to leave the zenith sky unobstructed. The resulting geometric distortion is removed through an angular map derived from a combination of checkerboard-target imaging, geometric ray tracing, and sun-location-based alignment. A tape of high-emissivity material on the side of the reflector acts as a reference that is used to estimate and remove thermal emission from the metal sphere. Once a bias that is under continuing study was removed, sky radiance measurements from the all-sky imager in the 8-14 μm wavelength range agreed to within 0.91 W/(m 2 sr) of measurements from a previously calibrated, lens-based infrared cloud imager over its 110° field of view.

Toward Confirming a Framework for Securing the Virtual Machine Image in Cloud Computing

Directory of Open Access Journals (Sweden)

Raid Khalid Hussein

2017-04-01

Full Text Available The concept of cloud computing has arisen thanks to academic work in the fields of utility computing, distributed computing, virtualisation, and web services. By using cloud computing, which can be accessed from anywhere, newly-launched businesses can minimise their start-up costs. Among the most important notions when it comes to the construction of cloud computing is virtualisation. While this concept brings its own security risks, these risks are not necessarily related to the cloud. The main disadvantage of using cloud computing is linked to safety and security. This is because anybody which chooses to employ cloud computing will use someone else’s hard disk and CPU in order to sort and store data. In cloud environments, a great deal of importance is placed on guaranteeing that the virtual machine image is safe and secure. Indeed, a previous study has put forth a framework with which to protect the virtual machine image in cloud computing. As such, the present study is primarily concerned with confirming this theoretical framework so as to ultimately secure the virtual machine image in cloud computing. This will be achieved by carrying out interviews with experts in the field of cloud security.

Coupled Retrieval of Liquid Water Cloud and Above-Cloud Aerosol Properties Using the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI)

Science.gov (United States)

Xu, Feng; van Harten, Gerard; Diner, David J.; Davis, Anthony B.; Seidel, Felix C.; Rheingans, Brian; Tosca, Mika; Alexandrov, Mikhail D.; Cairns, Brian; Ferrare, Richard A.; Burton, Sharon P.; Fenn, Marta A.; Hostetler, Chris A.; Wood, Robert; Redemann, Jens

2018-03-01

An optimization algorithm is developed to retrieve liquid water cloud properties including cloud optical depth (COD), droplet size distribution and cloud top height (CTH), and above-cloud aerosol properties including aerosol optical depth (AOD), single-scattering albedo, and microphysical properties from sweep-mode observations by Jet Propulsion Laboratory's Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) instrument. The retrieval is composed of three major steps: (1) initial estimate of the mean droplet size distribution across the entire image of 80-100 km along track by 10-25 km across track from polarimetric cloudbow observations, (2) coupled retrieval of image-scale cloud and above-cloud aerosol properties by fitting the polarimetric data at all observation angles, and (3) iterative retrieval of 1-D radiative transfer-based COD and droplet size distribution at pixel scale (25 m) by establishing relationships between COD and droplet size and fitting the total radiance measurements. Our retrieval is tested using 134 AirMSPI data sets acquired during the National Aeronautics and Space Administration (NASA) field campaign ObseRvations of Aerosols above CLouds and their intEractionS. The retrieved above-cloud AOD and CTH are compared to coincident HSRL-2 (HSRL-2, NASA Langley Research Center) data, and COD and droplet size distribution parameters (effective radius reff and effective variance veff) are compared to coincident Research Scanning Polarimeter (RSP) (NASA Goddard Institute for Space Studies) data. Mean absolute differences between AirMSPI and HSRL-2 retrievals of above-cloud AOD at 532 nm and CTH are 0.03 and mean absolute differences between RSP and AirMSPI retrievals of COD, reff, and veff in the cloudbow area are 2.33, 0.69 μm, and 0.020, respectively. Neglect of smoke aerosols above cloud leads to an underestimate of image-averaged COD by 15%.

GIFT-Cloud: A data sharing and collaboration platform for medical imaging research.

Science.gov (United States)

Doel, Tom; Shakir, Dzhoshkun I; Pratt, Rosalind; Aertsen, Michael; Moggridge, James; Bellon, Erwin; David, Anna L; Deprest, Jan; Vercauteren, Tom; Ourselin, Sébastien

2017-02-01

Clinical imaging data are essential for developing research software for computer-aided diagnosis, treatment planning and image-guided surgery, yet existing systems are poorly suited for data sharing between healthcare and academia: research systems rarely provide an integrated approach for data exchange with clinicians; hospital systems are focused towards clinical patient care with limited access for external researchers; and safe haven environments are not well suited to algorithm development. We have established GIFT-Cloud, a data and medical image sharing platform, to meet the needs of GIFT-Surg, an international research collaboration that is developing novel imaging methods for fetal surgery. GIFT-Cloud also has general applicability to other areas of imaging research. GIFT-Cloud builds upon well-established cross-platform technologies. The Server provides secure anonymised data storage, direct web-based data access and a REST API for integrating external software. The Uploader provides automated on-site anonymisation, encryption and data upload. Gateways provide a seamless process for uploading medical data from clinical systems to the research server. GIFT-Cloud has been implemented in a multi-centre study for fetal medicine research. We present a case study of placental segmentation for pre-operative surgical planning, showing how GIFT-Cloud underpins the research and integrates with the clinical workflow. GIFT-Cloud simplifies the transfer of imaging data from clinical to research institutions, facilitating the development and validation of medical research software and the sharing of results back to the clinical partners. GIFT-Cloud supports collaboration between multiple healthcare and research institutions while satisfying the demands of patient confidentiality, data security and data ownership. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Registration of vehicle based panoramic image and LiDAR point cloud

Science.gov (United States)

Chen, Changjun; Cao, Liang; Xie, Hong; Zhuo, Xiangyu

2013-10-01

Higher quality surface information would be got when data from optical images and LiDAR were integrated, owing to the fact that optical images and LiDAR point cloud have unique characteristics that make them preferable in many applications. While most previous works focus on registration of pinhole perspective cameras to 2D or 3D LiDAR data. In this paper, a method for the registration of vehicle based panoramic image and LiDAR point cloud is proposed. Using the translation among panoramic image, single CCD image, laser scanner and Position and Orientation System (POS) along with the GPS/IMU data, precise co-registration between the panoramic image and the LiDAR point cloud in the world system is achieved. Results are presented under a real world data set collected by a new developed Mobile Mapping System (MMS) integrated with a high resolution panoramic camera, two laser scanners and a POS.

A cloud-based system for automatic glaucoma screening.

Science.gov (United States)

Fengshou Yin; Damon Wing Kee Wong; Ying Quan; Ai Ping Yow; Ngan Meng Tan; Gopalakrishnan, Kavitha; Beng Hai Lee; Yanwu Xu; Zhuo Zhang; Jun Cheng; Jiang Liu

2015-08-01

In recent years, there has been increasing interest in the use of automatic computer-based systems for the detection of eye diseases including glaucoma. However, these systems are usually standalone software with basic functions only, limiting their usage in a large scale. In this paper, we introduce an online cloud-based system for automatic glaucoma screening through the use of medical image-based pattern classification technologies. It is designed in a hybrid cloud pattern to offer both accessibility and enhanced security. Raw data including patient's medical condition and fundus image, and resultant medical reports are collected and distributed through the public cloud tier. In the private cloud tier, automatic analysis and assessment of colour retinal fundus images are performed. The ubiquitous anywhere access nature of the system through the cloud platform facilitates a more efficient and cost-effective means of glaucoma screening, allowing the disease to be detected earlier and enabling early intervention for more efficient intervention and disease management.

Preliminary Results from the First Deployment of a Tethered-Balloon Cloud Particle Imager Instrument Package in Arctic Stratus Clouds at Ny-Alesund

Science.gov (United States)

Lawson, P.; Stamnes, K.; Stamnes, J.; Zmarzly, P.; O'Connor, D.; Koskulics, J.; Hamre, B.

2008-12-01

A tethered balloon system specifically designed to collect microphysical data in mixed-phase clouds was deployed in Arctic stratus clouds during May 2008 near Ny-Alesund, Svalbard, at 79 degrees North Latitude. This is the first time a tethered balloon system with a cloud particle imager (CPI) that records high-resolution digital images of cloud drops and ice particles has been operated in cloud. The custom tether supplies electrical power to the instrument package, which in addition to the CPI houses a 4-pi short-wavelength radiometer and a met package that measures temperature, humidity, pressure, GPS position, wind speed and direction. The instrument package was profiled vertically through cloud up to altitudes of 1.6 km. Since power was supplied to the instrument package from the ground, it was possible to keep the balloon package aloft for extended periods of time, up to 9 hours at Ny- Ålesund, which was limited only by crew fatigue. CPI images of cloud drops and the sizes, shapes and degree of riming of ice particles are shown throughout vertical profiles of Arctic stratus clouds. The images show large regions of mixed-phase cloud from -8 to -2 C. The predominant ice crystal habits in these regions are needles and aggregates of needles. The amount of ice in the mixed-phase clouds varied considerably and did not appear to be a function of temperature. On some occasions, ice was observed near cloud base at -2 C with supercooled cloud above to - 8 C that was devoid of ice. Measurements of shortwave radiation are also presented. Correlations between particle distributions and radiative measurements will be analyzed to determine the effect of these Arctic stratus clouds on radiative forcing.

Influence of Ice Cloud Microphysics on Imager-Based Estimates of Earth's Radiation Budget

Science.gov (United States)

Loeb, N. G.; Kato, S.; Minnis, P.; Yang, P.; Sun-Mack, S.; Rose, F. G.; Hong, G.; Ham, S. H.

2016-12-01

A central objective of the Clouds and the Earth's Radiant Energy System (CERES) is to produce a long-term global climate data record of Earth's radiation budget from the TOA down to the surface along with the associated atmospheric and surface properties that influence it. CERES relies on a number of data sources, including broadband radiometers measuring incoming and reflected solar radiation and OLR, high-resolution spectral imagers, meteorological, aerosol and ozone assimilation data, and snow/sea-ice maps based on microwave radiometer data. While the TOA radiation budget is largely determined directly from accurate broadband radiometer measurements, the surface radiation budget is derived indirectly through radiative transfer model calculations initialized using imager-based cloud and aerosol retrievals and meteorological assimilation data. Because ice cloud particles exhibit a wide range of shapes, sizes and habits that cannot be independently retrieved a priori from passive visible/infrared imager measurements, assumptions about the scattering properties of ice clouds are necessary in order to retrieve ice cloud optical properties (e.g., optical depth) from imager radiances and to compute broadband radiative fluxes. This presentation will examine how the choice of an ice cloud particle model impacts computed shortwave (SW) radiative fluxes at the top-of-atmosphere (TOA) and surface. The ice cloud particle models considered correspond to those from prior, current and future CERES data product versions. During the CERES Edition2 (and Edition3) processing, ice cloud particles were assumed to be smooth hexagonal columns. In the Edition4, roughened hexagonal columns are assumed. The CERES team is now working on implementing in a future version an ice cloud particle model comprised of a two-habit ice cloud model consisting of roughened hexagonal columns and aggregates of roughened columnar elements. In each case, we use the same ice particle model in both the

Automatic Detection of Clouds and Shadows Using High Resolution Satellite Image Time Series

Science.gov (United States)

Champion, Nicolas

2016-06-01

Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel) with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel) with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8 and Pl

AUTOMATIC DETECTION OF CLOUDS AND SHADOWS USING HIGH RESOLUTION SATELLITE IMAGE TIME SERIES

Directory of Open Access Journals (Sweden)

N. Champion

2016-06-01

Full Text Available Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8

Off the Shelf Cloud Robotics for the Smart Home: Empowering a Wireless Robot through Cloud Computing

Directory of Open Access Journals (Sweden)

Javier Ramírez De La Pinta

2017-03-01

Full Text Available In this paper, we explore the possibilities offered by the integration of home automation systems and service robots. In particular, we examine how advanced computationally expensive services can be provided by using a cloud computing approach to overcome the limitations of the hardware available at the user’s home. To this end, we integrate two wireless low-cost, off-the-shelf systems in this work, namely, the service robot Rovio and the home automation system Z-wave. Cloud computing is used to enhance the capabilities of these systems so that advanced sensing and interaction services based on image processing and voice recognition can be offered.

Off the Shelf Cloud Robotics for the Smart Home: Empowering a Wireless Robot through Cloud Computing.

Science.gov (United States)

Ramírez De La Pinta, Javier; Maestre Torreblanca, José María; Jurado, Isabel; Reyes De Cozar, Sergio

2017-03-06

In this paper, we explore the possibilities offered by the integration of home automation systems and service robots. In particular, we examine how advanced computationally expensive services can be provided by using a cloud computing approach to overcome the limitations of the hardware available at the user's home. To this end, we integrate two wireless low-cost, off-the-shelf systems in this work, namely, the service robot Rovio and the home automation system Z-wave. Cloud computing is used to enhance the capabilities of these systems so that advanced sensing and interaction services based on image processing and voice recognition can be offered.

Auto-Scaling of Geo-Based Image Processing in an OpenStack Cloud Computing Environment

Directory of Open Access Journals (Sweden)

Sanggoo Kang

2016-08-01

Full Text Available Cloud computing is a base platform for the distribution of large volumes of data and high-performance image processing on the Web. Despite wide applications in Web-based services and their many benefits, geo-spatial applications based on cloud computing technology are still developing. Auto-scaling realizes automatic scalability, i.e., the scale-out and scale-in processing of virtual servers in a cloud computing environment. This study investigates the applicability of auto-scaling to geo-based image processing algorithms by comparing the performance of a single virtual server and multiple auto-scaled virtual servers under identical experimental conditions. In this study, the cloud computing environment is built with OpenStack, and four algorithms from the Orfeo toolbox are used for practical geo-based image processing experiments. The auto-scaling results from all experimental performance tests demonstrate applicable significance with respect to cloud utilization concerning response time. Auto-scaling contributes to the development of web-based satellite image application services using cloud-based technologies.

Leveraging the Cloud for Robust and Efficient Lunar Image Processing

Science.gov (United States)

Chang, George; Malhotra, Shan; Wolgast, Paul

2011-01-01

The Lunar Mapping and Modeling Project (LMMP) is tasked to aggregate lunar data, from the Apollo era to the latest instruments on the LRO spacecraft, into a central repository accessible by scientists and the general public. A critical function of this task is to provide users with the best solution for browsing the vast amounts of imagery available. The image files LMMP manages range from a few gigabytes to hundreds of gigabytes in size with new data arriving every day. Despite this ever-increasing amount of data, LMMP must make the data readily available in a timely manner for users to view and analyze. This is accomplished by tiling large images into smaller images using Hadoop, a distributed computing software platform implementation of the MapReduce framework, running on a small cluster of machines locally. Additionally, the software is implemented to use Amazon's Elastic Compute Cloud (EC2) facility. We also developed a hybrid solution to serve images to users by leveraging cloud storage using Amazon's Simple Storage Service (S3) for public data while keeping private information on our own data servers. By using Cloud Computing, we improve upon our local solution by reducing the need to manage our own hardware and computing infrastructure, thereby reducing costs. Further, by using a hybrid of local and cloud storage, we are able to provide data to our users more efficiently and securely. 12 This paper examines the use of a distributed approach with Hadoop to tile images, an approach that provides significant improvements in image processing time, from hours to minutes. This paper describes the constraints imposed on the solution and the resulting techniques developed for the hybrid solution of a customized Hadoop infrastructure over local and cloud resources in managing this ever-growing data set. It examines the performance trade-offs of using the more plentiful resources of the cloud, such as those provided by S3, against the bandwidth limitations such use

Cloud-based processing of multi-spectral imaging data

Science.gov (United States)

Bernat, Amir S.; Bolton, Frank J.; Weiser, Reuven; Levitz, David

2017-03-01

Multispectral imaging holds great promise as a non-contact tool for the assessment of tissue composition. Performing multi - spectral imaging on a hand held mobile device would allow to bring this technology and with it knowledge to low resource settings to provide a state of the art classification of tissue health. This modality however produces considerably larger data sets than white light imaging and requires preliminary image analysis for it to be used. The data then needs to be analyzed and logged, while not requiring too much of the system resource or a long computation time and battery use by the end point device. Cloud environments were designed to allow offloading of those problems by allowing end point devices (smartphones) to offload computationally hard tasks. For this end we present a method where the a hand held device based around a smartphone captures a multi - spectral dataset in a movie file format (mp4) and compare it to other image format in size, noise and correctness. We present the cloud configuration used for segmenting images to frames where they can later be used for further analysis.

Results from the Two-Year Infrared Cloud Imager Deployment at ARM's NSA Observatory in Barrow, Alaska

Science.gov (United States)

Shaw, J. A.; Nugent, P. W.

2016-12-01

Ground-based longwave-infrared (LWIR) cloud imaging can provide continuous cloud measurements in the Arctic. This is of particular importance during the Arctic winter when visible wavelength cloud imaging systems cannot operate. This method uses a thermal infrared camera to observe clouds and produce measurements of cloud amount and cloud optical depth. The Montana State University Optical Remote Sensor Laboratory deployed an infrared cloud imager (ICI) at the Atmospheric Radiation Monitoring North Slope of Alaska site at Barrow, AK from July 2012 through July 2014. This study was used to both understand the long-term operation of an ICI in the Arctic and to study the consistency of the ICI data products in relation to co-located active and passive sensors. The ICI was found to have a high correlation (> 0.92) with collocated cloud instruments and to produce an unbiased data product. However, the ICI also detects thin clouds that are not detected by most operational cloud sensors. Comparisons with high-sensitivity actively sensed cloud products confirm the existence of these thin clouds. Infrared cloud imaging systems can serve a critical role in developing our understanding of cloud cover in the Arctic by provided a continuous annual measurement of clouds at sites of interest.

Automatic registration of terrestrial point cloud using panoramic reflectance images

NARCIS (Netherlands)

Kang, Z.

2008-01-01

Much attention is paid to registration of terrestrial point clouds nowadays. Research is carried out towards improved efficiency and automation of the registration process. This paper reports a new approach for point clouds registration utilizing reflectance panoramic images. The approach follows a

Low level cloud motion vectors from Kalpana-1 visible images

Indian Academy of Sciences (India)

. In this paper, an attempt has been made to retrieve low-level cloud motion vectors using Kalpana-1 visible (VIS) images at every half an hour. The VIS channel provides better detection of low level clouds, which remain obscure in thermal IR ...

DICOM relay over the cloud.

Science.gov (United States)

Silva, Luís A Bastião; Costa, Carlos; Oliveira, José Luis

2013-05-01

Healthcare institutions worldwide have adopted picture archiving and communication system (PACS) for enterprise access to images, relying on Digital Imaging Communication in Medicine (DICOM) standards for data exchange. However, communication over a wider domain of independent medical institutions is not well standardized. A DICOM-compliant bridge was developed for extending and sharing DICOM services across healthcare institutions without requiring complex network setups or dedicated communication channels. A set of DICOM routers interconnected through a public cloud infrastructure was implemented to support medical image exchange among institutions. Despite the advantages of cloud computing, new challenges were encountered regarding data privacy, particularly when medical data are transmitted over different domains. To address this issue, a solution was introduced by creating a ciphered data channel between the entities sharing DICOM services. Two main DICOM services were implemented in the bridge: Storage and Query/Retrieve. The performance measures demonstrated it is quite simple to exchange information and processes between several institutions. The solution can be integrated with any currently installed PACS-DICOM infrastructure. This method works transparently with well-known cloud service providers. Cloud computing was introduced to augment enterprise PACS by providing standard medical imaging services across different institutions, offering communication privacy and enabling creation of wider PACS scenarios with suitable technical solutions.

Cloud Image Data Center for Healthcare Network in Taiwan.

Science.gov (United States)

Weng, Shao-Jen; Lai, Lai-Shiun; Gotcher, Donald; Wu, Hsin-Hung; Xu, Yeong-Yuh; Yang, Ching-Wen

2016-04-01

This paper investigates how a healthcare network in Taiwan uses a practical cloud image data center (CIDC) to communicate with its constituent hospital branches. A case study approach was used. The study was carried out in the central region of Taiwan, with four hospitals belonging to the Veterans Hospital healthcare network. The CIDC provides synchronous and asynchronous consultation among these branches. It provides storage, platforms, and services on demand to the hospitals. Any branch-client can pull up the patient's medical images from any hospital off this cloud. Patients can be examined at the branches, and the images and reports can be further evaluated by physicians in the main Taichung Veterans General Hospital (TVGH) to enhance the usage and efficiency of equipment in the various branches, thereby shortening the waiting time of patients. The performance of the CIDC over 5 years shows: (1) the total number of cross-hospital images accessed with CDC in the branches was 132,712; and (2) TVGH assisted the branches in keying in image reports using the CIDC 4,424 times; and (3) Implementation of the system has improved management, efficiency, speed and quality of care. Therefore, the results lead to the recommendation of continuing and expanding the cloud computing architecture to improve information sharing among branches in the healthcare network.

Virtual Machine Images Management in Cloud Environments

CERN Multimedia

CERN. Geneva

2017-01-01

Nowadays, the demand for scalability in distributed systems has led a design philosophy in which virtual resources need to be configured in a flexible way to provide services to a large number of users. The configuration and management of such an architecture is challenging (e.g.: 100,000 compute cores on the private cloud together with thousands of cores on external cloud resources). There is the need to process CPU intensive work whilst ensuring that the resources are shared fairly between different users of the system, and guarantee that all nodes are up to date with new images containing the latest software configurations. Different types of automated systems can be used to facilitate the orchestration. CERN’s current system, composed of different technologies such as OpenStack, Packer, Puppet, Rundeck and Docker will be introduced and explained, together with the process used to create new Virtual Machines images at CERN.

Three-dimensional imaging technology offers promise in medicine.

Science.gov (United States)

Karako, Kenji; Wu, Qiong; Gao, Jianjun

2014-04-01

Medical imaging plays an increasingly important role in the diagnosis and treatment of disease. Currently, medical equipment mainly has two-dimensional (2D) imaging systems. Although this conventional imaging largely satisfies clinical requirements, it cannot depict pathologic changes in 3 dimensions. The development of three-dimensional (3D) imaging technology has encouraged advances in medical imaging. Three-dimensional imaging technology offers doctors much more information on a pathology than 2D imaging, thus significantly improving diagnostic capability and the quality of treatment. Moreover, the combination of 3D imaging with augmented reality significantly improves surgical navigation process. The advantages of 3D imaging technology have made it an important component of technological progress in the field of medical imaging.

12MAP: Cloud Disaster Recovery Based on Image-Instance Mapping

OpenAIRE

Nadgowda , Shripad; Jayachandran , Praveen; Verma , Akshat

2013-01-01

Part 2: Cloud Computing; International audience; Virtual machines (VMs) in a cloud use standardized ‘golden master’ images, standard software catalog and management tools. This facilitates quick provisioning of VMs and helps reduce the cost of managing the cloud by reducing the need for specialized software skills. However, knowledge of this similarity is lost post-provisioning, as VMs could experience different changes and may drift away from one another. In this work, we propose the 12MAP s...

Cloud solution for histopathological image analysis using region of interest based compression.

Science.gov (United States)

Kanakatte, Aparna; Subramanya, Rakshith; Delampady, Ashik; Nayak, Rajarama; Purushothaman, Balamuralidhar; Gubbi, Jayavardhana

2017-07-01

Recent technological gains have led to the adoption of innovative cloud based solutions in medical imaging field. Once the medical image is acquired, it can be viewed, modified, annotated and shared on many devices. This advancement is mainly due to the introduction of Cloud computing in medical domain. Tissue pathology images are complex and are normally collected at different focal lengths using a microscope. The single whole slide image contains many multi resolution images stored in a pyramidal structure with the highest resolution image at the base and the smallest thumbnail image at the top of the pyramid. Highest resolution image will be used for tissue pathology diagnosis and analysis. Transferring and storing such huge images is a big challenge. Compression is a very useful and effective technique to reduce the size of these images. As pathology images are used for diagnosis, no information can be lost during compression (lossless compression). A novel method of extracting the tissue region and applying lossless compression on this region and lossy compression on the empty regions has been proposed in this paper. The resulting compression ratio along with lossless compression on tissue region is in acceptable range allowing efficient storage and transmission to and from the Cloud.

COMPARISON OF POINT CLOUDS DERIVED FROM AERIAL IMAGE MATCHING WITH DATA FROM AIRBORNE LASER SCANNING

Directory of Open Access Journals (Sweden)

Dominik Wojciech

2017-04-01

Full Text Available The aim of this study was to invest igate the properties of point clouds derived from aerial image matching and to compare them with point clouds from airborne laser scanning. A set of aerial images acquired in years 2010 - 2013 over the city of Elblag were used for the analysis. Images were acquired with the use of three digital cameras: DMC II 230, DMC I and DigiCAM60 with a GSD varying from 4.5 cm to 15 cm. Eight sets of images that were used in the study were acquired at different stages of the growing season – from March to December. Two L iDAR point clouds were used for the comparison – one with a density of 1.3 p/m 2 and a second with a density of 10 p/m 2 . Based on the input images point clouds were created with the use of the semi - global matching method. The properties of the obtained poi nt clouds were analyzed in three ways: – b y the comparison of the vertical accuracy of point clouds with reference to a terrain profile surveyed on bare ground with GPS - RTK method – b y visual assessment of point cloud profiles generated both from SGM and LiDAR point clouds – b y visual assessment of a digital surface model generated from a SGM point cloud with reference to a digital surface model generated from a LiDAR point cloud. The conducted studies allowed a number of observations about the quality o f SGM point clouds to be formulated with respect to different factors. The main factors having influence on the quality of SGM point clouds are GSD and base/height ratio. The essential problem related to SGM point clouds are areas covered with vegetation w here SGM point clouds are visibly worse in terms of both accuracy and the representation of terrain surface. It is difficult to expect that in these areas SG M point clouds could replace LiDAR point clouds. This leads to a general conclusion that SGM point clouds are less reliable, more unpredictable and are dependent on more factors than LiDAR point clouds. Nevertheless, SGM point

Jovian cloud structure from 5-mu M images

Science.gov (United States)

Ortiz, J. L.; Moreno, F.; Molina, A.; Roos-Serote, M.; Orton, G. S.

1999-09-01

Most radiative transfer studies place the cloud clearings responsible for the 5-mu m bright areas at pressure levels greater than 1.5 bar whereas the low-albedo clouds are placed at lower pressure levels, in the so-called ammonia cloud. If this picture is correct, and assuming that the strong vertical shear of the zonal wind detected by the Galileo Entry Probe exists at all latitudes in Jupiter, the bright areas at 5 mu m should drift faster than the dark clouds, which is not observed. At the Galileo Probe Entry latitude this can be explained by a wave, but this is not a likely explanation for all regions where the anticorrelation between 5-mu m brightness and red-nIR reflectivity is observed. Therefore, either the vertical zonal wind shears are not global or cloud clearings and dark clouds are located at the same pressure level. We have developed a multiple scattering radiative transfer code to model the limb-darkening at several jovian features derived from IRTF 4.8-mu m images, in order to retrieve information on the cloud levels. The limb darkening coefficients range from 1.4 at hot spots to 0.58 at the Equatorial Region. We also find that reflected light is dominant over thermal emission in the Equatorial Region, as already pointed out by other investigators. Preliminary results from our code tend to favor the idea that the ammonia cloud is a very high-albedo cloud with little influence on the contrast seen in the red and nIR and that a deeper cloud at P >1.5 bar can be responsible for the cloud clearings and for the low-albedo features simultaneously. This research was supported by the Comision Interministerial de Ciencia y Tecnologia under contract ESP96-0623.

Investigation into Cloud Computing for More Robust Automated Bulk Image Geoprocessing

Science.gov (United States)

Brown, Richard B.; Smoot, James C.; Underwood, Lauren; Armstrong, C. Duane

2012-01-01

Geospatial resource assessments frequently require timely geospatial data processing that involves large multivariate remote sensing data sets. In particular, for disasters, response requires rapid access to large data volumes, substantial storage space and high performance processing capability. The processing and distribution of this data into usable information products requires a processing pipeline that can efficiently manage the required storage, computing utilities, and data handling requirements. In recent years, with the availability of cloud computing technology, cloud processing platforms have made available a powerful new computing infrastructure resource that can meet this need. To assess the utility of this resource, this project investigates cloud computing platforms for bulk, automated geoprocessing capabilities with respect to data handling and application development requirements. This presentation is of work being conducted by Applied Sciences Program Office at NASA-Stennis Space Center. A prototypical set of image manipulation and transformation processes that incorporate sample Unmanned Airborne System data were developed to create value-added products and tested for implementation on the "cloud". This project outlines the steps involved in creating and testing of open source software developed process code on a local prototype platform, and then transitioning this code with associated environment requirements into an analogous, but memory and processor enhanced cloud platform. A data processing cloud was used to store both standard digital camera panchromatic and multi-band image data, which were subsequently subjected to standard image processing functions such as NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index), band stacking, reprojection, and other similar type data processes. Cloud infrastructure service providers were evaluated by taking these locally tested processing functions, and then

Cloud Classification in Wide-Swath Passive Sensor Images Aided by Narrow-Swath Active Sensor Data

Directory of Open Access Journals (Sweden)

Hongxia Wang

2018-05-01

Full Text Available It is a challenge to distinguish between different cloud types because of the complexity and diversity of cloud coverage, which is a significant clutter source that impacts on target detection and identification from the images of space-based infrared sensors. In this paper, a novel strategy for cloud classification in wide-swath passive sensor images is developed, which is aided by narrow-swath active sensor data. The strategy consists of three steps, that is, the orbit registration, most matching donor pixel selection, and cloud type assignment for each recipient pixel. A new criterion for orbit registration is proposed so as to improve the matching accuracy. The most matching donor pixel is selected via the Euclidean distance and the square sum of the radiance relative differences between the recipient and the potential donor pixels. Each recipient pixel is then assigned a cloud type that corresponds to the most matching donor. The cloud classification of the Moderate Resolution Imaging Spectroradiometer (MODIS images is performed with the aid of the data from Cloud Profiling Radar (CPR. The results are compared with the CloudSat product 2B-CLDCLASS, as well as those that are obtained using the method of the International Satellite Cloud Climatology Project (ISCCP, which demonstrates the superior classification performance of the proposed strategy.

Cloud Infrastructure & Applications - CloudIA

Science.gov (United States)

Sulistio, Anthony; Reich, Christoph; Doelitzscher, Frank

The idea behind Cloud Computing is to deliver Infrastructure-as-a-Services and Software-as-a-Service over the Internet on an easy pay-per-use business model. To harness the potentials of Cloud Computing for e-Learning and research purposes, and to small- and medium-sized enterprises, the Hochschule Furtwangen University establishes a new project, called Cloud Infrastructure & Applications (CloudIA). The CloudIA project is a market-oriented cloud infrastructure that leverages different virtualization technologies, by supporting Service-Level Agreements for various service offerings. This paper describes the CloudIA project in details and mentions our early experiences in building a private cloud using an existing infrastructure.

A Classification-oriented Method of Feature Image Generation for Vehicle-borne Laser Scanning Point Clouds

Directory of Open Access Journals (Sweden)

YANG Bisheng

2016-02-01

Full Text Available An efficient method of feature image generation of point clouds to automatically classify dense point clouds into different categories is proposed, such as terrain points, building points. The method first uses planar projection to sort points into different grids, then calculates the weights and feature values of grids according to the distribution of laser scanning points, and finally generates the feature image of point clouds. Thus, the proposed method adopts contour extraction and tracing means to extract the boundaries and point clouds of man-made objects (e.g. buildings and trees in 3D based on the image generated. Experiments show that the proposed method provides a promising solution for classifying and extracting man-made objects from vehicle-borne laser scanning point clouds.

An Intelligent Cloud Storage Gateway for Medical Imaging.

Science.gov (United States)

Viana-Ferreira, Carlos; Guerra, António; Silva, João F; Matos, Sérgio; Costa, Carlos

2017-09-01

Historically, medical imaging repositories have been supported by indoor infrastructures. However, the amount of diagnostic imaging procedures has continuously increased over the last decades, imposing several challenges associated with the storage volume, data redundancy and availability. Cloud platforms are focused on delivering hardware and software services over the Internet, becoming an appealing solution for repository outsourcing. Although this option may bring financial and technological benefits, it also presents new challenges. In medical imaging scenarios, communication latency is a critical issue that still hinders the adoption of this paradigm. This paper proposes an intelligent Cloud storage gateway that optimizes data access times. This is achieved through a new cache architecture that combines static rules and pattern recognition for eviction and prefetching. The evaluation results, obtained from experiments over a real-world dataset, show that cache hit ratios can reach around 80%, leading to reductions of image retrieval times by over 60%. The combined use of eviction and prefetching policies proposed can significantly reduce communication latency, even when using a small cache in comparison to the total size of the repository. Apart from the performance gains, the proposed system is capable of adjusting to specific workflows of different institutions.

Cloud Engineering Principles and Technology Enablers for Medical Image Processing-as-a-Service

Science.gov (United States)

Bao, Shunxing; Plassard, Andrew J.; Landman, Bennett A.; Gokhale, Aniruddha

2017-01-01

Traditional in-house, laboratory-based medical imaging studies use hierarchical data structures (e.g., NFS file stores) or databases (e.g., COINS, XNAT) for storage and retrieval. The resulting performance from these approaches is, however, impeded by standard network switches since they can saturate network bandwidth during transfer from storage to processing nodes for even moderate-sized studies. To that end, a cloud-based “medical image processing-as-a-service” offers promise in utilizing the ecosystem of Apache Hadoop, which is a flexible framework providing distributed, scalable, fault tolerant storage and parallel computational modules, and HBase, which is a NoSQL database built atop Hadoop’s distributed file system. Despite this promise, HBase’s load distribution strategy of region split and merge is detrimental to the hierarchical organization of imaging data (e.g., project, subject, session, scan, slice). This paper makes two contributions to address these concerns by describing key cloud engineering principles and technology enhancements we made to the Apache Hadoop ecosystem for medical imaging applications. First, we propose a row-key design for HBase, which is a necessary step that is driven by the hierarchical organization of imaging data. Second, we propose a novel data allocation policy within HBase to strongly enforce collocation of hierarchically related imaging data. The proposed enhancements accelerate data processing by minimizing network usage and localizing processing to machines where the data already exist. Moreover, our approach is amenable to the traditional scan, subject, and project-level analysis procedures, and is compatible with standard command line/scriptable image processing software. Experimental results for an illustrative sample of imaging data reveals that our new HBase policy results in a three-fold time improvement in conversion of classic DICOM to NiFTI file formats when compared with the default HBase region split

Cloud Engineering Principles and Technology Enablers for Medical Image Processing-as-a-Service.

Science.gov (United States)

Bao, Shunxing; Plassard, Andrew J; Landman, Bennett A; Gokhale, Aniruddha

2017-04-01

Traditional in-house, laboratory-based medical imaging studies use hierarchical data structures (e.g., NFS file stores) or databases (e.g., COINS, XNAT) for storage and retrieval. The resulting performance from these approaches is, however, impeded by standard network switches since they can saturate network bandwidth during transfer from storage to processing nodes for even moderate-sized studies. To that end, a cloud-based "medical image processing-as-a-service" offers promise in utilizing the ecosystem of Apache Hadoop, which is a flexible framework providing distributed, scalable, fault tolerant storage and parallel computational modules, and HBase, which is a NoSQL database built atop Hadoop's distributed file system. Despite this promise, HBase's load distribution strategy of region split and merge is detrimental to the hierarchical organization of imaging data (e.g., project, subject, session, scan, slice). This paper makes two contributions to address these concerns by describing key cloud engineering principles and technology enhancements we made to the Apache Hadoop ecosystem for medical imaging applications. First, we propose a row-key design for HBase, which is a necessary step that is driven by the hierarchical organization of imaging data. Second, we propose a novel data allocation policy within HBase to strongly enforce collocation of hierarchically related imaging data. The proposed enhancements accelerate data processing by minimizing network usage and localizing processing to machines where the data already exist. Moreover, our approach is amenable to the traditional scan, subject, and project-level analysis procedures, and is compatible with standard command line/scriptable image processing software. Experimental results for an illustrative sample of imaging data reveals that our new HBase policy results in a three-fold time improvement in conversion of classic DICOM to NiFTI file formats when compared with the default HBase region split policy

Astronomy In The Cloud: Using Mapreduce For Image Coaddition

Science.gov (United States)

Wiley, Keith; Connolly, A.; Gardner, J.; Krughoff, S.; Balazinska, M.; Howe, B.; Kwon, Y.; Bu, Y.

2011-01-01

In the coming decade, astronomical surveys of the sky will generate tens of terabytes of images and detect hundreds of millions of sources every night. The study of these sources will involve computational challenges such as anomaly detection, classification, and moving object tracking. Since such studies require the highest quality data, methods such as image coaddition, i.e., registration, stacking, and mosaicing, will be critical to scientific investigation. With a requirement that these images be analyzed on a nightly basis to identify moving sources, e.g., asteroids, or transient objects, e.g., supernovae, these datastreams present many computational challenges. Given the quantity of data involved, the computational load of these problems can only be addressed by distributing the workload over a large number of nodes. However, the high data throughput demanded by these applications may present scalability challenges for certain storage architectures. One scalable data-processing method that has emerged in recent years is MapReduce, and in this paper we focus on its popular open-source implementation called Hadoop. In the Hadoop framework, the data is partitioned among storage attached directly to worker nodes, and the processing workload is scheduled in parallel on the nodes that contain the required input data. A further motivation for using Hadoop is that it allows us to exploit cloud computing resources, i.e., platforms where Hadoop is offered as a service. We report on our experience implementing a scalable image-processing pipeline for the SDSS imaging database using Hadoop. This multi-terabyte imaging dataset provides a good testbed for algorithm development since its scope and structure approximate future surveys. First, we describe MapReduce and how we adapted image coaddition to the MapReduce framework. Then we describe a number of optimizations to our basic approach and report experimental results compring their performance. This work is funded by

3D Aerosol-Cloud Radiative Interaction Observed in Collocated MODIS and ASTER Images of Cumulus Cloud Fields

Science.gov (United States)

Wen, Guoyong; Marshak, Alexander; Cahalan, Robert F.; Remer, Lorraine A.; Kleidman, Richard G.

2007-01-01

3D aerosol-cloud interaction is examined by analyzing two images containing cumulus clouds in biomass burning regions in Brazil. The research consists of two parts. The first part focuses on identifying 3D clo ud impacts on the reflectance of pixel selected for the MODIS aerosol retrieval based purely on observations. The second part of the resea rch combines the observations with radiative transfer computations to identify key parameters in 3D aerosol-cloud interaction. We found that 3D cloud-induced enhancement depends on optical properties of nearb y clouds as well as wavelength. The enhancement is too large to be ig nored. Associated biased error in 1D aerosol optical thickness retrie val ranges from 50% to 140% depending on wavelength and optical prope rties of nearby clouds as well as aerosol optical thickness. We caution the community to be prudent when applying 1D approximations in comp uting solar radiation in dear regions adjacent to clouds or when usin g traditional retrieved aerosol optical thickness in aerosol indirect effect research.

The benefit of limb cloud imaging for infrared limb sounding of tropospheric trace gases

Directory of Open Access Journals (Sweden)

G. Heinemann

2009-06-01

Full Text Available Advances in detector technology enable a new generation of infrared limb sounders to measure 2-D images of the atmosphere. A proposed limb cloud imager (LCI mode will detect clouds with a spatial resolution unprecedented for limb sounding. For the inference of temperature and trace gas distributions, detector pixels of the LCI have to be combined into super-pixels which provide the required signal-to-noise and information content for the retrievals. This study examines the extent to which tropospheric coverage can be improved in comparison to limb sounding using a fixed field of view with the size of the super-pixels, as in conventional limb sounders. The study is based on cloud topographies derived from (a IR brightness temperatures (BT of geostationary weather satellites in conjunction with ECMWF temperature profiles and (b ice and liquid water content data of the Consortium for Small-scale Modeling-Europe (COSMO-EU of the German Weather Service. Limb cloud images are simulated by matching the cloud topography with the limb sounding line of sight (LOS. The analysis of the BT data shows that the reduction of the spatial sampling along the track has hardly any effect on the gain in information. The comparison between BT and COSMO-EU data identifies the strength of both data sets, which are the representation of the horizontal cloud extent for the BT data and the reproduction of the cloud amount for the COSMO-EU data. The results of the analysis of both data sets show the great advantage of the cloud imager. However, because both cloud data sets do not present the complete fine structure of the real cloud fields in the atmosphere it is assumed that the results tend to underestimate the increase in information. In conclusion, real measurements by such an instrument may result in an even higher benefit for tropospheric limb retrievals.

AUTOMATIC CLOUD DETECTION FROM MULTI-TEMPORAL SATELLITE IMAGES: TOWARDS THE USE OF PLÉIADES TIME SERIES

Directory of Open Access Journals (Sweden)

N. Champion

2012-08-01

Full Text Available Contrary to aerial images, satellite images are often affected by the presence of clouds. Identifying and removing these clouds is one of the primary steps to perform when processing satellite images, as they may alter subsequent procedures such as atmospheric corrections, DSM production or land cover classification. The main goal of this paper is to present the cloud detection approach, developed at the French Mapping agency. Our approach is based on the availability of multi-temporal satellite images (i.e. time series that generally contain between 5 and 10 images and is based on a region-growing procedure. Seeds (corresponding to clouds are firstly extracted through a pixel-to-pixel comparison between the images contained in time series (the presence of a cloud is here assumed to be related to a high variation of reflectance between two images. Clouds are then delineated finely using a dedicated region-growing algorithm. The method, originally designed for panchromatic SPOT5-HRS images, is tested in this paper using time series with 9 multi-temporal satellite images. Our preliminary experiments show the good performances of our method. In a near future, the method will be applied to Pléiades images, acquired during the in-flight commissioning phase of the satellite (launched at the end of 2011. In that context, this is a particular goal of this paper to show to which extent and in which way our method can be adapted to this kind of imagery.

A novel technique for extracting clouds base height using ground based imaging

Directory of Open Access Journals (Sweden)

E. Hirsch

2011-01-01

Full Text Available The height of a cloud in the atmospheric column is a key parameter in its characterization. Several remote sensing techniques (passive and active, either ground-based or on space-borne platforms and in-situ measurements are routinely used in order to estimate top and base heights of clouds. In this article we present a novel method that combines thermal imaging from the ground and sounded wind profile in order to derive the cloud base height. This method is independent of cloud types, making it efficient for both low boundary layer and high clouds. In addition, using thermal imaging ensures extraction of clouds' features during daytime as well as at nighttime. The proposed technique was validated by comparison to active sounding by ceilometers (which is a standard ground based method, to lifted condensation level (LCL calculations, and to MODIS products obtained from space. As all passive remote sensing techniques, the proposed method extracts only the height of the lowest cloud layer, thus upper cloud layers are not detected. Nevertheless, the information derived from this method can be complementary to space-borne cloud top measurements when deep-convective clouds are present. Unlike techniques such as LCL, this method is not limited to boundary layer clouds, and can extract the cloud base height at any level, as long as sufficient thermal contrast exists between the radiative temperatures of the cloud and its surrounding air parcel. Another advantage of the proposed method is its simplicity and modest power needs, making it particularly suitable for field measurements and deployment at remote locations. Our method can be further simplified for use with visible CCD or CMOS camera (although nighttime clouds will not be observed.

A Medical Image Backup Architecture Based on a NoSQL Database and Cloud Computing Services.

Science.gov (United States)

Santos Simões de Almeida, Luan Henrique; Costa Oliveira, Marcelo

2015-01-01

The use of digital systems for storing medical images generates a huge volume of data. Digital images are commonly stored and managed on a Picture Archiving and Communication System (PACS), under the DICOM standard. However, PACS is limited because it is strongly dependent on the server's physical space. Alternatively, Cloud Computing arises as an extensive, low cost, and reconfigurable resource. However, medical images contain patient information that can not be made available in a public cloud. Therefore, a mechanism to anonymize these images is needed. This poster presents a solution for this issue by taking digital images from PACS, converting the information contained in each image file to a NoSQL database, and using cloud computing to store digital images.

Big Data in the Cloud - Processing and Performance

CERN Multimedia

CERN. Geneva

2015-01-01

**Anthony F. Voellm** is currently leading the Google Cloud Performance Team and has a wide range of experience from kernel and database engines to graphics and automated image and map extraction from satellite images. Anthony is an avid inventor with 7 technology patents issued. In his current role at Google Anthony is focused on delivering Price Performance to existing products like Google Compute Engine and Google Cloud Storage while also innovating new offerings. Anthony holds a Master of Science from George Washington University, BA in Physics and a BS in Computer Science and Mathematics from the University of Vermont.

Venus: cloud level circulation during 1982 as determined from Pioneer cloud photopolarimeter images. 11. Solar longitude dependent circulation

International Nuclear Information System (INIS)

Limaye, S.S.

1988-01-01

Pioneer Venus Orbiter images obtained in 1982 indicate a marked solar-locked dependence of cloud level circulation in both averaged cloud motions and cloud layer UV reflectivity. An apparent relationship is noted between horizontal divergence and UV reflectivity: the highest reflectivities are associated with regions of convergence at high latitudes, while lower values are associated with equatorial latitude regions where the motions are divergent. In solar-locked coordinates, the rms deviation of normalized UV brightness is higher at 45-deg latitudes than in equatorial regions. 37 references

Testing a polarimetric cloud imager aboard research vessel Polarstern: comparison of color-based and polarimetric cloud detection algorithms.

Science.gov (United States)

Barta, András; Horváth, Gábor; Horváth, Ákos; Egri, Ádám; Blahó, Miklós; Barta, Pál; Bumke, Karl; Macke, Andreas

2015-02-10

Cloud cover estimation is an important part of routine meteorological observations. Cloudiness measurements are used in climate model evaluation, nowcasting solar radiation, parameterizing the fluctuations of sea surface insolation, and building energy transfer models of the atmosphere. Currently, the most widespread ground-based method to measure cloudiness is based on analyzing the unpolarized intensity and color distribution of the sky obtained by digital cameras. As a new approach, we propose that cloud detection can be aided by the additional use of skylight polarization measured by 180° field-of-view imaging polarimetry. In the fall of 2010, we tested such a novel polarimetric cloud detector aboard the research vessel Polarstern during expedition ANT-XXVII/1. One of our goals was to test the durability of the measurement hardware under the extreme conditions of a trans-Atlantic cruise. Here, we describe the instrument and compare the results of several different cloud detection algorithms, some conventional and some newly developed. We also discuss the weaknesses of our design and its possible improvements. The comparison with cloud detection algorithms developed for traditional nonpolarimetric full-sky imagers allowed us to evaluate the added value of polarimetric quantities. We found that (1) neural-network-based algorithms perform the best among the investigated schemes and (2) global information (the mean and variance of intensity), nonoptical information (e.g., sun-view geometry), and polarimetric information (e.g., the degree of polarization) improve the accuracy of cloud detection, albeit slightly.

Cloud cover detection combining high dynamic range sky images and ceilometer measurements

Science.gov (United States)

Román, R.; Cazorla, A.; Toledano, C.; Olmo, F. J.; Cachorro, V. E.; de Frutos, A.; Alados-Arboledas, L.

2017-11-01

This paper presents a new algorithm for cloud detection based on high dynamic range images from a sky camera and ceilometer measurements. The algorithm is also able to detect the obstruction of the sun. This algorithm, called CPC (Camera Plus Ceilometer), is based on the assumption that under cloud-free conditions the sky field must show symmetry. The symmetry criteria are applied depending on ceilometer measurements of the cloud base height. CPC algorithm is applied in two Spanish locations (Granada and Valladolid). The performance of CPC retrieving the sun conditions (obstructed or unobstructed) is analyzed in detail using as reference pyranometer measurements at Granada. CPC retrievals are in agreement with those derived from the reference pyranometer in 85% of the cases (it seems that this agreement does not depend on aerosol size or optical depth). The agreement percentage goes down to only 48% when another algorithm, based on Red-Blue Ratio (RBR), is applied to the sky camera images. The retrieved cloud cover at Granada and Valladolid is compared with that registered by trained meteorological observers. CPC cloud cover is in agreement with the reference showing a slight overestimation and a mean absolute error around 1 okta. A major advantage of the CPC algorithm with respect to the RBR method is that the determined cloud cover is independent of aerosol properties. The RBR algorithm overestimates cloud cover for coarse aerosols and high loads. Cloud cover obtained only from ceilometer shows similar results than CPC algorithm; but the horizontal distribution cannot be obtained. In addition, it has been observed that under quick and strong changes on cloud cover ceilometers retrieve a cloud cover fitting worse with the real cloud cover.

University of California, San Diego (UCSD) Sky Imager Cloud Position Study Field Campaign Report

Energy Technology Data Exchange (ETDEWEB)

Kleissl, J. [Univ. of California, San Diego, CA (United States); Urquhart, B. [Univ. of California, San Diego, CA (United States); Ghonima, M. [Univ. of California, San Diego, CA (United States); Dahlin, E. [Univ. of California, San Diego, CA (United States); Nguyen, A. [Univ. of California, San Diego, CA (United States); Kurtz, B. [Univ. of California, San Diego, CA (United States); Chow, C. W. [Univ. of California, San Diego, CA (United States); Mejia, F. A. [Univ. of California, San Diego, CA (United States)

2016-04-01

During the University of California, San Diego (UCSD) Sky Imager Cloud Position Study, two University of California, San Diego Sky Imagers (USI) (Figure 1) were deployed the U.S. Department of Energy(DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility Southern Great Plains SGP) research facility. The UCSD Sky Imagers were placed 1.7 km apart to allow for stereographic determination of the cloud height for clouds over approximately 1.5 km. Images with a 180-degree field of view were captured from both systems during daylight hours every 30 seconds beginning on March 11, 2013 and ending on November 4, 2013. The spatial resolution of the images was 1,748 × 1,748, and the intensity resolution was 16 bits using a high-dynamic-range capture process. The cameras use a fisheye lens, so the images are distorted following an equisolid angle projection.

Creating cloud-free Landsat ETM+ data sets in tropical landscapes: cloud and cloud-shadow removal

Science.gov (United States)

Sebastián Martinuzzi; William A. Gould; Olga M. Ramos Gonzalez

2007-01-01

Clouds and cloud shadows are common features of visible and infrared remotelysensed images collected from many parts of the world, particularly in humid and tropical regions. We have developed a simple and semiautomated method to mask clouds and shadows in Landsat ETM+ imagery, and have developed a recent cloud-free composite of multitemporal images for Puerto Rico and...

Pediatric Trauma Transfer Imaging Inefficiencies-Opportunities for Improvement with Cloud Technology.

Science.gov (United States)

Puckett, Yana; To, Alvin

2016-01-01

This study examines the inefficiencies of radiologic imaging transfers from one hospital to the other during pediatric trauma transfers in an era of cloud based information sharing. Retrospective review of all patients transferred to a pediatric trauma center from 2008-2014 was performed. Imaging was reviewed for whether imaging accompanied the patient, whether imaging was able to be uploaded onto computer for records, whether imaging had to be repeated, and whether imaging obtained at outside hospitals (OSH) was done per universal pediatric trauma guidelines. Of the 1761 patients retrospectively reviewed, 559 met our inclusion criteria. Imaging was sent with the patient 87.7% of the time. Imaging was unable to be uploaded 31.9% of the time. CT imaging had to be repeated 1.8% of the time. CT scan was not done per universal pediatric trauma guidelines 1.2% of the time. Our study demonstrated that current imaging transfer is inefficient, leads to excess ionizing radiation, and increased healthcare costs. Universal implementation of cloud based radiology has the potential to eliminate excess ionizing radiation to children, improve patient care, and save cost to healthcare system.

Pediatric Trauma Transfer Imaging Inefficiencies—Opportunities for Improvement with Cloud Technology

Directory of Open Access Journals (Sweden)

Yana Puckett

2016-02-01

Full Text Available BACKGROUND: This study examines the inefficiencies of radiologic imaging transfers from one hospital to the other during pediatric trauma transfers in an era of cloud based information sharing. METHODS: Retrospective review of all patients transferred to a pediatric trauma center from 2008–2014 was performed. Imaging was reviewed for whether imaging accompanied the patient, whether imaging was able to be uploaded onto computer for records, whether imaging had to be repeated, and whether imaging obtained at outside hospitals (OSH was done per universal pediatric trauma guidelines. RESULTS: Of the 1761 patients retrospectively reviewed, 559 met our inclusion criteria. Imaging was sent with the patient 87.7% of the time. Imaging was unable to be uploaded 31.9% of the time. CT imaging had to be repeated 1.8% of the time. CT scan was not done per universal pediatric trauma guidelines 1.2% of the time. CONCLUSION: Our study demonstrated that current imaging transfer is inefficient, leads to excess ionizing radiation, and increased healthcare costs. Universal implementation of cloud based radiology has the potential to eliminate excess ionizing radiation to children, improve patient care, and save cost to healthcare system.

CLOUD COMPUTING SECURITY

Directory of Open Access Journals (Sweden)

Ştefan IOVAN

2016-05-01

Full Text Available Cloud computing reprentes the software applications offered as a service online, but also the software and hardware components from the data center.In the case of wide offerd services for any type of client, we are dealing with a public cloud. In the other case, in wich a cloud is exclusively available for an organization and is not available to the open public, this is consider a private cloud [1]. There is also a third type, called hibrid in which case an user or an organization might use both services available in the public and private cloud. One of the main challenges of cloud computing are to build the trust and ofer information privacy in every aspect of service offerd by cloud computingle. The variety of existing standards, just like the lack of clarity in sustenability certificationis not a real help in building trust. Also appear some questions marks regarding the efficiency of traditionsecurity means that are applied in the cloud domain. Beside the economic and technology advantages offered by cloud, also are some advantages in security area if the information is migrated to cloud. Shared resources available in cloud includes the survey, use of the "best practices" and technology for advance security level, above all the solutions offered by the majority of medium and small businesses, big companies and even some guvermental organizations [2].

Image selection as a service for cloud computing environments

KAUST Repository

Filepp, Robert; Shwartz, Larisa; Ward, Christopher; Kearney, Robert D.; Cheng, Karen; Young, Christopher C.; Ghosheh, Yanal

2010-01-01

Customers of Cloud Services are expected to choose specific machine images to instantiate in order to host their workloads. Unfortunately very little information is provided to the users to enable them to make intelligent choices. We believe

Cloud Computing Fundamentals

Science.gov (United States)

Furht, Borko

In the introductory chapter we define the concept of cloud computing and cloud services, and we introduce layers and types of cloud computing. We discuss the differences between cloud computing and cloud services. New technologies that enabled cloud computing are presented next. We also discuss cloud computing features, standards, and security issues. We introduce the key cloud computing platforms, their vendors, and their offerings. We discuss cloud computing challenges and the future of cloud computing.

Cloud networking understanding cloud-based data center networks

CERN Document Server

Lee, Gary

2014-01-01

Cloud Networking: Understanding Cloud-Based Data Center Networks explains the evolution of established networking technologies into distributed, cloud-based networks. Starting with an overview of cloud technologies, the book explains how cloud data center networks leverage distributed systems for network virtualization, storage networking, and software-defined networking. The author offers insider perspective to key components that make a cloud network possible such as switch fabric technology and data center networking standards. The final chapters look ahead to developments in architectures

Cloud Computing Quality

Directory of Open Access Journals (Sweden)

Anamaria Şiclovan

2013-02-01

Full Text Available Cloud computing was and it will be a new way of providing Internet services and computers. This calculation approach is based on many existing services, such as the Internet, grid computing, Web services. Cloud computing as a system aims to provide on demand services more acceptable as price and infrastructure. It is exactly the transition from computer to a service offered to the consumers as a product delivered online. This paper is meant to describe the quality of cloud computing services, analyzing the advantages and characteristics offered by it. It is a theoretical paper.Keywords: Cloud computing, QoS, quality of cloud computing

International inter-rater agreement in scoring acne severity utilizing cloud-based image sharing of mobile phone photographs.

Science.gov (United States)

Foolad, Negar; Ornelas, Jennifer N; Clark, Ashley K; Ali, Ifrah; Sharon, Victoria R; Al Mubarak, Luluah; Lopez, Andrés; Alikhan, Ali; Al Dabagh, Bishr; Firooz, Alireza; Awasthi, Smita; Liu, Yu; Li, Chin-Shang; Sivamani, Raja K

2017-09-01

Cloud-based image sharing technology allows facilitated sharing of images. Cloud-based image sharing technology has not been well-studied for acne assessments or treatment preferences, among international evaluators. We evaluated inter-rater variability of acne grading and treatment recommendations among an international group of dermatologists that assessed photographs. This is a prospective, single visit photographic study to assess inter-rater agreement of acne photographs shared through an integrated mobile device, cloud-based, and HIPAA-compliant platform. Inter-rater agreements for global acne assessment and acne lesion counts were evaluated by the Kendall's coefficient of concordance while correlations between treatment recommendations and acne severity were calculated by Spearman's rank correlation coefficient. There was good agreement for the evaluation of inflammatory lesions (KCC = 0.62, P cloud-based image sharing for acne assessment. Cloud-based sharing may facilitate acne care and research among international collaborators. © 2017 The International Society of Dermatology.

CO-REGISTRATION AIRBORNE LIDAR POINT CLOUD DATA AND SYNCHRONOUS DIGITAL IMAGE REGISTRATION BASED ON COMBINED ADJUSTMENT

Directory of Open Access Journals (Sweden)

Z. H. Yang

2016-06-01

Full Text Available Aim at the problem of co-registration airborne laser point cloud data with the synchronous digital image, this paper proposed a registration method based on combined adjustment. By integrating tie point, point cloud data with elevation constraint pseudo observations, using the principle of least-squares adjustment to solve the corrections of exterior orientation elements of each image, high-precision registration results can be obtained. In order to ensure the reliability of the tie point, and the effectiveness of pseudo observations, this paper proposed a point cloud data constrain SIFT matching and optimizing method, can ensure that the tie points are located on flat terrain area. Experiments with the airborne laser point cloud data and its synchronous digital image, there are about 43 pixels error in image space using the original POS data. If only considering the bore-sight of POS system, there are still 1.3 pixels error in image space. The proposed method regards the corrections of the exterior orientation elements of each image as unknowns and the errors are reduced to 0.15 pixels.

Increasing Security for Cloud Computing By Steganography in Image Edges

Directory of Open Access Journals (Sweden)

Hassan Hadi Saleh

2017-03-01

Full Text Available The security of data storage in “cloud” is big challenge because the data keep within resources that may be accessed by particular machines. The managing of these data and services may not be high reliable. Therefore, the security of data is highly challenging. To increase the security of data in data center of cloud, we have introduced good method to ensure data security in “cloud computing” by methods of data hiding using color images which is called steganography. The fundamental objective of this paper is to prevent "Data Access” by unauthorized or opponent users. This scheme stores data at data centers within edges of color images and retrieves data from it when it is wanted.

Information Recovery Algorithm for Ground Objects in Thin Cloud Images by Fusing Guide Filter and Transfer Learning

Directory of Open Access Journals (Sweden)

HU Gensheng

2018-03-01

Full Text Available Ground object information of remote sensing images covered with thin clouds is obscure. An information recovery algorithm for ground objects in thin cloud images is proposed by fusing guide filter and transfer learning. Firstly, multi-resolution decomposition of thin cloud target images and cloud-free guidance images is performed by using multi-directional nonsubsampled dual-tree complex wavelet transform. Then the decomposed low frequency subbands are processed by using support vector guided filter and transfer learning respectively. The decomposed high frequency subbands are enhanced by using modified Laine enhancement function. The low frequency subbands output by guided filter and those predicted by transfer learning model are fused by the method of selection and weighting based on regional energy. Finally, the enhanced high frequency subbands and the fused low frequency subbands are reconstructed by using inverse multi-directional nonsubsampled dual-tree complex wavelet transform to obtain the ground object information recovery images. Experimental results of Landsat-8 OLI multispectral images show that, support vector guided filter can effectively preserve the detail information of the target images, domain adaptive transfer learning can effectively extend the range of available multi-source and multi-temporal remote sensing images, and good effects for ground object information recover are obtained by fusing guide filter and transfer learning to remove thin cloud on the remote sensing images.

Dense range images from sparse point clouds using multi-scale processing

NARCIS (Netherlands)

Do, Q.L.; Ma, L.; With, de P.H.N.

2013-01-01

Multi-modal data processing based on visual and depth/range images has become relevant in computer vision for 3D reconstruction applications such as city modeling, robot navigation etc. In this paper, we generate highaccuracy dense range images from sparse point clouds to facilitate such

EVALUATION OF METHODS FOR COREGISTRATION AND FUSION OF RPAS-BASED 3D POINT CLOUDS AND THERMAL INFRARED IMAGES

Directory of Open Access Journals (Sweden)

L. Hoegner

2016-06-01

Full Text Available This paper discusses the automatic coregistration and fusion of 3d point clouds generated from aerial image sequences and corresponding thermal infrared (TIR images. Both RGB and TIR images have been taken from a RPAS platform with a predefined flight path where every RGB image has a corresponding TIR image taken from the same position and with the same orientation with respect to the accuracy of the RPAS system and the inertial measurement unit. To remove remaining differences in the exterior orientation, different strategies for coregistering RGB and TIR images are discussed: (i coregistration based on 2D line segments for every single TIR image and the corresponding RGB image. This method implies a mainly planar scene to avoid mismatches; (ii coregistration of both the dense 3D point clouds from RGB images and from TIR images by coregistering 2D image projections of both point clouds; (iii coregistration based on 2D line segments in every single TIR image and 3D line segments extracted from intersections of planes fitted in the segmented dense 3D point cloud; (iv coregistration of both the dense 3D point clouds from RGB images and from TIR images using both ICP and an adapted version based on corresponding segmented planes; (v coregistration of both image sets based on point features. The quality is measured by comparing the differences of the back projection of homologous points in both corrected RGB and TIR images.

Assuring virtual network function image integrity and host sealing in telco cloud

NARCIS (Netherlands)

Lal, S.; Ravidas, S.; Oliver, I.; Taleb, T.

In Telco cloud environment, virtual network func- tions (VNFs) can be shipped in the form of virtual machine images and hosted over commodity hardware. It is likely that these VNF images will contain highly sensitive data and mission critical network operations. For this reason, these VNF images are

Estimation of cloud optical thickness by processing SEVIRI images and implementing a semi analytical cloud property retrieval algorithm

Science.gov (United States)

Pandey, P.; De Ridder, K.; van Lipzig, N.

2009-04-01

Clouds play a very important role in the Earth's climate system, as they form an intermediate layer between Sun and the Earth. Satellite remote sensing systems are the only means to provide information about clouds on large scales. The geostationary satellite, Meteosat Second Generation (MSG) has onboard an imaging radiometer, the Spinning Enhanced Visible and Infrared Imager (SEVIRI). SEVIRI is a 12 channel imager, with 11 channels observing the earth's full disk with a temporal resolution of 15 min and spatial resolution of 3 km at nadir, and a high resolution visible (HRV) channel. The visible channels (0.6 µm and 0.81 µm) and near infrared channel (1.6µm) of SEVIRI are being used to retrieve the cloud optical thickness (COT). The study domain is over Europe covering the region between 35°N - 70°N and 10°W - 30°E. SEVIRI level 1.5 images over this domain are being acquired from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) archive. The processing of this imagery, involves a number of steps before estimating the COT. The steps involved in pre-processing are as follows. First, the digital count number is acquired from the imagery. Image geo-coding is performed in order to relate the pixel positions to the corresponding longitude and latitude. Solar zenith angle is determined as a function of latitude and time. The radiometric conversion is done using the values of offsets and slopes of each band. The values of radiance obtained are then used to calculate the reflectance for channels in the visible spectrum using the information of solar zenith angle. An attempt is made to estimate the COT from the observed radiances. A semi analytical algorithm [Kokhanovsky et al., 2003] is implemented for the estimation of cloud optical thickness from the visible spectrum of light intensity reflected from clouds. The asymptotical solution of the radiative transfer equation, for clouds with large optical thickness, is the basis of

Hidden in the Clouds: New Ideas in Cloud Computing

CERN Multimedia

CERN. Geneva

2013-01-01

Abstract: Cloud computing has become a hot topic. But 'cloud' is no newer in 2013 than MapReduce was in 2005: We've been doing both for years. So why is cloud more relevant today than it ever has been? In this presentation, we will introduce the (current) central thesis of cloud computing, and explore how and why (or even whether) the concept has evolved. While we will cover a little light background, our primary focus will be on the consequences, corollaries and techniques introduced by some of the leading cloud developers and organizations. We each have a different deployment model, different applications and workloads, and many of us are still learning to efficiently exploit the platform services offered by a modern implementation. The discussion will offer the opportunity to share these experiences and help us all to realize the benefits of cloud computing to the fullest degree. Please bring questions and opinions, and be ready to share both!   Bio: S...

NOAA GOES-R Series Advanced Baseline Imager (ABI) Level 2+ Cloud Top Pressure (CTP)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Cloud Top Pressure product contains an image with pixel values identifying the atmospheric pressure at the top of a cloud layer. The product is generated in...

CERES cloud property retrievals from imagers on TRMM, Terra, and Aqua

Science.gov (United States)

Minnis, Patrick; Young, David F.; Sun-Mack, Sunny; Heck, Patrick W.; Doelling, David R.; Trepte, Qing Z.

2004-02-01

The micro- and macrophysical properties of clouds play a crucial role in Earth"s radiation budget. The NASA Clouds and Earth"s Radiant Energy System (CERES) is providing simultaneous measurements of the radiation and cloud fields on a global basis to improve the understanding and modeling of the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. Cloud properties derived for CERES from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites are compared to ensure consistency between the products to ensure the reliability of the retrievals from multiple platforms at different times of day. Comparisons of cloud fraction, height, optical depth, phase, effective particle size, and ice and liquid water paths from the two satellites show excellent consistency. Initial calibration comparisons are also very favorable. Differences between the Aqua and Terra results are generally due to diurnally dependent changes in the clouds. Additional algorithm refinement is needed over the polar regions for Aqua and at night over those same areas for Terra. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.

Automated cloud classification using a ground based infra-red camera and texture analysis techniques

Science.gov (United States)

Rumi, Emal; Kerr, David; Coupland, Jeremy M.; Sandford, Andrew P.; Brettle, Mike J.

2013-10-01

Clouds play an important role in influencing the dynamics of local and global weather and climate conditions. Continuous monitoring of clouds is vital for weather forecasting and for air-traffic control. Convective clouds such as Towering Cumulus (TCU) and Cumulonimbus clouds (CB) are associated with thunderstorms, turbulence and atmospheric instability. Human observers periodically report the presence of CB and TCU clouds during operational hours at airports and observatories; however such observations are expensive and time limited. Robust, automatic classification of cloud type using infrared ground-based instrumentation offers the advantage of continuous, real-time (24/7) data capture and the representation of cloud structure in the form of a thermal map, which can greatly help to characterise certain cloud formations. The work presented here utilised a ground based infrared (8-14 μm) imaging device mounted on a pan/tilt unit for capturing high spatial resolution sky images. These images were processed to extract 45 separate textural features using statistical and spatial frequency based analytical techniques. These features were used to train a weighted k-nearest neighbour (KNN) classifier in order to determine cloud type. Ground truth data were obtained by inspection of images captured simultaneously from a visible wavelength colour camera at the same installation, with approximately the same field of view as the infrared device. These images were classified by a trained cloud observer. Results from the KNN classifier gave an encouraging success rate. A Probability of Detection (POD) of up to 90% with a Probability of False Alarm (POFA) as low as 16% was achieved.

Cloud screening Coastal Zone Color Scanner images using channel 5

Science.gov (United States)

Eckstein, B. A.; Simpson, J. J.

1991-01-01

Clouds are removed from Coastal Zone Color Scanner (CZCS) data using channel 5. Instrumentation problems require pre-processing of channel 5 before an intelligent cloud-screening algorithm can be used. For example, at intervals of about 16 lines, the sensor records anomalously low radiances. Moreover, the calibration equation yields negative radiances when the sensor records zero counts, and pixels corrupted by electronic overshoot must also be excluded. The remaining pixels may then be used in conjunction with the procedure of Simpson and Humphrey to determine the CZCS cloud mask. These results plus in situ observations of phytoplankton pigment concentration show that pre-processing and proper cloud-screening of CZCS data are necessary for accurate satellite-derived pigment concentrations. This is especially true in the coastal margins, where pigment content is high and image distortion associated with electronic overshoot is also present. The pre-processing algorithm is critical to obtaining accurate global estimates of pigment from spacecraft data.

3D change detection at street level using mobile laser scanning point clouds and terrestrial images

Science.gov (United States)

Qin, Rongjun; Gruen, Armin

2014-04-01

Automatic change detection and geo-database updating in the urban environment are difficult tasks. There has been much research on detecting changes with satellite and aerial images, but studies have rarely been performed at the street level, which is complex in its 3D geometry. Contemporary geo-databases include 3D street-level objects, which demand frequent data updating. Terrestrial images provides rich texture information for change detection, but the change detection with terrestrial images from different epochs sometimes faces problems with illumination changes, perspective distortions and unreliable 3D geometry caused by the lack of performance of automatic image matchers, while mobile laser scanning (MLS) data acquired from different epochs provides accurate 3D geometry for change detection, but is very expensive for periodical acquisition. This paper proposes a new method for change detection at street level by using combination of MLS point clouds and terrestrial images: the accurate but expensive MLS data acquired from an early epoch serves as the reference, and terrestrial images or photogrammetric images captured from an image-based mobile mapping system (MMS) at a later epoch are used to detect the geometrical changes between different epochs. The method will automatically mark the possible changes in each view, which provides a cost-efficient method for frequent data updating. The methodology is divided into several steps. In the first step, the point clouds are recorded by the MLS system and processed, with data cleaned and classified by semi-automatic means. In the second step, terrestrial images or mobile mapping images at a later epoch are taken and registered to the point cloud, and then point clouds are projected on each image by a weighted window based z-buffering method for view dependent 2D triangulation. In the next step, stereo pairs of the terrestrial images are rectified and re-projected between each other to check the geometrical

Observation of a cavitation cloud in tissue using correlation between ultrafast ultrasound images.

Science.gov (United States)

Prieur, Fabrice; Zorgani, Ali; Catheline, Stefan; Souchon, Rémi; Mestas, Jean-Louis; Lafond, Maxime; Lafon, Cyril

2015-07-01

The local application of ultrasound is known to improve drug intake by tumors. Cavitating bubbles are one of the contributing effects. A setup in which two ultrasound transducers are placed confocally is used to generate cavitation in ex vivo tissue. As the transducers emit a series of short excitation bursts, the evolution of the cavitation activity is monitored using an ultrafast ultrasound imaging system. The frame rate of the system is several thousands of images per second, which provides several tens of images between consecutive excitation bursts. Using the correlation between consecutive images for speckle tracking, a decorrelation of the imaging signal appears due to the creation, fast movement, and dissolution of the bubbles in the cavitation cloud. By analyzing this area of decorrelation, the cavitation cloud can be localized and the spatial extent of the cavitation activity characterized.

Green Cloud Computing: A Literature Survey

Directory of Open Access Journals (Sweden)

Laura-Diana Radu

2017-11-01

Full Text Available Cloud computing is a dynamic field of information and communication technologies (ICTs, introducing new challenges for environmental protection. Cloud computing technologies have a variety of application domains, since they offer scalability, are reliable and trustworthy, and offer high performance at relatively low cost. The cloud computing revolution is redesigning modern networking, and offering promising environmental protection prospects as well as economic and technological advantages. These technologies have the potential to improve energy efficiency and to reduce carbon footprints and (e-waste. These features can transform cloud computing into green cloud computing. In this survey, we review the main achievements of green cloud computing. First, an overview of cloud computing is given. Then, recent studies and developments are summarized, and environmental issues are specifically addressed. Finally, future research directions and open problems regarding green cloud computing are presented. This survey is intended to serve as up-to-date guidance for research with respect to green cloud computing.

Reconstruction of 3D Shapes of Opaque Cumulus Clouds from Airborne Multiangle Imaging: A Proof-of-Concept

Science.gov (United States)

Davis, A. B.; Bal, G.; Chen, J.

2015-12-01

Operational remote sensing of microphysical and optical cloud properties is invariably predicated on the assumption of plane-parallel slab geometry for the targeted cloud. The sole benefit of this often-questionable assumption about the cloud is that it leads to one-dimensional (1D) radiative transfer (RT)---a textbook, computationally tractable model. We present new results as evidence that, thanks to converging advances in 3D RT, inverse problem theory, algorithm implementation, and computer hardware, we are at the dawn of a new era in cloud remote sensing where we can finally go beyond the plane-parallel paradigm. Granted, the plane-parallel/1D RT assumption is reasonable for spatially extended stratiform cloud layers, as well as the smoothly distributed background aerosol layers. However, these 1D RT-friendly scenarios exclude cases that are critically important for climate physics. 1D RT---whence operational cloud remote sensing---fails catastrophically for cumuliform clouds that have fully 3D outer shapes and internal structures driven by shallow or deep convection. For these situations, the first order of business in a robust characterization by remote sensing is to abandon the slab geometry framework and determine the 3D geometry of the cloud, as a first step toward bone fide 3D cloud tomography. With this specific goal in mind, we deliver a proof-of-concept for an entirely new kind of remote sensing applicable to 3D clouds. It is based on highly simplified 3D RT and exploits multi-angular suites of cloud images at high spatial resolution. Airborne sensors like AirMSPI readily acquire such data. The key element of the reconstruction algorithm is a sophisticated solution of the nonlinear inverse problem via linearization of the forward model and an iteration scheme supported, where necessary, by adaptive regularization. Currently, the demo uses a 2D setting to show how either vertical profiles or horizontal slices of the cloud can be accurately reconstructed

COMPREHENSIVE COMPARISON OF TWO IMAGE-BASED POINT CLOUDS FROM AERIAL PHOTOS WITH AIRBORNE LIDAR FOR LARGE-SCALE MAPPING

Directory of Open Access Journals (Sweden)

E. Widyaningrum

2017-09-01

Full Text Available The integration of computer vision and photogrammetry to generate three-dimensional (3D information from images has contributed to a wider use of point clouds, for mapping purposes. Large-scale topographic map production requires 3D data with high precision and accuracy to represent the real conditions of the earth surface. Apart from LiDAR point clouds, the image-based matching is also believed to have the ability to generate reliable and detailed point clouds from multiple-view images. In order to examine and analyze possible fusion of LiDAR and image-based matching for large-scale detailed mapping purposes, point clouds are generated by Semi Global Matching (SGM and by Structure from Motion (SfM. In order to conduct comprehensive and fair comparison, this study uses aerial photos and LiDAR data that were acquired at the same time. Qualitative and quantitative assessments have been applied to evaluate LiDAR and image-matching point clouds data in terms of visualization, geometric accuracy, and classification result. The comparison results conclude that LiDAR is the best data for large-scale mapping.

The benefit of limb cloud imaging for infrared limb sounding of tropospheric trace gases

OpenAIRE

G. Heinemann; P. Preusse; R. Spang; S. Adams

2009-01-01

Advances in detector technology enable a new generation of infrared limb sounders to measure 2-D images of the atmosphere. A proposed limb cloud imager (LCI) mode will detect clouds with a spatial resolution unprecedented for limb sounding. For the inference of temperature and trace gas distributions, detector pixels of the LCI have to be combined into super-pixels which provide the required signal-to-noise and information content for the retrievals. This study examines the extent to which tr...

Volunteered Cloud Computing for Disaster Management

Science.gov (United States)

Evans, J. D.; Hao, W.; Chettri, S. R.

2014-12-01

Disaster management relies increasingly on interpreting earth observations and running numerical models; which require significant computing capacity - usually on short notice and at irregular intervals. Peak computing demand during event detection, hazard assessment, or incident response may exceed agency budgets; however some of it can be met through volunteered computing, which distributes subtasks to participating computers via the Internet. This approach has enabled large projects in mathematics, basic science, and climate research to harness the slack computing capacity of thousands of desktop computers. This capacity is likely to diminish as desktops give way to battery-powered mobile devices (laptops, smartphones, tablets) in the consumer market; but as cloud computing becomes commonplace, it may offer significant slack capacity -- if its users are given an easy, trustworthy mechanism for participating. Such a "volunteered cloud computing" mechanism would also offer several advantages over traditional volunteered computing: tasks distributed within a cloud have fewer bandwidth limitations; granular billing mechanisms allow small slices of "interstitial" computing at no marginal cost; and virtual storage volumes allow in-depth, reversible machine reconfiguration. Volunteered cloud computing is especially suitable for "embarrassingly parallel" tasks, including ones requiring large data volumes: examples in disaster management include near-real-time image interpretation, pattern / trend detection, or large model ensembles. In the context of a major disaster, we estimate that cloud users (if suitably informed) might volunteer hundreds to thousands of CPU cores across a large provider such as Amazon Web Services. To explore this potential, we are building a volunteered cloud computing platform and targeting it to a disaster management context. Using a lightweight, fault-tolerant network protocol, this platform helps cloud users join parallel computing projects

Satellite Cloud and Radiative Property Processing and Distribution System on the NASA Langley ASDC OpenStack and OpenShift Cloud Platform

Science.gov (United States)

Nguyen, L.; Chee, T.; Palikonda, R.; Smith, W. L., Jr.; Bedka, K. M.; Spangenberg, D.; Vakhnin, A.; Lutz, N. E.; Walter, J.; Kusterer, J.

2017-12-01

Cloud Computing offers new opportunities for large-scale scientific data producers to utilize Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) IT resources to process and deliver data products in an operational environment where timely delivery, reliability, and availability are critical. The NASA Langley Research Center Atmospheric Science Data Center (ASDC) is building and testing a private and public facing cloud for users in the Science Directorate to utilize as an everyday production environment. The NASA SatCORPS (Satellite ClOud and Radiation Property Retrieval System) team processes and derives near real-time (NRT) global cloud products from operational geostationary (GEO) satellite imager datasets. To deliver these products, we will utilize the public facing cloud and OpenShift to deploy a load-balanced webserver for data storage, access, and dissemination. The OpenStack private cloud will host data ingest and computational capabilities for SatCORPS processing. This paper will discuss the SatCORPS migration towards, and usage of, the ASDC Cloud Services in an operational environment. Detailed lessons learned from use of prior cloud providers, specifically the Amazon Web Services (AWS) GovCloud and the Government Cloud administered by the Langley Managed Cloud Environment (LMCE) will also be discussed.

Study of the relations between cloud properties and atmospheric conditions using ground-based digital images

Science.gov (United States)

Bakalova, Kalinka

The aerosol constituents of the earth atmosphere are of great significance for the radiation budget and global climate of the planet. They are the precursors of clouds that in turn play an essential role in these processes and in the hydrological cycle of the Earth. Understanding the complex aerosol-cloud interactions requires a detailed knowledge of the dynamical processes moving the water vapor through the atmosphere, and of the physical mechanisms involved in the formation and growth of cloud particles. Ground-based observations on regional and short time scale provide valuable detailed information about atmospheric dynamics and cloud properties, and are used as a complementary tool to the global satellite observations. The objective of the present paper is to study the physical properties of clouds as displayed in ground-based visible images, and juxtapose them to the specific surface and atmospheric meteorological conditions. The observations are being carried out over the urban area of the city of Sofia, Bulgaria. The data obtained from visible images of clouds enable a quantitative description of texture and morphological features of clouds such as shape, thickness, motion, etc. These characteristics are related to cloud microphysical properties. The changes of relative humidity and the horizontal visibility are considered to be representative of the variations of the type (natural/manmade) and amount of the atmospheric aerosols near the earth surface, and potentially, the cloud drop number concentration. The atmospheric dynamics is accounted for by means of the values of the atmospheric pressure, temperature, wind velocity, etc., observed at the earth's surface. The advantage of ground-based observations of clouds compared to satellite ones is in the high spatial and temporal resolution of the obtained data about the lowermost cloud layer, which in turn is sensitive to the meteorological regimes that determine cloud formation and evolution. It turns out

Deep convective cloud characterizations from both broadband imager and hyperspectral infrared sounder measurements

Science.gov (United States)

Ai, Yufei; Li, Jun; Shi, Wenjing; Schmit, Timothy J.; Cao, Changyong; Li, Wanbiao

2017-02-01

Deep convective storms have contributed to airplane accidents, making them a threat to aviation safety. The most common method to identify deep convective clouds (DCCs) is using the brightness temperature difference (BTD) between the atmospheric infrared (IR) window band and the water vapor (WV) absorption band. The effectiveness of the BTD method for DCC detection is highly related to the spectral resolution and signal-to-noise ratio (SNR) of the WV band. In order to understand the sensitivity of BTD to spectral resolution and SNR for DCC detection, a BTD to noise ratio method using the difference between the WV and IR window radiances is developed to assess the uncertainty of DCC identification for different instruments. We examined the case of AirAsia Flight QZ8501. The brightness temperatures (Tbs) over DCCs from this case are simulated for BTD sensitivity studies by a fast forward radiative transfer model with an opaque cloud assumption for both broadband imager (e.g., Multifunction Transport Satellite imager, MTSAT-2 imager) and hyperspectral IR sounder (e.g., Atmospheric Infrared Sounder) instruments; we also examined the relationship between the simulated Tb and the cloud top height. Results show that despite the coarser spatial resolution, BTDs measured by a hyperspectral IR sounder are much more sensitive to high cloud tops than broadband BTDs. As demonstrated in this study, a hyperspectral IR sounder can identify DCCs with better accuracy.

pCloud: A Cloud-based Power Market Simulation Environment

Energy Technology Data Exchange (ETDEWEB)

Rudkevich, Aleksandr; Goldis, Evgeniy

2012-12-02

This research conducted by the Newton Energy Group, LLC (NEG) is dedicated to the development of pCloud: a Cloud-based Power Market Simulation Environment. pCloud is offering power industry stakeholders the capability to model electricity markets and is organized around the Software as a Service (SaaS) concept -- a software application delivery model in which software is centrally hosted and provided to many users via the internet. During the Phase I of this project NEG developed a prototype design for pCloud as a SaaS-based commercial service offering, system architecture supporting that design, ensured feasibility of key architecture's elements, formed technological partnerships and negotiated commercial agreements with partners, conducted market research and other related activities and secured funding for continue development of pCloud between the end of Phase I and beginning of Phase II, if awarded. Based on the results of Phase I activities, NEG has established that the development of a cloud-based power market simulation environment within the Windows Azure platform is technologically feasible, can be accomplished within the budget and timeframe available through the Phase II SBIR award with additional external funding. NEG believes that pCloud has the potential to become a game-changing technology for the modeling and analysis of electricity markets. This potential is due to the following critical advantages of pCloud over its competition: - Standardized access to advanced and proven power market simulators offered by third parties. - Automated parallelization of simulations and dynamic provisioning of computing resources on the cloud. This combination of automation and scalability dramatically reduces turn-around time while offering the capability to increase the number of analyzed scenarios by a factor of 10, 100 or even 1000. - Access to ready-to-use data and to cloud-based resources leading to a reduction in software, hardware, and IT costs

Securing the Cloud Cloud Computer Security Techniques and Tactics

CERN Document Server

Winkler, Vic (JR)

2011-01-01

As companies turn to cloud computing technology to streamline and save money, security is a fundamental concern. Loss of certain control and lack of trust make this transition difficult unless you know how to handle it. Securing the Cloud discusses making the move to the cloud while securing your peice of it! The cloud offers felxibility, adaptability, scalability, and in the case of security-resilience. This book details the strengths and weaknesses of securing your company's information with different cloud approaches. Attacks can focus on your infrastructure, communications network, data, o

Cloud computing patterns fundamentals to design, build, and manage cloud applications

CERN Document Server

Fehling, Christoph; Retter, Ralph; Schupeck, Walter; Arbitter, Peter

2014-01-01

The current work provides CIOs, software architects, project managers, developers, and cloud strategy initiatives with a set of architectural patterns that offer nuggets of advice on how to achieve common cloud computing-related goals. The cloud computing patterns capture knowledge and experience in an abstract format that is independent of concrete vendor products. Readers are provided with a toolbox to structure cloud computing strategies and design cloud application architectures. By using this book cloud-native applications can be implemented and best suited cloud vendors and tooling for i

Enabling outsourcing XDS for imaging on the public cloud.

Science.gov (United States)

Ribeiro, Luís S; Rodrigues, Renato P; Costa, Carlos; Oliveira, José Luís

2013-01-01

Picture Archiving and Communication System (PACS) has been the main paradigm in supporting medical imaging workflows during the last decades. Despite its consolidation, the appearance of Cross-Enterprise Document Sharing for imaging (XDS-I), within IHE initiative, constitutes a great opportunity to readapt PACS workflow for inter-institutional data exchange. XDS-I provides a centralized discovery of medical imaging and associated reports. However, the centralized XDS-I actors (document registry and repository) must be deployed in a trustworthy node in order to safeguard patient privacy, data confidentiality and integrity. This paper presents XDS for Protected Imaging (XDS-p), a new approach to XDS-I that is capable of being outsourced (e.g. Cloud Computing) while maintaining privacy, confidentiality, integrity and legal concerns about patients' medical information.

Automatic registration of Iphone images to LASER point clouds of the urban structures using shape features

Directory of Open Access Journals (Sweden)

B. Sirmacek

2013-10-01

Full Text Available Fusion of 3D airborne laser (LIDAR data and terrestrial optical imagery can be applied in 3D urban modeling and model up-dating. The most challenging aspect of the fusion procedure is registering the terrestrial optical images on the LIDAR point clouds. In this article, we propose an approach for registering these two different data from different sensor sources. As we use iPhone camera images which are taken in front of the interested urban structure by the application user and the high resolution LIDAR point clouds of the acquired by an airborne laser sensor. After finding the photo capturing position and orientation from the iPhone photograph metafile, we automatically select the area of interest in the point cloud and transform it into a range image which has only grayscale intensity levels according to the distance from the image acquisition position. We benefit from local features for registering the iPhone image to the generated range image. In this article, we have applied the registration process based on local feature extraction and graph matching. Finally, the registration result is used for facade texture mapping on the 3D building surface mesh which is generated from the LIDAR point cloud. Our experimental results indicate possible usage of the proposed algorithm framework for 3D urban map updating and enhancing purposes.

The Measurement of cloud velocity using the pulsed laser and image tracking technique

Energy Technology Data Exchange (ETDEWEB)

Kwon, Seong-Ouk; Baik, Seung-Hoon; Park, Seung-Kyu; Park, Nak-Gyu; Kim, Dong-lyul; Ahn, Yong-Jin [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2015-05-15

The height of the clouds is also important for the three dimensional radiative interaction of aerosols and clouds, since the radiative effects vary strongly depending whether the cloud is above, below or even embedded in an aerosol layer. Clouds play an important role in climate change, in the prediction of local weather, and also in aviation safety when instrument assisted flying is unavailable. Presently, various ground-based instruments used for the measurements of the cloud base height or velocity. Lidar techniques are powerful and have many applications in climate studies, including the clouds' temperature measurement, the aerosol particle properties, etc. Otherwise, it is very circumscribed in cloud velocity measurements In this paper, we propose a new method to measure the cloud velocity. In this paper, we presented a method for the measurement of the cloud altitude and velocity using lidar's range detection and the tracking system. For the lidar system, we used an injection-seeded pulsed Nd:YAG laser as the transmitter to measure the distance to the target clouds. We used the DIC system to track the cloud image and calculate the actual displacement per unit time. The configured lidar system acquired the lidar signal of clouds at a distance of about 4 km. The developed fast correlation algorithm of the tracking, which is used to track the fast moving cloud relatively, was efficient for measuring the cloud velocity in real time. The measurement values had a linear distribution.

Content-based histopathology image retrieval using CometCloud.

Science.gov (United States)

Qi, Xin; Wang, Daihou; Rodero, Ivan; Diaz-Montes, Javier; Gensure, Rebekah H; Xing, Fuyong; Zhong, Hua; Goodell, Lauri; Parashar, Manish; Foran, David J; Yang, Lin

2014-08-26

The development of digital imaging technology is creating extraordinary levels of accuracy that provide support for improved reliability in different aspects of the image analysis, such as content-based image retrieval, image segmentation, and classification. This has dramatically increased the volume and rate at which data are generated. Together these facts make querying and sharing non-trivial and render centralized solutions unfeasible. Moreover, in many cases this data is often distributed and must be shared across multiple institutions requiring decentralized solutions. In this context, a new generation of data/information driven applications must be developed to take advantage of the national advanced cyber-infrastructure (ACI) which enable investigators to seamlessly and securely interact with information/data which is distributed across geographically disparate resources. This paper presents the development and evaluation of a novel content-based image retrieval (CBIR) framework. The methods were tested extensively using both peripheral blood smears and renal glomeruli specimens. The datasets and performance were evaluated by two pathologists to determine the concordance. The CBIR algorithms that were developed can reliably retrieve the candidate image patches exhibiting intensity and morphological characteristics that are most similar to a given query image. The methods described in this paper are able to reliably discriminate among subtle staining differences and spatial pattern distributions. By integrating a newly developed dual-similarity relevance feedback module into the CBIR framework, the CBIR results were improved substantially. By aggregating the computational power of high performance computing (HPC) and cloud resources, we demonstrated that the method can be successfully executed in minutes on the Cloud compared to weeks using standard computers. In this paper, we present a set of newly developed CBIR algorithms and validate them using two

The role of ensemble-based statistics in variational assimilation of cloud-affected observations from infrared imagers

Science.gov (United States)

Hacker, Joshua; Vandenberghe, Francois; Jung, Byoung-Jo; Snyder, Chris

2017-04-01

Effective assimilation of cloud-affected radiance observations from space-borne imagers, with the aim of improving cloud analysis and forecasting, has proven to be difficult. Large observation biases, nonlinear observation operators, and non-Gaussian innovation statistics present many challenges. Ensemble-variational data assimilation (EnVar) systems offer the benefits of flow-dependent background error statistics from an ensemble, and the ability of variational minimization to handle nonlinearity. The specific benefits of ensemble statistics, relative to static background errors more commonly used in variational systems, have not been quantified for the problem of assimilating cloudy radiances. A simple experiment framework is constructed with a regional NWP model and operational variational data assimilation system, to provide the basis understanding the importance of ensemble statistics in cloudy radiance assimilation. Restricting the observations to those corresponding to clouds in the background forecast leads to innovations that are more Gaussian. The number of large innovations is reduced compared to the more general case of all observations, but not eliminated. The Huber norm is investigated to handle the fat tails of the distributions, and allow more observations to be assimilated without the need for strict background checks that eliminate them. Comparing assimilation using only ensemble background error statistics with assimilation using only static background error statistics elucidates the importance of the ensemble statistics. Although the cost functions in both experiments converge to similar values after sufficient outer-loop iterations, the resulting cloud water, ice, and snow content are greater in the ensemble-based analysis. The subsequent forecasts from the ensemble-based analysis also retain more condensed water species, indicating that the local environment is more supportive of clouds. In this presentation we provide details that explain the

Development of Multi-Sensor Global Cloud and Radiance Composites for DSCOVR EPIC Imager with Subpixel Definition

Science.gov (United States)

Khlopenkov, K. V.; Duda, D. P.; Thieman, M. M.; Sun-Mack, S.; Su, W.; Minnis, P.; Bedka, K. M.

2017-12-01

The Deep Space Climate Observatory (DSCOVR) is designed to study the daytime Earth radiation budget by means of onboard Earth Polychromatic Imaging Camera (EPIC) and National Institute of Standards and Technology Advanced Radiometer (NISTAR). EPIC imager observes in several shortwave bands (317-780 nm), while NISTAR measures the top-of-atmosphere (TOA) whole-disk radiance in shortwave and total broadband windows. Calculation of albedo and outgoing longwave flux requires a high-resolution scene identification such as the radiance observations and cloud property retrievals from low earth orbit and geostationary satellite imagers. These properties have to be co-located with EPIC imager pixels to provide scene identification and to select anisotropic directional models, which are then used to adjust the NISTAR-measured radiance and subsequently obtain the global daytime shortwave and longwave fluxes. This work presents an algorithm for optimal merging of selected radiances and cloud properties derived from multiple satellite imagers to obtain seamless global hourly composites at 5-km resolution. The highest quality observation is selected by means of an aggregated rating which incorporates several factors such as the nearest time relative to EPIC observation, lowest viewing zenith angle, and others. This process provides a smoother transition and avoids abrupt changes in the merged composite data. Higher spatial accuracy in the composite product is achieved by using the inverse mapping with gradient search during reprojection and bicubic interpolation for pixel resampling. The composite data are subsequently remapped into the EPIC-view domain by convolving composite pixels with the EPIC point spread function (PSF) defined with a half-pixel accuracy. Within every EPIC footprint, the PSF-weighted average radiances and cloud properties are computed for each cloud phase and then stored within five data subsets (clear-sky, water cloud, ice cloud, total cloud, and no

Auto-Scaling of Geo-Based Image Processing in an OpenStack Cloud Computing Environment

OpenAIRE

Sanggoo Kang; Kiwon Lee

2016-01-01

Cloud computing is a base platform for the distribution of large volumes of data and high-performance image processing on the Web. Despite wide applications in Web-based services and their many benefits, geo-spatial applications based on cloud computing technology are still developing. Auto-scaling realizes automatic scalability, i.e., the scale-out and scale-in processing of virtual servers in a cloud computing environment. This study investigates the applicability of auto-scaling to geo-bas...

New Satellite Estimates of Mixed-Phase Cloud Properties: A Synergistic Approach for Application to Global Satellite Imager Data

Science.gov (United States)

Smith, W. L., Jr.; Spangenberg, D.; Fleeger, C.; Sun-Mack, S.; Chen, Y.; Minnis, P.

2016-12-01

Determining accurate cloud properties horizontally and vertically over a full range of time and space scales is currently next to impossible using data from either active or passive remote sensors or from modeling systems. Passive satellite imagers provide horizontal and temporal resolution of clouds, but little direct information on vertical structure. Active sensors provide vertical resolution but limited spatial and temporal coverage. Cloud models embedded in NWP can produce realistic clouds but often not at the right time or location. Thus, empirical techniques that integrate information from multiple observing and modeling systems are needed to more accurately characterize clouds and their impacts. Such a strategy is employed here in a new cloud water content profiling technique developed for application to satellite imager cloud retrievals based on VIS, IR and NIR radiances. Parameterizations are developed to relate imager retrievals of cloud top phase, optical depth, effective radius and temperature to ice and liquid water content profiles. The vertical structure information contained in the parameterizations is characterized climatologically from cloud model analyses, aircraft observations, ground-based remote sensing data, and from CloudSat and CALIPSO. Thus, realistic cloud-type dependent vertical structure information (including guidance on cloud phase partitioning) circumvents poor assumptions regarding vertical homogeneity that plague current passive satellite retrievals. This paper addresses mixed phase cloud conditions for clouds with glaciated tops including those associated with convection and mid-latitude storm systems. Novel outcomes of our approach include (1) simultaneous retrievals of ice and liquid water content and path, which are validated with active sensor, microwave and in-situ data, and yield improved global cloud climatologies, and (2) new estimates of super-cooled LWC, which are demonstrated in aviation safety applications and

Automatic Cloud and Shadow Detection in Optical Satellite Imagery Without Using Thermal Bands—Application to Suomi NPP VIIRS Images over Fennoscandia

Directory of Open Access Journals (Sweden)

Eija Parmes

2017-08-01

Full Text Available In land monitoring applications, clouds and shadows are considered noise that should be removed as automatically and quickly as possible, before further analysis. This paper presents a method to detect clouds and shadows in Suomi NPP satellite’s VIIRS (Visible Infrared Imaging Radiometer Suite satellite images. The proposed cloud and shadow detection method has two distinct features when compared to many other methods. First, the method does not use the thermal bands and can thus be applied to other sensors which do not contain thermal channels, such as Sentinel-2 data. Secondly, the method uses the ratio between blue and green reflectance to detect shadows. Seven hundred and forty-seven VIIRS images over Fennoscandia from August 2014 to April 2016 were processed to train and develop the method. Twenty four points from every tenth of the images were used in accuracy assessment. These 1752 points were interpreted visually to cloud, cloud shadow and clear classes, then compared to the output of the cloud and shadow detection. The comparison on VIIRS images showed 94.2% correct detection rates and 11.1% false alarms for clouds, and respectively 36.1% and 82.7% for shadows. The results on cloud detection were similar to state-of-the-art methods. Shadows showed correctly on the northern edge of the clouds, but many shadows were wrongly assigned to other classes in some cases (e.g., to water class on lake and forest boundary, or with shadows over cloud. This may be due to the low spatial resolution of VIIRS images, where shadows are only a few pixels wide and contain lots of mixed pixels.

Image velocimetry for clouds with relaxation labeling based on deformation consistency

International Nuclear Information System (INIS)

Horinouchi, Takeshi; Murakami, Shin-ya; Yamazaki, Atsushi; Kouyama, Toru; Ogohara, Kazunori; Yamada, Manabu; Watanabe, Shigeto

2017-01-01

Correlation-based cloud tracking has been extensively used to measure atmospheric winds, but still difficulty remains. In this study, aiming at developing a cloud tracking system for Akatsuki, an artificial satellite orbiting Venus, a formulation is developed for improving the relaxation labeling technique to select appropriate peaks of cross-correlation surfaces which tend to have multiple peaks. The formulation makes an explicit use of consistency inherent in the type of cross-correlation method where template sub-images are slid without deformation; if the resultant motion vectors indicate a too-large deformation, it is contradictory to the assumption of the method. The deformation consistency is exploited further to develop two post processes; one clusters the motion vectors into groups within each of which the consistency is perfect, and the other extends the groups using the original candidate lists. These processes are useful to eliminate erroneous vectors, distinguish motion vectors at different altitudes, and detect phase velocities of waves in fluids such as atmospheric gravity waves. As a basis of the relaxation labeling and the post processes as well as uncertainty estimation, the necessity to find isolated (well-separated) peaks of cross-correlation surfaces is argued, and an algorithm to realize it is presented. All the methods are implemented, and their effectiveness is demonstrated with initial images obtained by the ultraviolet imager onboard Akatsuki. Since the deformation consistency regards the logical consistency inherent in template matching methods, it should have broad application beyond cloud tracking. (paper)

Image velocimetry for clouds with relaxation labeling based on deformation consistency

Science.gov (United States)

Horinouchi, Takeshi; Murakami, Shin-ya; Kouyama, Toru; Ogohara, Kazunori; Yamazaki, Atsushi; Yamada, Manabu; Watanabe, Shigeto

2017-08-01

Correlation-based cloud tracking has been extensively used to measure atmospheric winds, but still difficulty remains. In this study, aiming at developing a cloud tracking system for Akatsuki, an artificial satellite orbiting Venus, a formulation is developed for improving the relaxation labeling technique to select appropriate peaks of cross-correlation surfaces which tend to have multiple peaks. The formulation makes an explicit use of consistency inherent in the type of cross-correlation method where template sub-images are slid without deformation; if the resultant motion vectors indicate a too-large deformation, it is contradictory to the assumption of the method. The deformation consistency is exploited further to develop two post processes; one clusters the motion vectors into groups within each of which the consistency is perfect, and the other extends the groups using the original candidate lists. These processes are useful to eliminate erroneous vectors, distinguish motion vectors at different altitudes, and detect phase velocities of waves in fluids such as atmospheric gravity waves. As a basis of the relaxation labeling and the post processes as well as uncertainty estimation, the necessity to find isolated (well-separated) peaks of cross-correlation surfaces is argued, and an algorithm to realize it is presented. All the methods are implemented, and their effectiveness is demonstrated with initial images obtained by the ultraviolet imager onboard Akatsuki. Since the deformation consistency regards the logical consistency inherent in template matching methods, it should have broad application beyond cloud tracking.

Cloud and radiance measurements with the VIS/NIR Daylight Whole Sky Imager at Lindenberg (Germany)

Energy Technology Data Exchange (ETDEWEB)

Feister, U. [Deutscher Wetterdienst, Meteorologisches Observatorium Lindenberg (Germany); Shields, J. [Scripps Inst. of Oceanography, Univ. of California, San Diego (United States)

2005-10-01

Ground-based cloud data acquired with the whole sky imager (WSI) are analyzed in relation to measurements of solar radiation performed at the Lindenberg Meteorological Observatory. Cloud fractions derived by the cloud detection algorithm from WSI images acquired during daylight hours between 2002 and 2004 are compared with conventional cloud observations for the two sites Potsdam and Lindenberg, and also with ceilometer data of cloud-base heights at Lindenberg. The comparison statistics are discussed in the context of different principles of measurement. A few case studies illustrate the strong scattering effect of clouds on solar radiance and irradiance measured at the ground in different spectral regions. Particularly clouds close to the apparent position of the sun lead to strong enhancements of solar diffuse irradiance incident on horizontal planes and hemispheres that substantially exceed corresponding clear-sky values. Irradiances derived from WSI sky radiance fields are shown in comparison to pyranometer data of diffuse irradiance and radiative transfer model calculations performed for clear sky conditions. Examples of spectral sky radiances with moving contrails illustrate the significant enhancement the contrails have compared to clear sky, even though they may have a relatively small direct effect on global irradiance values. As contrails are observed at Lindenberg for about 18 to 19% of daylight hours, and part of them become clouds, the indirect impact of these changes on solar irradiance received at the ground may not be negligible. (orig.)

Molecular Hydrogen Images of Star Forming Regions in the Magellanic Clouds

Science.gov (United States)

Probst, Ronald G.; Barba, R.; Bolatto, A.; Chu, Y.; Points, S.; Rubio, M.; Smith, C.

2011-01-01

The Large and Small Magellanic Clouds exhibit a variety of star formation physics with multiple phase components in low metallicity, gas rich environments. The 10 K, 100 K, and 104 K regimes are well explored. We are imaging LMC and SMC star forming regions in 2.12 micron H2 emission which arises in the 1000 K transition zone of molecular clouds. This is an NOAO Survey program using the widefield IR camera NEWFIRM on the CTIO 4-m Blanco telescope during its limited southern deployment. The data set will have immediate morphological applications and will provide target selection for followup infrared spectroscopy. We will provide a public archive of fully calibrated images with no proprietary period. NOAO is operated by the Association of Universities for Research in Astronomy, under cooperative agreement with the National Science Foundation.

Cloud Computing for radiologists.

Science.gov (United States)

Kharat, Amit T; Safvi, Amjad; Thind, Ss; Singh, Amarjit

2012-07-01

Cloud computing is a concept wherein a computer grid is created using the Internet with the sole purpose of utilizing shared resources such as computer software, hardware, on a pay-per-use model. Using Cloud computing, radiology users can efficiently manage multimodality imaging units by using the latest software and hardware without paying huge upfront costs. Cloud computing systems usually work on public, private, hybrid, or community models. Using the various components of a Cloud, such as applications, client, infrastructure, storage, services, and processing power, Cloud computing can help imaging units rapidly scale and descale operations and avoid huge spending on maintenance of costly applications and storage. Cloud computing allows flexibility in imaging. It sets free radiology from the confines of a hospital and creates a virtual mobile office. The downsides to Cloud computing involve security and privacy issues which need to be addressed to ensure the success of Cloud computing in the future.

Cloud Computing for radiologists

International Nuclear Information System (INIS)

Kharat, Amit T; Safvi, Amjad; Thind, SS; Singh, Amarjit

2012-01-01

Cloud computing is a concept wherein a computer grid is created using the Internet with the sole purpose of utilizing shared resources such as computer software, hardware, on a pay-per-use model. Using Cloud computing, radiology users can efficiently manage multimodality imaging units by using the latest software and hardware without paying huge upfront costs. Cloud computing systems usually work on public, private, hybrid, or community models. Using the various components of a Cloud, such as applications, client, infrastructure, storage, services, and processing power, Cloud computing can help imaging units rapidly scale and descale operations and avoid huge spending on maintenance of costly applications and storage. Cloud computing allows flexibility in imaging. It sets free radiology from the confines of a hospital and creates a virtual mobile office. The downsides to Cloud computing involve security and privacy issues which need to be addressed to ensure the success of Cloud computing in the future

Cloud computing for radiologists

Directory of Open Access Journals (Sweden)

Amit T Kharat

2012-01-01

Full Text Available Cloud computing is a concept wherein a computer grid is created using the Internet with the sole purpose of utilizing shared resources such as computer software, hardware, on a pay-per-use model. Using Cloud computing, radiology users can efficiently manage multimodality imaging units by using the latest software and hardware without paying huge upfront costs. Cloud computing systems usually work on public, private, hybrid, or community models. Using the various components of a Cloud, such as applications, client, infrastructure, storage, services, and processing power, Cloud computing can help imaging units rapidly scale and descale operations and avoid huge spending on maintenance of costly applications and storage. Cloud computing allows flexibility in imaging. It sets free radiology from the confines of a hospital and creates a virtual mobile office. The downsides to Cloud computing involve security and privacy issues which need to be addressed to ensure the success of Cloud computing in the future.

Chargeback for cloud services.

NARCIS (Netherlands)

Baars, T.; Khadka, R.; Stefanov, H.; Jansen, S.; Batenburg, R.; Heusden, E. van

2014-01-01

With pay-per-use pricing models, elastic scaling of resources, and the use of shared virtualized infrastructures, cloud computing offers more efficient use of capital and agility. To leverage the advantages of cloud computing, organizations have to introduce cloud-specific chargeback practices.

Current Trends in Cloud Computing A Survey of Cloud Computing Systems

OpenAIRE

Harjit Singh

2012-01-01

Cloud computing that has become an increasingly important trend, is a virtualization technology that uses the internet and central remote servers to offer the sharing of resources that include infrastructures, software, applications and business processes to the market environment to fulfill the elastic demand. In today’s competitive environment, the service vitality, elasticity, choices and flexibility offered by this scalable technology are too attractive that makes the cloud computing to i...

Cloud Computing and Its Applications in GIS

Science.gov (United States)

Kang, Cao

2011-12-01

Cloud computing is a novel computing paradigm that offers highly scalable and highly available distributed computing services. The objectives of this research are to: 1. analyze and understand cloud computing and its potential for GIS; 2. discover the feasibilities of migrating truly spatial GIS algorithms to distributed computing infrastructures; 3. explore a solution to host and serve large volumes of raster GIS data efficiently and speedily. These objectives thus form the basis for three professional articles. The first article is entitled "Cloud Computing and Its Applications in GIS". This paper introduces the concept, structure, and features of cloud computing. Features of cloud computing such as scalability, parallelization, and high availability make it a very capable computing paradigm. Unlike High Performance Computing (HPC), cloud computing uses inexpensive commodity computers. The uniform administration systems in cloud computing make it easier to use than GRID computing. Potential advantages of cloud-based GIS systems such as lower barrier to entry are consequently presented. Three cloud-based GIS system architectures are proposed: public cloud- based GIS systems, private cloud-based GIS systems and hybrid cloud-based GIS systems. Public cloud-based GIS systems provide the lowest entry barriers for users among these three architectures, but their advantages are offset by data security and privacy related issues. Private cloud-based GIS systems provide the best data protection, though they have the highest entry barriers. Hybrid cloud-based GIS systems provide a compromise between these extremes. The second article is entitled "A cloud computing algorithm for the calculation of Euclidian distance for raster GIS". Euclidean distance is a truly spatial GIS algorithm. Classical algorithms such as the pushbroom and growth ring techniques require computational propagation through the entire raster image, which makes it incompatible with the distributed nature

Astronomy in the Cloud: Using MapReduce for Image Co-Addition

Science.gov (United States)

Wiley, K.; Connolly, A.; Gardner, J.; Krughoff, S.; Balazinska, M.; Howe, B.; Kwon, Y.; Bu, Y.

2011-03-01

In the coming decade, astronomical surveys of the sky will generate tens of terabytes of images and detect hundreds of millions of sources every night. The study of these sources will involve computation challenges such as anomaly detection and classification and moving-object tracking. Since such studies benefit from the highest-quality data, methods such as image co-addition, i.e., astrometric registration followed by per-pixel summation, will be a critical preprocessing step prior to scientific investigation. With a requirement that these images be analyzed on a nightly basis to identify moving sources such as potentially hazardous asteroids or transient objects such as supernovae, these data streams present many computational challenges. Given the quantity of data involved, the computational load of these problems can only be addressed by distributing the workload over a large number of nodes. However, the high data throughput demanded by these applications may present scalability challenges for certain storage architectures. One scalable data-processing method that has emerged in recent years is MapReduce, and in this article we focus on its popular open-source implementation called Hadoop. In the Hadoop framework, the data are partitioned among storage attached directly to worker nodes, and the processing workload is scheduled in parallel on the nodes that contain the required input data. A further motivation for using Hadoop is that it allows us to exploit cloud computing resources: i.e., platforms where Hadoop is offered as a service. We report on our experience of implementing a scalable image-processing pipeline for the SDSS imaging database using Hadoop. This multiterabyte imaging data set provides a good testbed for algorithm development, since its scope and structure approximate future surveys. First, we describe MapReduce and how we adapted image co-addition to the MapReduce framework. Then we describe a number of optimizations to our basic approach

Cloud security mechanisms

OpenAIRE

2014-01-01

Cloud computing has brought great benefits in cost and flexibility for provisioning services. The greatest challenge of cloud computing remains however the question of security. The current standard tools in access control mechanisms and cryptography can only partly solve the security challenges of cloud infrastructures. In the recent years of research in security and cryptography, novel mechanisms, protocols and algorithms have emerged that offer new ways to create secure services atop cloud...

Assessing the consistency of UAV-derived point clouds and images acquired at different altitudes

Science.gov (United States)

Ozcan, O.

2016-12-01

Unmanned Aerial Vehicles (UAVs) offer several advantages in terms of cost and image resolution compared to terrestrial photogrammetry and satellite remote sensing system. Nowadays, UAVs that bridge the gap between the satellite scale and field scale applications were initiated to be used in various application areas to acquire hyperspatial and high temporal resolution imageries due to working capacity and acquiring in a short span of time with regard to conventional photogrammetry methods. UAVs have been used for various fields such as for the creation of 3-D earth models, production of high resolution orthophotos, network planning, field monitoring and agricultural lands as well. Thus, geometric accuracy of orthophotos and volumetric accuracy of point clouds are of capital importance for land surveying applications. Correspondingly, Structure from Motion (SfM) photogrammetry, which is frequently used in conjunction with UAV, recently appeared in environmental sciences as an impressive tool allowing for the creation of 3-D models from unstructured imagery. In this study, it was aimed to reveal the spatial accuracy of the images acquired from integrated digital camera and the volumetric accuracy of Digital Surface Models (DSMs) which were derived from UAV flight plans at different altitudes using SfM methodology. Low-altitude multispectral overlapping aerial photography was collected at the altitudes of 30 to 100 meters and georeferenced with RTK-GPS ground control points. These altitudes allow hyperspatial imagery with the resolutions of 1-5 cm depending upon the sensor being used. Preliminary results revealed that the vertical comparison of UAV-derived point clouds with respect to GPS measurements pointed out an average distance at cm-level. Larger values are found in areas where instantaneous changes in surface are present.

HIERARCHICAL REGULARIZATION OF POLYGONS FOR PHOTOGRAMMETRIC POINT CLOUDS OF OBLIQUE IMAGES

Directory of Open Access Journals (Sweden)

L. Xie

2017-05-01

Full Text Available Despite the success of multi-view stereo (MVS reconstruction from massive oblique images in city scale, only point clouds and triangulated meshes are available from existing MVS pipelines, which are topologically defect laden, free of semantical information and hard to edit and manipulate interactively in further applications. On the other hand, 2D polygons and polygonal models are still the industrial standard. However, extraction of the 2D polygons from MVS point clouds is still a non-trivial task, given the fact that the boundaries of the detected planes are zigzagged and regularities, such as parallel and orthogonal, cannot preserve. Aiming to solve these issues, this paper proposes a hierarchical polygon regularization method for the photogrammetric point clouds from existing MVS pipelines, which comprises of local and global levels. After boundary points extraction, e.g. using alpha shapes, the local level is used to consolidate the original points, by refining the orientation and position of the points using linear priors. The points are then grouped into local segments by forward searching. In the global level, regularities are enforced through a labeling process, which encourage the segments share the same label and the same label represents segments are parallel or orthogonal. This is formulated as Markov Random Field and solved efficiently. Preliminary results are made with point clouds from aerial oblique images and compared with two classical regularization methods, which have revealed that the proposed method are more powerful in abstracting a single building and is promising for further 3D polygonal model reconstruction and GIS applications.

Jupiter's Multi-level Clouds

Science.gov (United States)

1997-01-01

Clouds and hazes at various altitudes within the dynamic Jovian atmosphere are revealed by multi-color imaging taken by the Near-Infrared Mapping Spectrometer (NIMS) onboard the Galileo spacecraft. These images were taken during the second orbit (G2) on September 5, 1996 from an early-morning vantage point 2.1 million kilometers (1.3 million miles) above Jupiter. They show the planet's appearance as viewed at various near-infrared wavelengths, with distinct differences due primarily to variations in the altitudes and opacities of the cloud systems. The top left and right images, taken at 1.61 microns and 2.73 microns respectively, show relatively clear views of the deep atmosphere, with clouds down to a level about three times the atmospheric pressure at the Earth's surface.By contrast, the middle image in top row, taken at 2.17 microns, shows only the highest altitude clouds and hazes. This wavelength is severely affected by the absorption of light by hydrogen gas, the main constituent of Jupiter's atmosphere. Therefore, only the Great Red Spot, the highest equatorial clouds, a small feature at mid-northern latitudes, and thin, high photochemical polar hazes can be seen. In the lower left image, at 3.01 microns, deeper clouds can be seen dimly against gaseous ammonia and methane absorption. In the lower middle image, at 4.99 microns, the light observed is the planet's own indigenous heat from the deep, warm atmosphere.The false color image (lower right) succinctly shows various cloud and haze levels seen in the Jovian atmosphere. This image indicates the temperature and altitude at which the light being observed is produced. Thermally-rich red areas denote high temperatures from photons in the deep atmosphere leaking through minimal cloud cover; green denotes cool temperatures of the tropospheric clouds; blue denotes cold of the upper troposphere and lower stratosphere. The polar regions appear purplish, because small-particle hazes allow leakage and reflectivity

Cloud Computing Bible

CERN Document Server

Sosinsky, Barrie

2010-01-01

The complete reference guide to the hot technology of cloud computingIts potential for lowering IT costs makes cloud computing a major force for both IT vendors and users; it is expected to gain momentum rapidly with the launch of Office Web Apps later this year. Because cloud computing involves various technologies, protocols, platforms, and infrastructure elements, this comprehensive reference is just what you need if you'll be using or implementing cloud computing.Cloud computing offers significant cost savings by eliminating upfront expenses for hardware and software; its growing popularit

IBM SmartCloud essentials

CERN Document Server

Schouten, Edwin

2013-01-01

A practical, user-friendly guide that provides an introduction to cloud computing using IBM SmartCloud, along with a thorough understanding of resource management in a cloud environment.This book is great for anyone who wants to get a grasp of what cloud computing is and what IBM SmartCloud has to offer. If you are an IT specialist, IT architect, system administrator, or a developer who wants to thoroughly understand the cloud computing resource model, this book is ideal for you. No prior knowledge of cloud computing is expected.

A comparison of performance of automatic cloud coverage assessment algorithm for Formosat-2 image using clustering-based and spatial thresholding methods

Science.gov (United States)

Hsu, Kuo-Hsien

2012-11-01

Formosat-2 image is a kind of high-spatial-resolution (2 meters GSD) remote sensing satellite data, which includes one panchromatic band and four multispectral bands (Blue, Green, Red, near-infrared). An essential sector in the daily processing of received Formosat-2 image is to estimate the cloud statistic of image using Automatic Cloud Coverage Assessment (ACCA) algorithm. The information of cloud statistic of image is subsequently recorded as an important metadata for image product catalog. In this paper, we propose an ACCA method with two consecutive stages: preprocessing and post-processing analysis. For pre-processing analysis, the un-supervised K-means classification, Sobel's method, thresholding method, non-cloudy pixels reexamination, and cross-band filter method are implemented in sequence for cloud statistic determination. For post-processing analysis, Box-Counting fractal method is implemented. In other words, the cloud statistic is firstly determined via pre-processing analysis, the correctness of cloud statistic of image of different spectral band is eventually cross-examined qualitatively and quantitatively via post-processing analysis. The selection of an appropriate thresholding method is very critical to the result of ACCA method. Therefore, in this work, We firstly conduct a series of experiments of the clustering-based and spatial thresholding methods that include Otsu's, Local Entropy(LE), Joint Entropy(JE), Global Entropy(GE), and Global Relative Entropy(GRE) method, for performance comparison. The result shows that Otsu's and GE methods both perform better than others for Formosat-2 image. Additionally, our proposed ACCA method by selecting Otsu's method as the threshoding method has successfully extracted the cloudy pixels of Formosat-2 image for accurate cloud statistic estimation.

Cloud computing strategies

CERN Document Server

Chorafas, Dimitris N

2011-01-01

A guide to managing cloud projects, Cloud Computing Strategies provides the understanding required to evaluate the technology and determine how it can be best applied to improve business and enhance your overall corporate strategy. Based on extensive research, it examines the opportunities and challenges that loom in the cloud. It explains exactly what cloud computing is, what it has to offer, and calls attention to the important issues management needs to consider before passing the point of no return regarding financial commitments.

Cloud Control

Science.gov (United States)

Ramaswami, Rama; Raths, David; Schaffhauser, Dian; Skelly, Jennifer

2011-01-01

For many IT shops, the cloud offers an opportunity not only to improve operations but also to align themselves more closely with their schools' strategic goals. The cloud is not a plug-and-play proposition, however--it is a complex, evolving landscape that demands one's full attention. Security, privacy, contracts, and contingency planning are all…

Diurnal, Seasonal, and Interannual Variations of Cloud Properties Derived for CERES From Imager Data

Science.gov (United States)

Minnis, Patrick; Young, David F.; Sun-Mack, Sunny; Trepte, Qing Z.; Chen, Yan; Brown, Richard R.; Gibson, Sharon; Heck, Patrick W.

2004-01-01

Simultaneous measurement of the radiation and cloud fields on a global basis is a key component in the effort to understand and model the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. The NASA Clouds and Earth s Radiant Energy System (CERES) Project, begun in 1998, is meeting this need. Broadband shortwave (SW) and longwave radiance measurements taken by the CERES scanners at resolutions between 10 and 20 km on the Tropical Rainfall Measuring Mission (TRMM), Terra, and Aqua satellites are matched to simultaneous retrievals of cloud height, phase, particle size, water path, and optical depth OD from the TRMM Visible Infrared Scanner (VIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Besides aiding the interpretation of the broadband radiances, the CERES cloud properties are valuable for understanding cloud variations at a variety of scales. In this paper, the resulting CERES cloud data taken to date are averaged at several temporal scales to examine the temporal and spatial variability of the cloud properties on a global scale at a 1 resolution.

Pricing Schemes in Cloud Computing: An Overview

OpenAIRE

Artan Mazrekaj; Isak Shabani; Besmir Sejdiu

2016-01-01

Cloud Computing is one of the technologies with rapid development in recent years where there is increasing interest in industry and academia. This technology enables many services and resources for end users. With the rise of cloud services number of companies that offer various services in cloud infrastructure is increased, thus creating a competition on prices in the global market. Cloud Computing providers offer more services to their clients ranging from infrastructure as a service (IaaS...

Security Architecture of Cloud Computing

OpenAIRE

V.KRISHNA REDDY; Dr. L.S.S.REDDY

2011-01-01

The Cloud Computing offers service over internet with dynamically scalable resources. Cloud Computing services provides benefits to the users in terms of cost and ease of use. Cloud Computing services need to address the security during the transmission of sensitive data and critical applications to shared and public cloud environments. The cloud environments are scaling large for data processing and storage needs. Cloud computing environment have various advantages as well as disadvantages o...

Cloud Security in 21st Century: Current Key Issues in Service Models on Cloud Computing and how to overcome them

OpenAIRE

Sharma, Supern

2011-01-01

Cloud computing is a disruptive innovation which offers new ways to increase capacity and capabilities of the organization’s IT infrastructure. In last few years cloud computing has taken computing industry by storm and many organizations are using cloud computing services to increase the efficiency, decrease their IT budgets and play an important role in defining the IT strategy of their business. Cloud computing offers various benefits such as scalability, elasticity, reducing IT expenditur...

Developing national on-line services to annotate and analyse underwater imagery in a research cloud

Science.gov (United States)

Proctor, R.; Langlois, T.; Friedman, A.; Davey, B.

2017-12-01

Fish image annotation data is currently collected by various research, management and academic institutions globally (+100,000's hours of deployments) with varying degrees of standardisation and limited formal collaboration or data synthesis. We present a case study of how national on-line services, developed within a domain-oriented research cloud, have been used to annotate habitat images and synthesise fish annotation data sets collected using Autonomous Underwater Vehicles (AUVs) and baited remote underwater stereo-video (stereo-BRUV). Two developing software tools have been brought together in the marine science cloud to provide marine biologists with a powerful service for image annotation. SQUIDLE+ is an online platform designed for exploration, management and annotation of georeferenced images & video data. It provides a flexible annotation framework allowing users to work with their preferred annotation schemes. We have used SQUIDLE+ to sample the habitat composition and complexity of images of the benthos collected using stereo-BRUV. GlobalArchive is designed to be a centralised repository of aquatic ecological survey data with design principles including ease of use, secure user access, flexible data import, and the collection of any sampling and image analysis information. To easily share and synthesise data we have implemented data sharing protocols, including Open Data and synthesis Collaborations, and a spatial map to explore global datasets and filter to create a synthesis. These tools in the science cloud, together with a virtual desktop analysis suite offering python and R environments offer an unprecedented capability to deliver marine biodiversity information of value to marine managers and scientists alike.

Jupiter's Great Red Spot upper cloud morphology and dynamics from JunoCam images

Science.gov (United States)

Sanchez-Lavega, A.; Hueso, R.; Eichstädt, G.; Orton, G.; Rogers, J.; Hansen, C. J.; Momary, T.; Tabataba-Vakili, F.

2017-12-01

We present an analysis of RGB color-composite images of the Great Red Spot (GRS) obtained with JunoCam during Juno's seventh close flyby (PJ7) on July 11, 2017. The images have been projected as 4 cylindrical maps with a resolution of 180 pixels per degree (about 7 km/pixel) spanning a temporal interval of 9 min 41s. The GRS shows a rich variety of cloud morphologies that reveal different dynamical processes in its interior. We consider three major regions. (1) An outer peripheral ring of homogeneous reddish clouds (width about 1,300 km) traces a laminar flow. A family of at least three packets of gravity waves with a mean wavelength of 75 km is present at the internal edge of the ring (in its northern side). They occupy an area of 2,500 km in length (East-West, EW) and 670 km in the North-South (NS) direction. Single clouds in the groups forming the wave have extents of 35 km EW and 70-135 km NS. (2) A large internal region of red clouds (width about 3,200 km) contains three morphologies: (a) fields of bright cumulus-like clusters, (b) long, dark curved filaments (about 7,000 km length with 100 km width), two of them converging into an arrowhead shape, and (c) individual anticyclonic vortices with radius of 500 km that grow due to the radial shear of the wind velocity in the GRS interior as previously measured. A cumulus cluster is conspicuous inside one such anticyclone. Each single cloud element is 50 km in size and the cluster has a 25-30 percent area coverage in cumulus-convective activity, presumably due to ammonia moist convection. (3) A central core has quasi-rectangular shape, extending about 5000 km EW and 3000 km NS, that is confined by elongated clouds distributed along its periphery. Its interior is filled with the redder clouds in the GRS that have a scale 100 km and form a turbulent pattern whose cloud orientations suggest three adjacent areas with alternating cyclonic-cyclonic-anticyclonic vorticity, each with radius 650-850 km.

Interferometric laser imaging for in-flight cloud droplet sizing

International Nuclear Information System (INIS)

Dunker, Christina; Roloff, Christoph; Grassmann, Arne

2016-01-01

A non-intrusive particle sizing method with a high spatial distribution is used to estimate cloud droplet spectra during flight test campaigns. The interferometric laser imaging for droplet sizing (ILIDS) method derives particle diameters of transparent spheres by evaluating the out-of-focus image patterns. This sizing approach requires a polarized monochromatic light source, a camera including an objective lens with a slit aperture, a synchronization unit and a processing tool for data evaluation. These components are adapted to a flight test environment to enable the microphysical investigation of different cloud genera. The present work addresses the design and specifications of ILIDS system, flight test preparation and selected results obtained in the lower and middle troposphere. The research platform was a Dornier Do228-101 commuter aircraft at the DLR Flight Operation Center in Braunschweig. It was equipped with the required instrumentation including a high-energy laser as the light source. A comprehensive data set of around 71 800 ILIDS images was acquired over the course of five flights. The data evaluation of the characteristic ILIDS fringe patterns relies, among other things, on a relationship between the fringe spacing and the diameter of the particle. The simplest way to extract this information from a pattern is by fringe counting, which is not viable for such an extensive number of data. A brief contrasting comparison of evaluation methods based on frequency analysis by means of fast Fourier transform and on correlation methods such as minimum quadratic difference is used to encompass the limits and accuracy of the ILIDS method for such applications. (paper)

Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based Mean-Shift Algorithm.

Science.gov (United States)

Yang, Mengzhao; Song, Wei; Mei, Haibin

2017-07-23

The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS) storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient.

Cloud top structure of Venus revealed by Subaru/COMICS mid-infrared images

Science.gov (United States)

Sato, T. M.; Sagawa, H.; Kouyama, T.; Mitsuyama, K.; Satoh, T.; Ohtsuki, S.; Ueno, M.; Kasaba, Y.; Nakamura, M.; Imamura, T.

2014-11-01

We have investigated the cloud top structure of Venus by analyzing ground-based images taken at the mid-infrared wavelengths of 8.66 μm and 11.34 μm. Venus at a solar phase angle of ∼90°, with the morning terminator in view, was observed by the Cooled Mid-Infrared Camera and Spectrometer (COMICS), mounted on the 8.2-m Subaru Telescope, during the period October 25-29, 2007. The disk-averaged brightness temperatures for the observation period are ∼230 K and ∼238 K at 8.66 μm and 11.34 μm, respectively. The obtained images with good signal-to-noise ratio and with high spatial resolution (∼200 km at the sub-observer point) provide several important findings. First, we present observational evidence, for the first time, of the possibility that the westward rotation of the polar features (the hot polar spots and the surrounding cold collars) is synchronized between the northern and southern hemispheres. Second, after high-pass filtering, the images reveal that streaks and mottled and patchy patterns are distributed over the entire disk, with typical amplitudes of ∼0.5 K, and vary from day to day. The detected features, some of which are similar to those seen in past UV images, result from inhomogeneities of both the temperature and the cloud top altitude. Third, the equatorial center-to-limb variations of brightness temperatures have a systematic day-night asymmetry, except those on October 25, that the dayside brightness temperatures are higher than the nightside brightness temperatures by 0-4 K under the same viewing geometry. Such asymmetry would be caused by the propagation of the migrating semidiurnal tide. Finally, by applying the lapse rates deduced from previous studies, we demonstrate that the equatorial center-to-limb curves in the two spectral channels give access to two parameters: the cloud scale height H and the cloud top altitude zc. The acceptable models for data on October 25 are obtained at H = 2.4-4.3 km and zc = 66-69 km; this supports

Issues in automatic combination of cloud services

NARCIS (Netherlands)

Nguyen, D.K.; Lelli, F.; Papazoglou, M.; van den Heuvel, W.J.A.M.

2012-01-01

Current cloud service description languages envision the ability to automatically combine cloud service offerings across multiple abstraction layers, i.e. software, platform, and infrastructure service offerings, to achieve a common shared business goal. However, only little effort has been spent in

A cloud collaborative medical image platform oriented by social network

Science.gov (United States)

Muniz, Frederico B.; Araújo, Luciano V.; Nunes, Fátima L. S.

2017-03-01

Computer-aided diagnosis systems using medical images and three-dimensional models as input data have greatly expanded and developed, but in terms of building suitable image databases to assess them, the challenge remains. Although there are some image databases available for this purpose, they are generally limited to certain types of exams or contain a limited number of medical cases. The objective of this work is to present the concepts and the development of a collaborative platform for sharing medical images and three-dimensional models, providing a resource to share and increase the number of images available for researchers. The collaborative cloud platform, called CATALYZER, aims to increase the availability and sharing of graphic objects, including 3D images, and their reports that are essential for research related to medical images. A survey conducted with researchers and health professionals indicated that this could be an innovative approach in the creation of medical image databases, providing a wider variety of cases together with a considerable amount of shared information among its users.

A ROBUST REGISTRATION ALGORITHM FOR POINT CLOUDS FROM UAV IMAGES FOR CHANGE DETECTION

Directory of Open Access Journals (Sweden)

A. Al-Rawabdeh

2016-06-01

Full Text Available Landslides are among the major threats to urban landscape and manmade infrastructure. They often cause economic losses, property damages, and loss of lives. Temporal monitoring data of landslides from different epochs empowers the evaluation of landslide progression. Alignment of overlapping surfaces from two or more epochs is crucial for the proper analysis of landslide dynamics. The traditional methods for point-cloud-based landslide monitoring rely on using a variation of the Iterative Closest Point (ICP registration procedure to align any reconstructed surfaces from different epochs to a common reference frame. However, sometimes the ICP-based registration can fail or may not provide sufficient accuracy. For example, point clouds from different epochs might fit to local minima due to lack of geometrical variability within the data. Also, manual interaction is required to exclude any non-stable areas from the registration process. In this paper, a robust image-based registration method is introduced for the simultaneous evaluation of all registration parameters. This includes the Interior Orientation Parameters (IOPs of the camera and the Exterior Orientation Parameters (EOPs of the involved images from all available observation epochs via a bundle block adjustment with self-calibration. Next, a semi-global dense matching technique is implemented to generate dense 3D point clouds for each epoch using the images captured in a particular epoch separately. The normal distances between any two consecutive point clouds can then be readily computed, because the point clouds are already effectively co-registered. A low-cost DJI Phantom II Unmanned Aerial Vehicle (UAV was customised and used in this research for temporal data collection over an active soil creep area in Lethbridge, Alberta, Canada. The customisation included adding a GPS logger and a Large-Field-Of-View (LFOV action camera which facilitated capturing high-resolution geo-tagged images

a Robust Registration Algorithm for Point Clouds from Uav Images for Change Detection

Science.gov (United States)

Al-Rawabdeh, A.; Al-Gurrani, H.; Al-Durgham, K.; Detchev, I.; He, F.; El-Sheimy, N.; Habib, A.

2016-06-01

Landslides are among the major threats to urban landscape and manmade infrastructure. They often cause economic losses, property damages, and loss of lives. Temporal monitoring data of landslides from different epochs empowers the evaluation of landslide progression. Alignment of overlapping surfaces from two or more epochs is crucial for the proper analysis of landslide dynamics. The traditional methods for point-cloud-based landslide monitoring rely on using a variation of the Iterative Closest Point (ICP) registration procedure to align any reconstructed surfaces from different epochs to a common reference frame. However, sometimes the ICP-based registration can fail or may not provide sufficient accuracy. For example, point clouds from different epochs might fit to local minima due to lack of geometrical variability within the data. Also, manual interaction is required to exclude any non-stable areas from the registration process. In this paper, a robust image-based registration method is introduced for the simultaneous evaluation of all registration parameters. This includes the Interior Orientation Parameters (IOPs) of the camera and the Exterior Orientation Parameters (EOPs) of the involved images from all available observation epochs via a bundle block adjustment with self-calibration. Next, a semi-global dense matching technique is implemented to generate dense 3D point clouds for each epoch using the images captured in a particular epoch separately. The normal distances between any two consecutive point clouds can then be readily computed, because the point clouds are already effectively co-registered. A low-cost DJI Phantom II Unmanned Aerial Vehicle (UAV) was customised and used in this research for temporal data collection over an active soil creep area in Lethbridge, Alberta, Canada. The customisation included adding a GPS logger and a Large-Field-Of-View (LFOV) action camera which facilitated capturing high-resolution geo-tagged images in two epochs

Time Series UAV Image-Based Point Clouds for Landslide Progression Evaluation Applications.

Science.gov (United States)

Al-Rawabdeh, Abdulla; Moussa, Adel; Foroutan, Marzieh; El-Sheimy, Naser; Habib, Ayman

2017-10-18

Landslides are major and constantly changing threats to urban landscapes and infrastructure. It is essential to detect and capture landslide changes regularly. Traditional methods for monitoring landslides are time-consuming, costly, dangerous, and the quality and quantity of the data is sometimes unable to meet the necessary requirements of geotechnical projects. This motivates the development of more automatic and efficient remote sensing approaches for landslide progression evaluation. Automatic change detection involving low-altitude unmanned aerial vehicle image-based point clouds, although proven, is relatively unexplored, and little research has been done in terms of accounting for volumetric changes. In this study, a methodology for automatically deriving change displacement rates, in a horizontal direction based on comparisons between extracted landslide scarps from multiple time periods, has been developed. Compared with the iterative closest projected point (ICPP) registration method, the developed method takes full advantage of automated geometric measuring, leading to fast processing. The proposed approach easily processes a large number of images from different epochs and enables the creation of registered image-based point clouds without the use of extensive ground control point information or further processing such as interpretation and image correlation. The produced results are promising for use in the field of landslide research.

Retrieval of Cloud Properties for Partially Cloud-Filled Pixels During CRYSTAL-FACE

Science.gov (United States)

Nguyen, L.; Minnis, P.; Smith, W. L.; Khaiyer, M. M.; Heck, P. W.; Sun-Mack, S.; Uttal, T.; Comstock, J.

2003-12-01

Partially cloud-filled pixels can be a significant problem for remote sensing of cloud properties. Generally, the optical depth and effective particle sizes are often too small or too large, respectively, when derived from radiances that are assumed to be overcast but contain radiation from both clear and cloud areas within the satellite imager field of view. This study presents a method for reducing the impact of such partially cloud field pixels by estimating the cloud fraction within each pixel using higher resolution visible (VIS, 0.65mm) imager data. Although the nominal resolution for most channels on the Geostationary Operational Environmental Satellite (GOES) imager and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra are 4 and 1 km, respectively, both instruments also take VIS channel data at 1 km and 0.25 km, respectively. Thus, it may be possible to obtain an improved estimate of cloud fraction within the lower resolution pixels by using the information contained in the higher resolution VIS data. GOES and MODIS multi-spectral data, taken during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL-FACE), are analyzed with the algorithm used for the Atmospheric Radiation Measurement Program (ARM) and the Clouds and Earth's Radiant Energy System (CERES) to derive cloud amount, temperature, height, phase, effective particle size, optical depth, and water path. Normally, the algorithm assumes that each pixel is either entirely clear or cloudy. In this study, a threshold method is applied to the higher resolution VIS data to estimate the partial cloud fraction within each low-resolution pixel. The cloud properties are then derived from the observed low-resolution radiances using the cloud cover estimate to properly extract the radiances due only to the cloudy part of the scene. This approach is applied to both GOES and MODIS data to estimate the improvement in the retrievals for each

Blueprinting Approach in Support of Cloud Computing

Directory of Open Access Journals (Sweden)

Willem-Jan van den Heuvel

2012-03-01

Full Text Available Current cloud service offerings, i.e., Software-as-a-service (SaaS, Platform-as-a-service (PaaS and Infrastructure-as-a-service (IaaS offerings are often provided as monolithic, one-size-fits-all solutions and give little or no room for customization. This limits the ability of Service-based Application (SBA developers to configure and syndicate offerings from multiple SaaS, PaaS, and IaaS providers to address their application requirements. Furthermore, combining different independent cloud services necessitates a uniform description format that facilitates the design, customization, and composition. Cloud Blueprinting is a novel approach that allows SBA developers to easily design, configure and deploy virtual SBA payloads on virtual machines and resource pools on the cloud. We propose the Blueprint concept as a uniform abstract description for cloud service offerings that may cross different cloud computing layers, i.e., SaaS, PaaS and IaaS. To support developers with the SBA design and development in the cloud, this paper introduces a formal Blueprint Template for unambiguously describing a blueprint, as well as a Blueprint Lifecycle that guides developers through the manipulation, composition and deployment of different blueprints for an SBA. Finally, the empirical evaluation of the blueprinting approach within an EC’s FP7 project is reported and an associated blueprint prototype implementation is presented.

THE VALUE OF CLOUD COMPUTING IN THE BUSINESS ENVIRONMENT

OpenAIRE

Mircea GEORGESCU; Marian MATEI

2013-01-01

Without any doubt, cloud computing has become one of the most significant trends in any enterprise, not only for IT businesses. Besides the fact that the cloud can offer access to low cost, considerably flexible computing resources, cloud computing also provides the capacity to create a new relationship between business entities and corporate IT departments. The value added to the business environment is given by the balanced use of resources, offered by cloud computing. The cloud mentality i...

Disaster damage detection through synergistic use of deep learning and 3D point cloud features derived from very high resolution oblique aerial images, and multiple-kernel-learning

Science.gov (United States)

Vetrivel, Anand; Gerke, Markus; Kerle, Norman; Nex, Francesco; Vosselman, George

2018-06-01

Oblique aerial images offer views of both building roofs and façades, and thus have been recognized as a potential source to detect severe building damages caused by destructive disaster events such as earthquakes. Therefore, they represent an important source of information for first responders or other stakeholders involved in the post-disaster response process. Several automated methods based on supervised learning have already been demonstrated for damage detection using oblique airborne images. However, they often do not generalize well when data from new unseen sites need to be processed, hampering their practical use. Reasons for this limitation include image and scene characteristics, though the most prominent one relates to the image features being used for training the classifier. Recently features based on deep learning approaches, such as convolutional neural networks (CNNs), have been shown to be more effective than conventional hand-crafted features, and have become the state-of-the-art in many domains, including remote sensing. Moreover, often oblique images are captured with high block overlap, facilitating the generation of dense 3D point clouds - an ideal source to derive geometric characteristics. We hypothesized that the use of CNN features, either independently or in combination with 3D point cloud features, would yield improved performance in damage detection. To this end we used CNN and 3D features, both independently and in combination, using images from manned and unmanned aerial platforms over several geographic locations that vary significantly in terms of image and scene characteristics. A multiple-kernel-learning framework, an effective way for integrating features from different modalities, was used for combining the two sets of features for classification. The results are encouraging: while CNN features produced an average classification accuracy of about 91%, the integration of 3D point cloud features led to an additional

A secure online image trading system for untrusted cloud environments.

Science.gov (United States)

Munadi, Khairul; Arnia, Fitri; Syaryadhi, Mohd; Fujiyoshi, Masaaki; Kiya, Hitoshi

2015-01-01

In conventional image trading systems, images are usually stored unprotected on a server, rendering them vulnerable to untrusted server providers and malicious intruders. This paper proposes a conceptual image trading framework that enables secure storage and retrieval over Internet services. The process involves three parties: an image publisher, a server provider, and an image buyer. The aim is to facilitate secure storage and retrieval of original images for commercial transactions, while preventing untrusted server providers and unauthorized users from gaining access to true contents. The framework exploits the Discrete Cosine Transform (DCT) coefficients and the moment invariants of images. Original images are visually protected in the DCT domain, and stored on a repository server. Small representation of the original images, called thumbnails, are generated and made publicly accessible for browsing. When a buyer is interested in a thumbnail, he/she sends a query to retrieve the visually protected image. The thumbnails and protected images are matched using the DC component of the DCT coefficients and the moment invariant feature. After the matching process, the server returns the corresponding protected image to the buyer. However, the image remains visually protected unless a key is granted. Our target application is the online market, where publishers sell their stock images over the Internet using public cloud servers.

CERN Computing Colloquium | Hidden in the Clouds: New Ideas in Cloud Computing | 30 May

CERN Multimedia

2013-01-01

by Dr. Shevek (NEBULA) Thursday 30 May 2013 from 2 p.m. to 4 p.m. at CERN ( 40-S2-D01 - Salle Dirac ) Abstract: Cloud computing has become a hot topic. But 'cloud' is no newer in 2013 than MapReduce was in 2005: We've been doing both for years. So why is cloud more relevant today than it ever has been? In this presentation, we will introduce the (current) central thesis of cloud computing, and explore how and why (or even whether) the concept has evolved. While we will cover a little light background, our primary focus will be on the consequences, corollaries and techniques introduced by some of the leading cloud developers and organizations. We each have a different deployment model, different applications and workloads, and many of us are still learning to efficiently exploit the platform services offered by a modern implementation. The discussion will offer the opportunity to share these experiences and help us all to realize the benefits of cloud computing to the ful...

Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC)

Science.gov (United States)

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2018-01-01

This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud temperature threshold based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (clouds the error is mostly limited to within 10%, although for thin clouds (COT cloud masking and cloud temperature retrievals are not considered in this study. PMID:29619116

Software engineering frameworks for the cloud computing paradigm

CERN Document Server

Mahmood, Zaigham

2013-01-01

This book presents the latest research on Software Engineering Frameworks for the Cloud Computing Paradigm, drawn from an international selection of researchers and practitioners. The book offers both a discussion of relevant software engineering approaches and practical guidance on enterprise-wide software deployment in the cloud environment, together with real-world case studies. Features: presents the state of the art in software engineering approaches for developing cloud-suitable applications; discusses the impact of the cloud computing paradigm on software engineering; offers guidance an

An Automatic Cloud Detection Method for ZY-3 Satellite

Directory of Open Access Journals (Sweden)

CHEN Zhenwei

2015-03-01

Full Text Available Automatic cloud detection for optical satellite remote sensing images is a significant step in the production system of satellite products. For the browse images cataloged by ZY-3 satellite, the tree discriminate structure is adopted to carry out cloud detection. The image was divided into sub-images and their features were extracted to perform classification between clouds and grounds. However, due to the high complexity of clouds and surfaces and the low resolution of browse images, the traditional classification algorithms based on image features are of great limitations. In view of the problem, a prior enhancement processing to original sub-images before classification was put forward in this paper to widen the texture difference between clouds and surfaces. Afterwards, with the secondary moment and first difference of the images, the feature vectors were extended in multi-scale space, and then the cloud proportion in the image was estimated through comprehensive analysis. The presented cloud detection algorithm has already been applied to the ZY-3 application system project, and the practical experiment results indicate that this algorithm is capable of promoting the accuracy of cloud detection significantly.

VENUS CLOUD MORPHOLOGY AND MOTIONS FROM GROUND-BASED IMAGES AT THE TIME OF THE AKATSUKI ORBIT INSERTION

Energy Technology Data Exchange (ETDEWEB)

Sánchez-Lavega, A.; Hueso, R.; Pérez-Hoyos, S.; Mendikoa, I.; Rojas, J. F. [Departamento de Física Aplicada I, Escuela de Ingeniería de Bilbao, Universidad del País Vasco UPV /EHU, Plaza Ingeniero Torres Quevedo, E-48013 Bilbao (Spain); Peralta, J.; Lee, Y. J. [Institute of Space and Astronautical Science (ISAS/JAXA), Sagamihara, Kanagawa (Japan); Gomez-Forrellad, J. M. [Fundació Observatori Esteve Duran, Montseny 46, E-08553 Seva, Barcelona (Spain); Horinouchi, T. [Faculty of Environment Earth Science, Hokkaido University, Hokkaido (Japan); Watanabe, S., E-mail: agustin.sanchez@ehu.es [Department of Cosmoscience, Hokkaido University, Hokkaido (Japan)

2016-12-10

We report Venus image observations around the two maximum elongations of the planet at 2015 June and October. From these images we describe the global atmospheric dynamics and cloud morphology in the planet before the arrival of JAXA’s Akatsuki mission on 2015 December 7. The majority of the images were acquired at ultraviolet wavelengths (380–410 nm) using small telescopes. The Venus dayside was also observed with narrowband filters at other wavelengths (890 nm, 725–950 nm, 1.435 μ m CO{sub 2} band) using the instrument PlanetCam-UPV/EHU at the 2.2 m telescope in Calar Alto Observatory. In all cases, the lucky imaging methodology was used to improve the spatial resolution of the images over the atmospheric seeing. During the April–June period, the morphology of the upper cloud showed an irregular and chaotic texture with a well-developed equatorial dark belt (afternoon hemisphere), whereas during October–December the dynamical regime was dominated by planetary-scale waves (Y-horizontal, C-reversed, and ψ -horizontal features) formed by long streaks, and banding suggesting more stable conditions. Measurements of the zonal wind velocity with cloud tracking in the latitude range from 50°N to 50°S shows agreement with retrievals from previous works.

FOREST Unbiased Galactic plane Imaging survey with the Nobeyama 45 m telescope (FUGIN): Molecular clouds toward W 33; possible evidence for a cloud-cloud collision triggering O star formation

Science.gov (United States)

Kohno, Mikito; Torii, Kazufumi; Tachihara, Kengo; Umemoto, Tomofumi; Minamidani, Tetsuhiro; Nishimura, Atsushi; Fujita, Shinji; Matsuo, Mitsuhiro; Yamagishi, Mitsuyoshi; Tsuda, Yuya; Kuriki, Mika; Kuno, Nario; Ohama, Akio; Hattori, Yusuke; Sano, Hidetoshi; Yamamoto, Hiroaki; Fukui, Yasuo

2018-05-01

We observed molecular clouds in the W 33 high-mass star-forming region associated with compact and extended H II regions using the NANTEN2 telescope as well as the Nobeyama 45 m telescope in the J = 1-0 transitions of 12CO, 13CO, and C18O as part of the FOREST Unbiased Galactic plane Imaging survey with the Nobeyama 45 m telescope (FUGIN) legacy survey. We detected three velocity components at 35 km s-1, 45 km s-1, and 58 km s-1. The 35 km s-1 and 58 km s-1 clouds are likely to be physically associated with W 33 because of the enhanced 12CO J = 3-2 to J = 1-0 intensity ratio as R_3-2/1-0} > 1.0 due to the ultraviolet irradiation by OB stars, and morphological correspondence between the distributions of molecular gas and the infrared and radio continuum emissions excited by high-mass stars. The two clouds show complementary distributions around W 33. The velocity separation is too large to be gravitationally bound, and yet not explained by expanding motion by stellar feedback. Therefore, we discuss whether a cloud-cloud collision scenario likely explains the high-mass star formation in W 33.

Cloud ERP and Cloud Accounting Software in Romania

Directory of Open Access Journals (Sweden)

Gianina MIHAI

2015-05-01

Full Text Available Nowadays, Cloud Computing becomes a more and more fashionable concept in the IT environment. There is no unanimous opinion on the definition of this concept, as it covers several versions of the newly emerged stage in the IT. But in fact, Cloud Computing should not suggest anything else than simplicity. Thus, in short, simple terms, Cloud Computing can be defined as a solution to use external IT resources (servers, storage media, applications and services, via Internet. Cloud computing is nothing more than the promise of an easy accessible technology. If the promise will eventually turn into something certain yet remains to be seen. In our opinion it is too early to make an assertion. In this article, our purpose is to find out what is the Romanian offer of ERP and Accounting software applications in Cloud and / or as services in SaaS version. Thus, we conducted an extensive study whose results we’ll present in the following.

Comparison Between CCCM and CloudSat Radar-Lidar (RL) Cloud and Radiation Products

Science.gov (United States)

Ham, Seung-Hee; Kato, Seiji; Rose, Fred G.; Sun-Mack, Sunny

2015-01-01

To enhance cloud properties, LaRC and CIRA developed each combination algorithm for obtained properties from passive, active and imager in A-satellite constellation. When comparing global cloud fraction each other, LaRC-produced CERES-CALIPSO-CloudSat-MODIS (CCCM) products larger low-level cloud fraction over tropic ocean, while CIRA-produced Radar-Lidar (RL) shows larger mid-level cloud fraction for high latitude region. The reason for different low-level cloud fraction is due to different filtering method of lidar-detected cloud layers. Meanwhile difference in mid-level clouds is occurred due to different priority of cloud boundaries from lidar and radar.

Cloud classification in a mediterranean location using radiation data and sky images

International Nuclear Information System (INIS)

Martinez-Chico, M.; Batlles, F.J.; Bosch, J.L.

2011-01-01

Knowledge regarding the solar radiation reaching the earth's surface and its geographical distribution is very important for the use of solar energy as a resource to produce electricity. Therefore, a proper assessment of available solar resource is particularly important to determine the placement and operation of solar thermal power plants. To perform this analysis correctly, it is necessary to determine the main factors influencing the radiation reaching the earth's surface, such as the earth's geometry, terrain, and atmospheric attenuation by gases, particles and clouds. Among these factors, it is important to emphasise the role of clouds as the main attenuating factor of radiation. Information about the amount and type of clouds present in the sky is therefore necessary to analyse both their attenuation levels and the prevalence of different sky conditions. Cloud cover is characterised according to attenuation levels, using the beam transmittance (k b , ratio of direct radiation incident on the surface to the extraterrestrial solar radiation) and hemispherical sky images. An analysis of the frequency and duration of each type of cloud cover blocking the sun's disk is also performed. Results show prevailing sky situations that make the studied area very suitable for the use of solar energy systems. -- Highlights: → Beam transmittance index k b have been used successfully to classify the cloud cover. → The proposed classification has been used to study a Mediterranean location in south-eastern Spain. → Percentage of cloudless/cloudy situations showed a good potential for solar energy applications in the studied area.

Ditching the Disc: The Effects of Cloud-Based Image Sharing on Department Efficiency and Report Turnaround Times in Mammography.

Science.gov (United States)

Morgan, Matthew B; Young, Elizabeth; Harada, Scott; Winkler, Nicole; Riegert, Joanna; Jones, Tony; Hu, Nan; Stein, Matthew

2017-12-01

In screening mammography, accessing prior examination images is crucial for accurate diagnosis and avoiding false-positives. When women visit multiple institutions for their screens, these "outside" examinations must be retrieved for comparison. Traditionally, prior images are obtained by faxing requests to other institutions and waiting for standard mail (film or CD-ROM), which can greatly delay report turnaround times. Recently, advancements in cloud-based image transfer technology have opened up more efficient options for examination transfer between institutions. The objective of this study was to evaluate the effect of cloud-based image transfer on mammography department workflow, time required to obtain prior images, and report turnaround times. Sixty screening examinations requiring prior images were placed into two groups (30 each). The control group used the standard institutional protocol for requesting prior images: faxing requests and waiting for mailed examinations. The experimental group used a cloud-based transfer for both requesting and receiving examinations. The mean number of days between examination request and examination receipt was measured for both groups and compared. The mean number of days from examination request to receipt was 6.08 days (SD 3.50) in the control group compared with 3.16 days (SD 3.95) in the experimental group. Using a cloud-based image transfer to obtain prior mammograms resulted in an average reduction of 2.92 days (P = .0361; 95% confidence interval 0.20-5.65) between examination request and receipt. This improvement in system efficiency is relevant for interpreting radiologists working to improve reporting times and for patients anxious to receive their mammography results. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Removal of Optically Thick Clouds from Multi-Spectral Satellite Images Using Multi-Frequency SAR Data

Directory of Open Access Journals (Sweden)

Robert Eckardt

2013-06-01

Full Text Available This study presents a method for the reconstruction of pixels contaminated by optical thick clouds in multi-spectral Landsat images using multi-frequency SAR data. A number of reconstruction techniques have already been proposed in the scientific literature. However, all of the existing techniques have certain limitations. In order to overcome these limitations, we expose the Closest Spectral Fit (CSF method proposed by Meng et al. to a new, synergistic approach using optical and SAR data. Therefore, the term Closest Feature Vector (CFV is introduced. The technique facilitates an elegant way to avoid radiometric distortions in the course of image reconstruction. Furthermore the cloud cover removal is independent from underlying land cover types and assumptions on seasonality, etc. The methodology is applied to mono-temporal, multi-frequency SAR data from TerraSAR-X (X-Band, ERS (C-Band and ALOS Palsar (L-Band. This represents a way of thinking about Radar data not as foreign, but as additional data source in multi-spectral remote sensing. For the assessment of the image restoration performance, an experimental framework is established and a statistical evaluation protocol is designed. The results show the potential of a synergistic usage of multi-spectral and SAR data to overcome the loss of data due to cloud cover.

Unveiling aerosol-cloud interactions - Part 1: Cloud contamination in satellite products enhances the aerosol indirect forcing estimate

Science.gov (United States)

Christensen, Matthew W.; Neubauer, David; Poulsen, Caroline A.; Thomas, Gareth E.; McGarragh, Gregory R.; Povey, Adam C.; Proud, Simon R.; Grainger, Roy G.

2017-11-01

Increased concentrations of aerosol can enhance the albedo of warm low-level cloud. Accurately quantifying this relationship from space is challenging due in part to contamination of aerosol statistics near clouds. Aerosol retrievals near clouds can be influenced by stray cloud particles in areas assumed to be cloud-free, particle swelling by humidification, shadows and enhanced scattering into the aerosol field from (3-D radiative transfer) clouds. To screen for this contamination we have developed a new cloud-aerosol pairing algorithm (CAPA) to link cloud observations to the nearest aerosol retrieval within the satellite image. The distance between each aerosol retrieval and nearest cloud is also computed in CAPA. Results from two independent satellite imagers, the Advanced Along-Track Scanning Radiometer (AATSR) and Moderate Resolution Imaging Spectroradiometer (MODIS), show a marked reduction in the strength of the intrinsic aerosol indirect radiative forcing when selecting aerosol pairs that are located farther away from the clouds (-0.28±0.26 W m-2) compared to those including pairs that are within 15 km of the nearest cloud (-0.49±0.18 W m-2). The larger aerosol optical depths in closer proximity to cloud artificially enhance the relationship between aerosol-loading, cloud albedo, and cloud fraction. These results suggest that previous satellite-based radiative forcing estimates represented in key climate reports may be exaggerated due to the inclusion of retrieval artefacts in the aerosol located near clouds.

CloudSat-Based Assessment of GPM Microwave Imager Snowfall Observation Capabilities

Directory of Open Access Journals (Sweden)

Giulia Panegrossi

2017-12-01

Full Text Available The sensitivity of Global Precipitation Measurement (GPM Microwave Imager (GMI high-frequency channels to snowfall at higher latitudes (around 60°N/S is investigated using coincident CloudSat observations. The 166 GHz channel is highlighted throughout the study due to its ice scattering sensitivity and polarization information. The analysis of three case studies evidences the important combined role of total precipitable water (TPW, supercooled cloud water, and background surface composition on the brightness temperature (TB behavior for different snow-producing clouds. A regression tree statistical analysis applied to the entire GMI-CloudSat snowfall dataset indicates which variables influence the 166 GHz polarization difference (166 ∆TB and its relation to snowfall. Critical thresholds of various parameters (sea ice concentration (SIC, TPW, ice water path (IWP are established for optimal snowfall detection capabilities. The 166 ∆TB can identify snowfall events over land and sea when critical thresholds are exceeded (TPW > 3.6 kg·m−2, IWP > 0.24 kg·m−2 over land, and SIC > 57%, TPW > 5.1 kg·m−2 over sea. The complex combined 166 ∆TB-TB relationship at higher latitudes and the impact of supercooled water vertical distribution are also investigated. The findings presented in this study can be exploited to improve passive microwave snowfall detection algorithms.

Community Cloud Computing

Science.gov (United States)

Marinos, Alexandros; Briscoe, Gerard

Cloud Computing is rising fast, with its data centres growing at an unprecedented rate. However, this has come with concerns over privacy, efficiency at the expense of resilience, and environmental sustainability, because of the dependence on Cloud vendors such as Google, Amazon and Microsoft. Our response is an alternative model for the Cloud conceptualisation, providing a paradigm for Clouds in the community, utilising networked personal computers for liberation from the centralised vendor model. Community Cloud Computing (C3) offers an alternative architecture, created by combing the Cloud with paradigms from Grid Computing, principles from Digital Ecosystems, and sustainability from Green Computing, while remaining true to the original vision of the Internet. It is more technically challenging than Cloud Computing, having to deal with distributed computing issues, including heterogeneous nodes, varying quality of service, and additional security constraints. However, these are not insurmountable challenges, and with the need to retain control over our digital lives and the potential environmental consequences, it is a challenge we must pursue.

Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC).

Science.gov (United States)

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2016-01-01

This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud temperature threshold based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (< 2%) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10%, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

Cloud detection, classification and motion estimation using geostationary satellite imagery for cloud cover forecast

International Nuclear Information System (INIS)

Escrig, H.; Batlles, F.J.; Alonso, J.; Baena, F.M.; Bosch, J.L.; Salbidegoitia, I.B.; Burgaleta, J.I.

2013-01-01

Considering that clouds are the greatest causes to solar radiation blocking, short term cloud forecasting can help power plant operation and therefore improve benefits. Cloud detection, classification and motion vector determination are key to forecasting sun obstruction by clouds. Geostationary satellites provide cloud information covering wide areas, allowing cloud forecast to be performed for several hours in advance. Herein, the methodology developed and tested in this study is based on multispectral tests and binary cross correlations followed by coherence and quality control tests over resulting motion vectors. Monthly synthetic surface albedo image and a method to reject erroneous correlation vectors were developed. Cloud classification in terms of opacity and height of cloud top is also performed. A whole-sky camera has been used for validation, showing over 85% of agreement between the camera and the satellite derived cloud cover, whereas error in motion vectors is below 15%. - Highlights: ► A methodology for detection, classification and movement of clouds is presented. ► METEOSAT satellite images are used to obtain a cloud mask. ► The prediction of cloudiness is estimated with 90% in overcast conditions. ► Results for partially covered sky conditions showed a 75% accuracy. ► Motion vectors are estimated from the clouds with a success probability of 86%

ASTER cloud coverage reassessment using MODIS cloud mask products

Science.gov (United States)

Tonooka, Hideyuki; Omagari, Kunjuro; Yamamoto, Hirokazu; Tachikawa, Tetsushi; Fujita, Masaru; Paitaer, Zaoreguli

2010-10-01

In the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) Project, two kinds of algorithms are used for cloud assessment in Level-1 processing. The first algorithm based on the LANDSAT-5 TM Automatic Cloud Cover Assessment (ACCA) algorithm is used for a part of daytime scenes observed with only VNIR bands and all nighttime scenes, and the second algorithm based on the LANDSAT-7 ETM+ ACCA algorithm is used for most of daytime scenes observed with all spectral bands. However, the first algorithm does not work well for lack of some spectral bands sensitive to cloud detection, and the two algorithms have been less accurate over snow/ice covered areas since April 2008 when the SWIR subsystem developed troubles. In addition, they perform less well for some combinations of surface type and sun elevation angle. We, therefore, have developed the ASTER cloud coverage reassessment system using MODIS cloud mask (MOD35) products, and have reassessed cloud coverage for all ASTER archived scenes (>1.7 million scenes). All of the new cloud coverage data are included in Image Management System (IMS) databases of the ASTER Ground Data System (GDS) and NASA's Land Process Data Active Archive Center (LP DAAC) and used for ASTER product search by users, and cloud mask images are distributed to users through Internet. Daily upcoming scenes (about 400 scenes per day) are reassessed and inserted into the IMS databases in 5 to 7 days after each scene observation date. Some validation studies for the new cloud coverage data and some mission-related analyses using those data are also demonstrated in the present paper.

Day/night whole sky imagers for 24-h cloud and sky assessment: history and overview.

Science.gov (United States)

Shields, Janet E; Karr, Monette E; Johnson, Richard W; Burden, Art R

2013-03-10

A family of fully automated digital whole sky imagers (WSIs) has been developed at the Marine Physical Laboratory over many years, for a variety of research and military applications. The most advanced of these, the day/night whole sky imagers (D/N WSIs), acquire digital imagery of the full sky down to the horizon under all conditions from full sunlight to starlight. Cloud algorithms process the imagery to automatically detect the locations of cloud for both day and night. The instruments can provide absolute radiance distribution over the full radiance range from starlight through daylight. The WSIs were fielded in 1984, followed by the D/N WSIs in 1992. These many years of experience and development have resulted in very capable instruments and algorithms that remain unique. This article discusses the history of the development of the D/N WSIs, system design, algorithms, and data products. The paper cites many reports with more detailed technical documentation. Further details of calibration, day and night algorithms, and cloud free line-of-sight results will be discussed in future articles.

The Offer of Advanced Imaging Techniques Leads to Higher Acceptance Rates for Screening Colonoscopy - a Prospective Study.

Science.gov (United States)

Albrecht, Heinz; Gallitz, Julia; Hable, Robert; Vieth, Michael; Tontini, Gian Eugenio; Neurath, Markus Friedrich; Riemann, Jurgen Ferdinand; Neumann, Helmut

2016-01-01

Colonoscopy plays a fundamental role in early diagnosis and management of colorectal cancer and requires public and professional acceptance to ensure the ongoing success of screening programs. The aim of the study was to prospectively assess whether patient acceptance rates to undergo screening colonoscopy could be improved by the offer of advanced imaging techniques. Overall, 372 randomly selected patients were prospectively included. A standardized questionnaire was developed that inquired of the patients their knowledge regarding advanced imaging techniques. Second, several media campaigns and information events were organized reporting about advanced imaging techniques, followed by repeated evaluation. After one year the evaluation ended. At baseline, 64% of the patients declared that they had no knowledge about new endoscopic methods. After twelve months the overall grade of information increased significantly from 14% at baseline to 34%. The percentage of patients who decided to undergo colonoscopy because of the offer of new imaging methods also increased significantly from 12% at baseline to 42% after 12 months. Patients were highly interested in the offer of advanced imaging techniques. Knowledge about these techniques could relatively easy be provided using local media campaigns. The offer of advanced imaging techniques leads to higher acceptance rates for screening colonoscopies.

Atmospheric Polarization Imaging with Variable Aerosols, Clouds, and Surface Albedo

Science.gov (United States)

2013-07-01

values found in this region only during episodes of intense wildfire smoke. Detailed analysis of the aerosols in this smoke plume and their effect...Continuous outdoor operation of an all-sky polarization imager,” Proc. SPIE 7672 (Polarization: Measurement, Analysis , and Remote Sensing IX), 76720A-1-7, 7...Pust, “ Lunar corona in ice wave cloud,” 10th International Meeting on Light and Color in Nature, St. Mary’s College of Maryland, 16-20 June 2010. 2

Cloud Computing Value Chains: Understanding Businesses and Value Creation in the Cloud

Science.gov (United States)

Mohammed, Ashraf Bany; Altmann, Jörn; Hwang, Junseok

Based on the promising developments in Cloud Computing technologies in recent years, commercial computing resource services (e.g. Amazon EC2) or software-as-a-service offerings (e.g. Salesforce. com) came into existence. However, the relatively weak business exploitation, participation, and adoption of other Cloud Computing services remain the main challenges. The vague value structures seem to be hindering business adoption and the creation of sustainable business models around its technology. Using an extensive analyze of existing Cloud business models, Cloud services, stakeholder relations, market configurations and value structures, this Chapter develops a reference model for value chains in the Cloud. Although this model is theoretically based on porter's value chain theory, the proposed Cloud value chain model is upgraded to fit the diversity of business service scenarios in the Cloud computing markets. Using this model, different service scenarios are explained. Our findings suggest new services, business opportunities, and policy practices for realizing more adoption and value creation paths in the Cloud.

Megahertz rate, volumetric imaging of bubble clouds in sonothrombolysis using a sparse hemispherical receiver array

Science.gov (United States)

Acconcia, Christopher N.; Jones, Ryan M.; Goertz, David E.; O'Reilly, Meaghan A.; Hynynen, Kullervo

2017-09-01

It is well established that high intensity focused ultrasound can be used to disintegrate clots. This approach has the potential to rapidly and noninvasively resolve clot causing occlusions in cardiovascular diseases such as deep vein thrombosis (DVT). However, lack of an appropriate treatment monitoring tool is currently a limiting factor in its widespread adoption. Here we conduct cavitation imaging with a large aperture, sparse hemispherical receiver array during sonothrombolysis with multi-cycle burst exposures (0.1 or 1 ms burst lengths) at 1.51 MHz. It was found that bubble cloud generation on imaging correlated with the locations of clot degradation, as identified with high frequency (30 MHz) ultrasound following exposures. 3D images could be formed at integration times as short as 1 µs, revealing the initiation and rapid development of cavitation clouds. Equating to megahertz frame rates, this is an order of magnitude faster than any other imaging technique available for in vivo application. Collectively, these results suggest that the development of a device to perform DVT therapy procedures would benefit greatly from the integration of receivers tailored to bubble activity imaging.

How to govern the cloud?

NARCIS (Netherlands)

Prüfer, J.; Diamond, S.; Wainwright, N.

2013-01-01

This paper applies economic governance theory to the cloud computing industry. We analyze which governance institution may be best suited to solve the problems stemming from asymmetric information about the true level of data protection, security, and accountability offered by cloud service

COMPARISON OF UAS-BASED PHOTOGRAMMETRY SOFTWARE FOR 3D POINT CLOUD GENERATION: A SURVEY OVER A HISTORICAL SITE

Directory of Open Access Journals (Sweden)

F. Alidoost

2017-11-01

Full Text Available Nowadays, Unmanned Aerial System (UAS-based photogrammetry offers an affordable, fast and effective approach to real-time acquisition of high resolution geospatial information and automatic 3D modelling of objects for numerous applications such as topography mapping, 3D city modelling, orthophoto generation, and cultural heritages preservation. In this paper, the capability of four different state-of-the-art software packages as 3DSurvey, Agisoft Photoscan, Pix4Dmapper Pro and SURE is examined to generate high density point cloud as well as a Digital Surface Model (DSM over a historical site. The main steps of this study are including: image acquisition, point cloud generation, and accuracy assessment. The overlapping images are first captured using a quadcopter and next are processed by different software to generate point clouds and DSMs. In order to evaluate the accuracy and quality of point clouds and DSMs, both visual and geometric assessments are carry out and the comparison results are reported.

Comparison of Uas-Based Photogrammetry Software for 3d Point Cloud Generation: a Survey Over a Historical Site

Science.gov (United States)

Alidoost, F.; Arefi, H.

2017-11-01

Nowadays, Unmanned Aerial System (UAS)-based photogrammetry offers an affordable, fast and effective approach to real-time acquisition of high resolution geospatial information and automatic 3D modelling of objects for numerous applications such as topography mapping, 3D city modelling, orthophoto generation, and cultural heritages preservation. In this paper, the capability of four different state-of-the-art software packages as 3DSurvey, Agisoft Photoscan, Pix4Dmapper Pro and SURE is examined to generate high density point cloud as well as a Digital Surface Model (DSM) over a historical site. The main steps of this study are including: image acquisition, point cloud generation, and accuracy assessment. The overlapping images are first captured using a quadcopter and next are processed by different software to generate point clouds and DSMs. In order to evaluate the accuracy and quality of point clouds and DSMs, both visual and geometric assessments are carry out and the comparison results are reported.

Cloud computing methods and practical approaches

CERN Document Server

Mahmood, Zaigham

2013-01-01

This book presents both state-of-the-art research developments and practical guidance on approaches, technologies and frameworks for the emerging cloud paradigm. Topics and features: presents the state of the art in cloud technologies, infrastructures, and service delivery and deployment models; discusses relevant theoretical frameworks, practical approaches and suggested methodologies; offers guidance and best practices for the development of cloud-based services and infrastructures, and examines management aspects of cloud computing; reviews consumer perspectives on mobile cloud computing an

A parameterization of cloud droplet nucleation

International Nuclear Information System (INIS)

Ghan, S.J.; Chuang, C.; Penner, J.E.

1993-01-01

Droplet nucleation is a fundamental cloud process. The number of aerosols activated to form cloud droplets influences not only the number of aerosols scavenged by clouds but also the size of the cloud droplets. Cloud droplet size influences the cloud albedo and the conversion of cloud water to precipitation. Global aerosol models are presently being developed with the intention of coupling with global atmospheric circulation models to evaluate the influence of aerosols and aerosol-cloud interactions on climate. If these and other coupled models are to address issues of aerosol-cloud interactions, the droplet nucleation process must be adequately represented. Here we introduce a droplet nucleation parametrization that offers certain advantages over the popular Twomey (1959) parameterization

Comparison of Cloud Properties from CALIPSO-CloudSat and Geostationary Satellite Data

Science.gov (United States)

Nguyen, L.; Minnis, P.; Chang, F.; Winker, D.; Sun-Mack, S.; Spangenberg, D.; Austin, R.

2007-01-01

Cloud properties are being derived in near-real time from geostationary satellite imager data for a variety of weather and climate applications and research. Assessment of the uncertainties in each of the derived cloud parameters is essential for confident use of the products. Determination of cloud amount, cloud top height, and cloud layering is especially important for using these real -time products for applications such as aircraft icing condition diagnosis and numerical weather prediction model assimilation. Furthermore, the distribution of clouds as a function of altitude has become a central component of efforts to evaluate climate model cloud simulations. Validation of those parameters has been difficult except over limited areas where ground-based active sensors, such as cloud radars or lidars, have been available on a regular basis. Retrievals of cloud properties are sensitive to the surface background, time of day, and the clouds themselves. Thus, it is essential to assess the geostationary satellite retrievals over a variety of locations. The availability of cloud radar data from CloudSat and lidar data from CALIPSO make it possible to perform those assessments over each geostationary domain at 0130 and 1330 LT. In this paper, CloudSat and CALIPSO data are matched with contemporaneous Geostationary Operational Environmental Satellite (GOES), Multi-functional Transport Satellite (MTSAT), and Meteosat-8 data. Unlike comparisons with cloud products derived from A-Train imagers, this study considers comparisons of nadir active sensor data with off-nadir retrievals. These matched data are used to determine the uncertainties in cloud-top heights and cloud amounts derived from the geostationary satellite data using the Clouds and the Earth s Radiant Energy System (CERES) cloud retrieval algorithms. The CERES multi-layer cloud detection method is also evaluated to determine its accuracy and limitations in the off-nadir mode. The results will be useful for

Cloud occurrences and cloud radiative effects (CREs) from CERES-CALIPSO-CloudSat-MODIS (CCCM) and CloudSat radar-lidar (RL) products

Science.gov (United States)

Ham, Seung-Hee; Kato, Seiji; Rose, Fred G.; Winker, David; L'Ecuyer, Tristan; Mace, Gerald G.; Painemal, David; Sun-Mack, Sunny; Chen, Yan; Miller, Walter F.

2017-08-01

Two kinds of cloud products obtained from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, and Moderate Resolution Imaging Spectroradiometer (MODIS) are compared and analyzed in this study: Clouds and the Earth's Radiant Energy System (CERES)-CALIPSO-CloudSat-MODIS (CCCM) product and CloudSat radar-lidar products such as GEOPROF-LIDAR and FLXHR-LIDAR. Compared to GEOPROF-LIDAR, low-level (40°). The difference occurs when hydrometeors are detected by CALIPSO lidar but are undetected by CloudSat radar. In the comparison of cloud radiative effects (CREs), global mean differences between CCCM and FLXHR-LIDAR are mostly smaller than 5 W m-2, while noticeable regional differences are found. For example, CCCM shortwave (SW) and longwave (LW) CREs are larger than FXLHR-LIDAR along the west coasts of Africa and America because the GEOPROF-LIDAR algorithm misses shallow marine boundary layer clouds. In addition, FLXHR-LIDAR SW CREs are larger than the CCCM counterpart over tropical oceans away from the west coasts of America. Over midlatitude storm-track regions, CCCM SW and LW CREs are larger than the FLXHR-LIDAR counterpart.

Cloud Security Audit for Migration and Continuous Monitoring

OpenAIRE

Ismail, Umar Mukhtar; Islam, Shareeful; Mouratidis, Haralambos

2015-01-01

Security assurance in cloud computing is one of the main barriers for wider cloud adoption. Potential cloud computing consumers like to know whether the controls in cloud environments can adequately protect critical assets migrated into the cloud. We present a cloud security audit approach to enable users' evaluate cloud service provider offerings before migration, as well as monitoring of events after migration. Our approach entails a set of concepts such as actor, goals, monitoring, conditi...

High-resolution imaging and target designation through clouds or smoke

Science.gov (United States)

Perry, Michael D.

2003-01-01

A method and system of combining gated intensifiers and advances in solid-state, short-pulse laser technology, compact systems capable of producing high resolution (i.e., approximately less than 20 centimeters) optical images through a scattering medium such as dense clouds, fog, smoke, etc. may be achieved from air or ground based platforms. Laser target designation through a scattering medium is also enabled by utilizing a short pulse illumination laser and a relatively minor change to the detectors on laser guided munitions.

Use of cloud computing in biomedicine.

Science.gov (United States)

Sobeslav, Vladimir; Maresova, Petra; Krejcar, Ondrej; Franca, Tanos C C; Kuca, Kamil

2016-12-01

Nowadays, biomedicine is characterised by a growing need for processing of large amounts of data in real time. This leads to new requirements for information and communication technologies (ICT). Cloud computing offers a solution to these requirements and provides many advantages, such as cost savings, elasticity and scalability of using ICT. The aim of this paper is to explore the concept of cloud computing and the related use of this concept in the area of biomedicine. Authors offer a comprehensive analysis of the implementation of the cloud computing approach in biomedical research, decomposed into infrastructure, platform and service layer, and a recommendation for processing large amounts of data in biomedicine. Firstly, the paper describes the appropriate forms and technological solutions of cloud computing. Secondly, the high-end computing paradigm of cloud computing aspects is analysed. Finally, the potential and current use of applications in scientific research of this technology in biomedicine is discussed.

Networking for the Cloud: Challenges and Trends

NARCIS (Netherlands)

Drago, Idilio; de Oliveira Schmidt, R.; Hofstede, R.J.; Sperotto, Anna; Karimzadeh Motallebi Azar, Morteza; Haverkort, Boudewijn R.H.M.; Pras, Aiko

2013-01-01

Cloud services have changed the way computing power is delivered to customers, by offering computing and storage capacity in remote data centers on demand over the Internet. The success of the cloud model, however, has not come without challenges. Cloud providers have repeatedly been related to

Transitioning ISR architecture into the cloud

Science.gov (United States)

Lash, Thomas D.

2012-06-01

Emerging cloud computing platforms offer an ideal opportunity for Intelligence, Surveillance, and Reconnaissance (ISR) intelligence analysis. Cloud computing platforms help overcome challenges and limitations of traditional ISR architectures. Modern ISR architectures can benefit from examining commercial cloud applications, especially as they relate to user experience, usage profiling, and transformational business models. This paper outlines legacy ISR architectures and their limitations, presents an overview of cloud technologies and their applications to the ISR intelligence mission, and presents an idealized ISR architecture implemented with cloud computing.

Wide-angle imaging LIDAR (WAIL): a ground-based instrument for monitoring the thickness and density of optically thick clouds

International Nuclear Information System (INIS)

Love, Steven P.; Davis, A.B.; Rohde, C.A.; Ho, Cheng

2001-01-01

Traditional lidar provides little information on dense clouds beyond the range to their base (ceilometry), due to their extreme opacity. At most optical wavelengths, however, laser photons are not absorbed but merely scattered out of the beam, and thus eventually escape the cloud via multiple scattering, producing distinctive extended space- and time-dependent patterns which are, in essence, the cloud's radiative Green functions. These Green functions, essentially 'movies' of the time evolution of the spatial distribution of escaping light, are the primary data products of a new type of lidar: Wide Angle Imaging Lidar (WAIL). WAIL data can be used to infer both optical depth and physical thickness of clouds, and hence the cloud liquid water content. The instrumental challenge is to accommodate a radiance field varying over many orders of magnitude and changing over widely varying time-scales. Our implementation uses a high-speed microchannel plate/crossed delay line imaging detector system with a 60-degree full-angle field of view, and a 532 nm doubled Nd:YAG laser. Nighttime field experiments testing various solutions to this problem show excellent agreement with diffusion theory, and retrievals yield plausible values for the optical and geometrical parameters of the observed cloud decks.

Galaxy CloudMan: delivering cloud compute clusters.

Science.gov (United States)

Afgan, Enis; Baker, Dannon; Coraor, Nate; Chapman, Brad; Nekrutenko, Anton; Taylor, James

2010-12-21

Widespread adoption of high-throughput sequencing has greatly increased the scale and sophistication of computational infrastructure needed to perform genomic research. An alternative to building and maintaining local infrastructure is "cloud computing", which, in principle, offers on demand access to flexible computational infrastructure. However, cloud computing resources are not yet suitable for immediate "as is" use by experimental biologists. We present a cloud resource management system that makes it possible for individual researchers to compose and control an arbitrarily sized compute cluster on Amazon's EC2 cloud infrastructure without any informatics requirements. Within this system, an entire suite of biological tools packaged by the NERC Bio-Linux team (http://nebc.nerc.ac.uk/tools/bio-linux) is available for immediate consumption. The provided solution makes it possible, using only a web browser, to create a completely configured compute cluster ready to perform analysis in less than five minutes. Moreover, we provide an automated method for building custom deployments of cloud resources. This approach promotes reproducibility of results and, if desired, allows individuals and labs to add or customize an otherwise available cloud system to better meet their needs. The expected knowledge and associated effort with deploying a compute cluster in the Amazon EC2 cloud is not trivial. The solution presented in this paper eliminates these barriers, making it possible for researchers to deploy exactly the amount of computing power they need, combined with a wealth of existing analysis software, to handle the ongoing data deluge.

Cloud Computing: An Overview

Science.gov (United States)

Qian, Ling; Luo, Zhiguo; Du, Yujian; Guo, Leitao

In order to support the maximum number of user and elastic service with the minimum resource, the Internet service provider invented the cloud computing. within a few years, emerging cloud computing has became the hottest technology. From the publication of core papers by Google since 2003 to the commercialization of Amazon EC2 in 2006, and to the service offering of AT&T Synaptic Hosting, the cloud computing has been evolved from internal IT system to public service, from cost-saving tools to revenue generator, and from ISP to telecom. This paper introduces the concept, history, pros and cons of cloud computing as well as the value chain and standardization effort.

Security for cloud storage systems

CERN Document Server

Yang, Kan

2014-01-01

Cloud storage is an important service of cloud computing, which offers service for data owners to host their data in the cloud. This new paradigm of data hosting and data access services introduces two major security concerns. The first is the protection of data integrity. Data owners may not fully trust the cloud server and worry that data stored in the cloud could be corrupted or even removed. The second is data access control. Data owners may worry that some dishonest servers provide data access to users that are not permitted for profit gain and thus they can no longer rely on the servers

Teaching Cybersecurity Using the Cloud

Science.gov (United States)

Salah, Khaled; Hammoud, Mohammad; Zeadally, Sherali

2015-01-01

Cloud computing platforms can be highly attractive to conduct course assignments and empower students with valuable and indispensable hands-on experience. In particular, the cloud can offer teaching staff and students (whether local or remote) on-demand, elastic, dedicated, isolated, (virtually) unlimited, and easily configurable virtual machines.…

The ethics of cloud computing

NARCIS (Netherlands)

de Bruin, Boudewijn; Floridi, Luciano

2016-01-01

Cloud computing is rapidly gaining traction in business. It offers businesses online services on demand (such as Gmail, iCloud and Salesforce) and allows them to cut costs on hardware and IT support. This is the first paper in business ethics dealing with this new technology. It analyzes the

A Survey on Cloud Security Issues and Techniques

OpenAIRE

Sharma, Shubhanjali; Gupta, Garima; Laxmi, P. R.

2014-01-01

Today, cloud computing is an emerging way of computing in computer science. Cloud computing is a set of resources and services that are offered by the network or internet. Cloud computing extends various computing techniques like grid computing, distributed computing. Today cloud computing is used in both industrial field and academic field. Cloud facilitates its users by providing virtual resources via internet. As the field of cloud computing is spreading the new techniques are developing. ...

A Routing Mechanism for Cloud Outsourcing of Medical Imaging Repositories.

Science.gov (United States)

Godinho, Tiago Marques; Viana-Ferreira, Carlos; Bastião Silva, Luís A; Costa, Carlos

2016-01-01

Web-based technologies have been increasingly used in picture archive and communication systems (PACS), in services related to storage, distribution, and visualization of medical images. Nowadays, many healthcare institutions are outsourcing their repositories to the cloud. However, managing communications between multiple geo-distributed locations is still challenging due to the complexity of dealing with huge volumes of data and bandwidth requirements. Moreover, standard methodologies still do not take full advantage of outsourced archives, namely because their integration with other in-house solutions is troublesome. In order to improve the performance of distributed medical imaging networks, a smart routing mechanism was developed. This includes an innovative cache system based on splitting and dynamic management of digital imaging and communications in medicine objects. The proposed solution was successfully deployed in a regional PACS archive. The results obtained proved that it is better than conventional approaches, as it reduces remote access latency and also the required cache storage space.

Photometric Calibration of the Barium Cloud Image in a Space Active Experiment: Determining the Release Efficiency

International Nuclear Information System (INIS)

Xie Liang-Hai; Li Lei; Wang Jing-Dong; Tao Ran; Cheng Bing-Jun; Zhang Yi-Teng

2014-01-01

The barium release experiment is an effective method to explore the near-earth environment and to study all kinds of space physics processes. The first space barium release experiment in China was successfully carried out by a sounding rocket on April 5, 2013. This work is devoted to calculating the release efficiency of the barium release by analyzing the optical image observed during the experiment. First, we present a method to calibrate the images grey value of barium cloud with the reference stars to obtain the radiant fluxes at different moments. Then the release efficiency is obtained by a curve fitting with the theoretical evolution model of barium cloud. The calculated result is basically consistent with the test value on ground

Point Cloud Based Change Detection - an Automated Approach for Cloud-based Services

Science.gov (United States)

Collins, Patrick; Bahr, Thomas

2016-04-01

The fusion of stereo photogrammetric point clouds with LiDAR data or terrain information derived from SAR interferometry has a significant potential for 3D topographic change detection. In the present case study latest point cloud generation and analysis capabilities are used to examine a landslide that occurred in the village of Malin in Maharashtra, India, on 30 July 2014, and affected an area of ca. 44.000 m2. It focuses on Pléiades high resolution satellite imagery and the Airbus DS WorldDEMTM as a product of the TanDEM-X mission. This case study was performed using the COTS software package ENVI 5.3. Integration of custom processes and automation is supported by IDL (Interactive Data Language). Thus, ENVI analytics is running via the object-oriented and IDL-based ENVITask API. The pre-event topography is represented by the WorldDEMTM product, delivered with a raster of 12 m x 12 m and based on the EGM2008 geoid (called pre-DEM). For the post-event situation a Pléiades 1B stereo image pair of the AOI affected was obtained. The ENVITask "GeneratePointCloudsByDenseImageMatching" was implemented to extract passive point clouds in LAS format from the panchromatic stereo datasets: • A dense image-matching algorithm is used to identify corresponding points in the two images. • A block adjustment is applied to refine the 3D coordinates that describe the scene geometry. • Additionally, the WorldDEMTM was input to constrain the range of heights in the matching area, and subsequently the length of the epipolar line. The "PointCloudFeatureExtraction" task was executed to generate the post-event digital surface model from the photogrammetric point clouds (called post-DEM). Post-processing consisted of the following steps: • Adding the geoid component (EGM 2008) to the post-DEM. • Pre-DEM reprojection to the UTM Zone 43N (WGS-84) coordinate system and resizing. • Subtraction of the pre-DEM from the post-DEM. • Filtering and threshold based classification of

Cloud computing for radiologists

OpenAIRE

Amit T Kharat; Amjad Safvi; S S Thind; Amarjit Singh

2012-01-01

Cloud computing is a concept wherein a computer grid is created using the Internet with the sole purpose of utilizing shared resources such as computer software, hardware, on a pay-per-use model. Using Cloud computing, radiology users can efficiently manage multimodality imaging units by using the latest software and hardware without paying huge upfront costs. Cloud computing systems usually work on public, private, hybrid, or community models. Using the various components of a Cloud, such as...

Cloud-based Networked Visual Servo Control

DEFF Research Database (Denmark)

Wu, Haiyan; Lu, Lei; Chen, Chih-Chung

2013-01-01

, which integrates networked computational resources for cloud image processing, is considered in this article. The main contributions of this article are i) a real-time transport protocol for transmitting large volume image data on a cloud computing platform, which enables high sampling rate visual...

High performance computing in Windows Azure cloud

OpenAIRE

Ambruš, Dejan

2013-01-01

High performance, security, availability, scalability, flexibility and lower costs of maintenance have essentially contributed to the growing popularity of cloud computing in all spheres of life, especially in business. In fact cloud computing offers even more than this. With usage of virtual computing clusters a runtime environment for high performance computing can be efficiently implemented also in a cloud. There are many advantages but also some disadvantages of cloud computing, some ...

Assessing the performance of aerial image point cloud and spectral metrics in predicting boreal forest canopy cover

Science.gov (United States)

Melin, M.; Korhonen, L.; Kukkonen, M.; Packalen, P.

2017-07-01

Canopy cover (CC) is a variable used to describe the status of forests and forested habitats, but also the variable used primarily to define what counts as a forest. The estimation of CC has relied heavily on remote sensing with past studies focusing on satellite imagery as well as Airborne Laser Scanning (ALS) using light detection and ranging (lidar). Of these, ALS has been proven highly accurate, because the fraction of pulses penetrating the canopy represents a direct measurement of canopy gap percentage. However, the methods of photogrammetry can be applied to produce point clouds fairly similar to airborne lidar data from aerial images. Currently there is little information about how well such point clouds measure canopy density and gaps. The aim of this study was to assess the suitability of aerial image point clouds for CC estimation and compare the results with those obtained using spectral data from aerial images and Landsat 5. First, we modeled CC for n = 1149 lidar plots using field-measured CCs and lidar data. Next, this data was split into five subsets in north-south direction (y-coordinate). Finally, four CC models (AerialSpectral, AerialPointcloud, AerialCombi (spectral + pointcloud) and Landsat) were created and they were used to predict new CC values to the lidar plots, subset by subset, using five-fold cross validation. The Landsat and AerialSpectral models performed with RMSEs of 13.8% and 12.4%, respectively. AerialPointcloud model reached an RMSE of 10.3%, which was further improved by the inclusion of spectral data; RMSE of the AerialCombi model was 9.3%. We noticed that the aerial image point clouds managed to describe only the outermost layer of the canopy and missed the details in lower canopy, which was resulted in weak characterization of the total CC variation, especially in the tails of the data.

ABrIL - Advanced Brain Imaging Lab : a cloud based computation environment for cooperative neuroimaging projects.

Science.gov (United States)

Neves Tafula, Sérgio M; Moreira da Silva, Nádia; Rozanski, Verena E; Silva Cunha, João Paulo

2014-01-01

Neuroscience is an increasingly multidisciplinary and highly cooperative field where neuroimaging plays an important role. Neuroimaging rapid evolution is demanding for a growing number of computing resources and skills that need to be put in place at every lab. Typically each group tries to setup their own servers and workstations to support their neuroimaging needs, having to learn from Operating System management to specific neuroscience software tools details before any results can be obtained from each setup. This setup and learning process is replicated in every lab, even if a strong collaboration among several groups is going on. In this paper we present a new cloud service model - Brain Imaging Application as a Service (BiAaaS) - and one of its implementation - Advanced Brain Imaging Lab (ABrIL) - in the form of an ubiquitous virtual desktop remote infrastructure that offers a set of neuroimaging computational services in an interactive neuroscientist-friendly graphical user interface (GUI). This remote desktop has been used for several multi-institution cooperative projects with different neuroscience objectives that already achieved important results, such as the contribution to a high impact paper published in the January issue of the Neuroimage journal. The ABrIL system has shown its applicability in several neuroscience projects with a relatively low-cost, promoting truly collaborative actions and speeding up project results and their clinical applicability.

Studi Perbandingan Layanan Cloud Computing

OpenAIRE

Afdhal, Afdhal

2013-01-01

In the past few years, cloud computing has became a dominant topic in the IT area. Cloud computing offers hardware, infrastructure, platform and applications without requiring end-users knowledge of the physical location and the configuration of providers who deliver the services. It has been a good solution to increase reliability, reduce computing cost, and make opportunities to IT industries to get more advantages. The purpose of this article is to present a better understanding of cloud d...

CHPS IN CLOUD COMPUTING ENVIRONMENT

OpenAIRE

K.L.Giridas; A.Shajin Nargunam

2012-01-01

Workflow have been utilized to characterize a various form of applications concerning high processing and storage space demands. So, to make the cloud computing environment more eco-friendly,our research project was aiming in reducing E-waste accumulated by computers. In a hybrid cloud, the user has flexibility offered by public cloud resources that can be combined to the private resources pool as required. Our previous work described the process of combining the low range and mid range proce...

High resolution depth reconstruction from monocular images and sparse point clouds using deep convolutional neural network

Science.gov (United States)

Dimitrievski, Martin; Goossens, Bart; Veelaert, Peter; Philips, Wilfried

2017-09-01

Understanding the 3D structure of the environment is advantageous for many tasks in the field of robotics and autonomous vehicles. From the robot's point of view, 3D perception is often formulated as a depth image reconstruction problem. In the literature, dense depth images are often recovered deterministically from stereo image disparities. Other systems use an expensive LiDAR sensor to produce accurate, but semi-sparse depth images. With the advent of deep learning there have also been attempts to estimate depth by only using monocular images. In this paper we combine the best of the two worlds, focusing on a combination of monocular images and low cost LiDAR point clouds. We explore the idea that very sparse depth information accurately captures the global scene structure while variations in image patches can be used to reconstruct local depth to a high resolution. The main contribution of this paper is a supervised learning depth reconstruction system based on a deep convolutional neural network. The network is trained on RGB image patches reinforced with sparse depth information and the output is a depth estimate for each pixel. Using image and point cloud data from the KITTI vision dataset we are able to learn a correspondence between local RGB information and local depth, while at the same time preserving the global scene structure. Our results are evaluated on sequences from the KITTI dataset and our own recordings using a low cost camera and LiDAR setup.

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Mask Environmental Data Record (EDR) from NDE

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains a high quality Environmental Data Record (EDR) of cloud masks from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument onboard...

Multi-Spectral Cloud Retrievals from Moderate Image Spectrometer (MODIS)

Science.gov (United States)

Platnick, Steven

2004-01-01

MODIS observations from the NASA EOS Terra spacecraft (1030 local time equatorial sun-synchronous crossing) launched in December 1999 have provided a unique set of Earth observation data. With the launch of the NASA EOS Aqua spacecraft (1330 local time crossing! in May 2002: two MODIS daytime (sunlit) and nighttime observations are now available in a 24-hour period allowing some measure of diurnal variability. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate modeling, climate change studies, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. An overview of the instrument and cloud algorithms will be presented along with various examples, including an initial analysis of several operational global gridded (Level-3) cloud products from the two platforms. Statistics of cloud optical and microphysical properties as a function of latitude for land and Ocean regions will be shown. Current algorithm research efforts will also be discussed.

Cloud computing applications for biomedical science: A perspective.

Science.gov (United States)

Navale, Vivek; Bourne, Philip E

2018-06-01

Biomedical research has become a digital data-intensive endeavor, relying on secure and scalable computing, storage, and network infrastructure, which has traditionally been purchased, supported, and maintained locally. For certain types of biomedical applications, cloud computing has emerged as an alternative to locally maintained traditional computing approaches. Cloud computing offers users pay-as-you-go access to services such as hardware infrastructure, platforms, and software for solving common biomedical computational problems. Cloud computing services offer secure on-demand storage and analysis and are differentiated from traditional high-performance computing by their rapid availability and scalability of services. As such, cloud services are engineered to address big data problems and enhance the likelihood of data and analytics sharing, reproducibility, and reuse. Here, we provide an introductory perspective on cloud computing to help the reader determine its value to their own research.

From On-Premise Software to Cloud Services: The Impact of Cloud Computing on Enterprise Software Vendors' Business Models

OpenAIRE

Boillat, Thomas; Legner, Christine

2013-01-01

Cloud computing is an emerging paradigm that allows users to conveniently access computing resources as pay-per-use services. Whereas cloud offerings such as Amazon's Elastic Compute Cloud and Google Apps are rapidly gaining a large user base, enterprise software's migration towards the cloud is still in its infancy. For software vendors the move towardscloud solutions implies profound changes in their value-creation logic. Not only are they forced to deliver fully web-enabled solutions and t...

NOAA GOES-R Series Advanced Baseline Imager (ABI) Level 2+ Cloud and Moisture Imagery Products (CMIP)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Cloud and Moisture Imagery product contains one or more Earth-view images with pixel values identifying brightness values that are scaled to support visual...

Services for domain specific developments in the Cloud

Science.gov (United States)

Schwichtenberg, Horst; Gemuend, André

2015-04-01

We will discuss and demonstrate the possibilities of new Cloud Services where the complete development of code is in the Cloud. We will discuss the possibilities of such services where the complete development cycle from programing to testing is in the cloud. This can be also combined with dedicated research domain specific services and hide the burden of accessing available infrastructures. As an example, we will show a service that is intended to complement the services of the VERCE projects infrastructure, a service that utilizes Cloud resources to offer simplified execution of data pre- and post-processing scripts. It offers users access to the ObsPy seismological toolbox for processing data with the Python programming language, executed on virtual Cloud resources in a secured sandbox. The solution encompasses a frontend with a modern graphical user interface, a messaging infrastructure as well as Python worker nodes for background processing. All components are deployable in the Cloud and have been tested on different environments based on OpenStack and OpenNebula. Deployments on commercial, public Clouds will be tested in the future.

CLASSIFICATION BY USING MULTISPECTRAL POINT CLOUD DATA

Directory of Open Access Journals (Sweden)

C. T. Liao

2012-07-01

Full Text Available Remote sensing images are generally recorded in two-dimensional format containing multispectral information. Also, the semantic information is clearly visualized, which ground features can be better recognized and classified via supervised or unsupervised classification methods easily. Nevertheless, the shortcomings of multispectral images are highly depending on light conditions, and classification results lack of three-dimensional semantic information. On the other hand, LiDAR has become a main technology for acquiring high accuracy point cloud data. The advantages of LiDAR are high data acquisition rate, independent of light conditions and can directly produce three-dimensional coordinates. However, comparing with multispectral images, the disadvantage is multispectral information shortage, which remains a challenge in ground feature classification through massive point cloud data. Consequently, by combining the advantages of both LiDAR and multispectral images, point cloud data with three-dimensional coordinates and multispectral information can produce a integrate solution for point cloud classification. Therefore, this research acquires visible light and near infrared images, via close range photogrammetry, by matching images automatically through free online service for multispectral point cloud generation. Then, one can use three-dimensional affine coordinate transformation to compare the data increment. At last, the given threshold of height and color information is set as threshold in classification.

Classification by Using Multispectral Point Cloud Data

Science.gov (United States)

Liao, C. T.; Huang, H. H.

2012-07-01

Remote sensing images are generally recorded in two-dimensional format containing multispectral information. Also, the semantic information is clearly visualized, which ground features can be better recognized and classified via supervised or unsupervised classification methods easily. Nevertheless, the shortcomings of multispectral images are highly depending on light conditions, and classification results lack of three-dimensional semantic information. On the other hand, LiDAR has become a main technology for acquiring high accuracy point cloud data. The advantages of LiDAR are high data acquisition rate, independent of light conditions and can directly produce three-dimensional coordinates. However, comparing with multispectral images, the disadvantage is multispectral information shortage, which remains a challenge in ground feature classification through massive point cloud data. Consequently, by combining the advantages of both LiDAR and multispectral images, point cloud data with three-dimensional coordinates and multispectral information can produce a integrate solution for point cloud classification. Therefore, this research acquires visible light and near infrared images, via close range photogrammetry, by matching images automatically through free online service for multispectral point cloud generation. Then, one can use three-dimensional affine coordinate transformation to compare the data increment. At last, the given threshold of height and color information is set as threshold in classification.

Determining ice water content from 2D crystal images in convective cloud systems

Science.gov (United States)

Leroy, Delphine; Coutris, Pierre; Fontaine, Emmanuel; Schwarzenboeck, Alfons; Strapp, J. Walter

2016-04-01

Cloud microphysical in-situ instrumentation measures bulk parameters like total water content (TWC) and/or derives particle size distributions (PSD) (utilizing optical spectrometers and optical array probes (OAP)). The goal of this work is to introduce a comprehensive methodology to compute TWC from OAP measurements, based on the dataset collected during recent HAIC (High Altitude Ice Crystals)/HIWC (High Ice Water Content) field campaigns. Indeed, the HAIC/HIWC field campaigns in Darwin (2014) and Cayenne (2015) provide a unique opportunity to explore the complex relationship between cloud particle mass and size in ice crystal environments. Numerous mesoscale convective systems (MCSs) were sampled with the French Falcon 20 research aircraft at different temperature levels from -10°C up to 50°C. The aircraft instrumentation included an IKP-2 (isokinetic probe) to get reliable measurements of TWC and the optical array probes 2D-S and PIP recording images over the entire ice crystal size range. Based on the known principle relating crystal mass and size with a power law (m=α•Dβ), Fontaine et al. (2014) performed extended 3D crystal simulations and thereby demonstrated that it is possible to estimate the value of the exponent β from OAP data, by analyzing the surface-size relationship for the 2D images as a function of time. Leroy et al. (2015) proposed an extended version of this method that produces estimates of β from the analysis of both the surface-size and perimeter-size relationships. Knowing the value of β, α then is deduced from the simultaneous IKP-2 TWC measurements for the entire HAIC/HIWC dataset. The statistical analysis of α and β values for the HAIC/HIWC dataset firstly shows that α is closely linked to β and that this link changes with temperature. From these trends, a generalized parameterization for α is proposed. Finally, the comparison with the initial IKP-2 measurements demonstrates that the method is able to predict TWC values

Vliv Cloud Computingu na Supply Chain Management

OpenAIRE

Karkošková, Soňa

2013-01-01

Master thesis "Impact of Cloud Computing on Supply Chain Management" analyses the provisioning of IT resources in the form of cloud computing services and their impact on supply chain management environment. Attention is focused particularly on providing SaaS model of public applications delivery. The Cloud SCM implementation offers many advantages especially for small and medium sized companies. In this thesis I analysed the specifics of the deployment of Cloud SCM in highly unstable market ...

Cloud Standardization: Consistent Business Processes and Information

Directory of Open Access Journals (Sweden)

Razvan Daniel ZOTA

2013-01-01

Full Text Available Cloud computing represents one of the latest emerging trends in distributed computing that enables the existence of hardware infrastructure and software applications as services. The present paper offers a general approach to the cloud computing standardization as a mean of improving the speed of adoption for the cloud technologies. Moreover, this study tries to show out how organizations may achieve more consistent business processes while operating with cloud computing technologies.

MVC for content management on the cloud

OpenAIRE

McGruder, Crystal A.

2011-01-01

Approved for public release; distribution is unlimited. Cloud computing portrays a new model for providing IT services over the Internet. In cloud computing, resources are accessed from the Internet through web-based tools. Although cloud computing offers reduced cost, increased storage, high automation, flexibility, mobility, and the ability of IT to shift focus, there are other concerns such as the management, organization and structure of content on the cloud that large organizations sh...

The AIST Managed Cloud Environment

Science.gov (United States)

Cook, S.

2016-12-01

ESTO is currently in the process of developing and implementing the AIST Managed Cloud Environment (AMCE) to offer cloud computing services to ESTO-funded PIs to conduct their project research. AIST will provide projects access to a cloud computing framework that incorporates NASA security, technical, and financial standards, on which project can freely store, run, and process data. Currently, many projects led by research groups outside of NASA do not have the awareness of requirements or the resources to implement NASA standards into their research, which limits the likelihood of infusing the work into NASA applications. Offering this environment to PIs will allow them to conduct their project research using the many benefits of cloud computing. In addition to the well-known cost and time savings that it allows, it also provides scalability and flexibility. The AMCE will facilitate infusion and end user access by ensuring standardization and security. This approach will ultimately benefit ESTO, the science community, and the research, allowing the technology developments to have quicker and broader applications.

YAWL in the cloud : supporting process sharing and variability

NARCIS (Netherlands)

Schunselaar, D.M.M.; Verbeek, H.M.W.; Reijers, H.A.; Aalst, van der W.M.P.; Fournier, F.; Mendling, J.

2015-01-01

The cloud is at the centre of attention in various fields, including that of BPM. However, all BPM systems in the cloud seem to be nothing more than an installation in the cloud with a web-interface for a single organisation, while cloud technology offers an excellent platform for cooperation on an

Evaluation of Passive Multilayer Cloud Detection Using Preliminary CloudSat and CALIPSO Cloud Profiles

Science.gov (United States)

Minnis, P.; Sun-Mack, S.; Chang, F.; Huang, J.; Nguyen, L.; Ayers, J. K.; Spangenberg, D. A.; Yi, Y.; Trepte, C. R.

2006-12-01

During the last few years, several algorithms have been developed to detect and retrieve multilayered clouds using passive satellite data. Assessing these techniques has been difficult due to the need for active sensors such as cloud radars and lidars that can "see" through different layers of clouds. Such sensors have been available only at a few surface sites and on aircraft during field programs. With the launch of the CALIPSO and CloudSat satellites on April 28, 2006, it is now possible to observe multilayered systems all over the globe using collocated cloud radar and lidar data. As part of the A- Train, these new active sensors are also matched in time ad space with passive measurements from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - EOS (AMSR-E). The Clouds and the Earth's Radiant Energy System (CERES) has been developing and testing algorithms to detect ice-over-water overlapping cloud systems and to retrieve the cloud liquid path (LWP) and ice water path (IWP) for those systems. One technique uses a combination of the CERES cloud retrieval algorithm applied to MODIS data and a microwave retrieval method applied to AMSR-E data. The combination of a CO2-slicing cloud retireval technique with the CERES algorithms applied to MODIS data (Chang et al., 2005) is used to detect and analyze such overlapped systems that contain thin ice clouds. A third technique uses brightness temperature differences and the CERES algorithms to detect similar overlapped methods. This paper uses preliminary CloudSat and CALIPSO data to begin a global scale assessment of these different methods. The long-term goals are to assess and refine the algorithms to aid the development of an optimal combination of the techniques to better monitor ice 9and liquid water clouds in overlapped conditions.

Smoke, Clouds and Radiation Brazil NASA ER-2 Moderate Resolution Imaging Spectrometer (MODIS) Airborne Simulator (MAS) Data

Data.gov (United States)

National Aeronautics and Space Administration — SCARB_ER2_MAS data are Smoke, Clouds and Radiation Brazil (SCARB) NASA ER2 Moderate Resolution Imaging Spectrometer (MODIS) Airborne Simulator (MAS)...

Managing IaaS and DBaaS clouds with Oracle Enterprise Manager Cloud Control 12c

CERN Document Server

Antani, Ved

2013-01-01

This book is a step-by-step tutorial filled with practical examples which will show readers how to configure and manage IaaS and DBaaS with Oracle Enterprise Manager.If you are a cloud administrator or a user of self-service provisioning systems offered by Enterprise Manager, this book is ideal for you. It will also help administrators who want to understand the chargeback mechanism offered by Enterprise Manager.An understanding of the basic building blocks of cloud computing such as networking, virtualization, storage, and so on, is needed by those of you interested in this book

The Economic and Social Value of an Image Exchange Network: A Case for the Cloud.

Science.gov (United States)

Mayo, Ray Cody; Pearson, Kathryn L; Avrin, David E; Leung, Jessica W T

2017-01-01

As the health care environment continually changes, radiologists look to the ACR's Imaging 3.0 ® initiative to guide the search for value. By leveraging new technology, a cloud-based image exchange network could provide secure universal access to prior images, which were previously siloed, to facilitate accurate interpretation, improved outcomes, and reduced costs. The breast imaging department represents a viable starting point given the robust data supporting the benefit of access to prior imaging studies, existing infrastructure for image sharing, and the current workflow reliance on prior images. This concept is scalable not only to the remainder of the radiology department but also to the broader medical record. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

The Risks of Cloud Computing in Accounting Field and the Solution Offers: The Case of Turkey

Directory of Open Access Journals (Sweden)

Serap Özdemir

2015-03-01

Full Text Available Cloud is the system that maintains common information sharing among the information devices. It is known that there are always risks and that hundred per cent safety is not available in the environments of information technology. Service providers that operate in accounting sector and utilize the cloud technology are responsible for keeping and preserving the digital financial data that are vitally important for the companies. Service providers need to take all the necessary technical measures, so that the digital data are not damaged, lost and possessed by the malicious third parties. The establishments that provide service for accounting systems by utilizing the cloud computing opportunities in accounting field need to consider the general and co untry-specific risks of cloud computing technology. Therefore, they need to build the necessary technical infrastructure and models in order to run the system flawlessly and to preserve the digital data of the establishments in a secure environment.

The AMCE (AIST Managed Cloud Environment)

Science.gov (United States)

Cook, S.

2017-12-01

ESTO has developed and implemented the AIST Managed Cloud Environment (AMCE) to offer cloud computing services to SMD-funded PIs to conduct their project research. AIST will provide projects access to a cloud computing framework that incorporates NASA security, technical, and financial standards, on which project can freely store, run, and process data. Currently, many projects led by research groups outside of NASA do not have the awareness of requirements or the resources to implement NASA standards into their research, which limits the likelihood of infusing the work into NASA applications. Offering this environment to PIs allows them to conduct their project research using the many benefits of cloud computing. In addition to the well-known cost and time savings that it allows, it also provides scalability and flexibility. The AMCE facilitates infusion and end user access by ensuring standardization and security. This approach will ultimately benefit ESTO, the science community, and the research, allowing the technology developments to have quicker and broader applications.

Emerging Cloud Computing Security Threats

OpenAIRE

Ahmat, Kamal

2015-01-01

Cloud computing is one of the latest emerging innovations of the modern internet and technological landscape. With everyone from the White house to major online technological leaders like Amazon and Google using or offering cloud computing services it is truly presents itself as an exciting and innovative method to store and use data on the internet.

A Survey Paper on Privacy Issue in Cloud Computing

OpenAIRE

Yousra Abdul Alsahib S. Aldeen; Mazleena Salleh; Mohammad Abdur Razzaque

2015-01-01

In past few years, cloud computing is one of the popular paradigm to host and deliver services over Internet. It is having popularity by offering multiple computing services as cloud storage, cloud hosting and cloud servers etc., for various types of businesses as well as in academics. Though there are several benefits of cloud computing, it suffers from security and privacy challenges. Privacy of cloud system is a serious concern for the customers. Considering the privacy within the cloud th...

Implementing and developing cloud computing applications

CERN Document Server

Sarna, David E Y

2010-01-01

From small start-ups to major corporations, companies of all sizes have embraced cloud computing for the scalability, reliability, and cost benefits it can provide. It has even been said that cloud computing may have a greater effect on our lives than the PC and dot-com revolutions combined.Filled with comparative charts and decision trees, Implementing and Developing Cloud Computing Applications explains exactly what it takes to build robust and highly scalable cloud computing applications in any organization. Covering the major commercial offerings available, it provides authoritative guidan

"BPELanon": Protect Business Processes on the Cloud

OpenAIRE

Marigianna Skouradaki; Dieter Roller; Frank Leymann; Vincenzo Ferme; Cesare Pautasso

2015-01-01

The advent of Cloud computing supports the offering of many Business Process Management applications on a distributed per use basis environment through its infrastructure. Due to the fact that privacy is still an open issue in the Cloud many companies are reluctant to move their Business Processes on a public Cloud. Since the Cloud environment can be beneficiary for the Business Processes the investigation of privacy issues needs to be further examined. In order to enforce the Business Proces...

Tharsis Limb Cloud

Science.gov (United States)

2005-01-01

[figure removed for brevity, see original site] Annotated image of Tharsis Limb Cloud 7 September 2005 This composite of red and blue Mars Global Surveyor (MGS) Mars Orbiter Camera (MOC) daily global images acquired on 6 July 2005 shows an isolated water ice cloud extending more than 30 kilometers (more than 18 miles) above the martian surface. Clouds such as this are common in late spring over the terrain located southwest of the Arsia Mons volcano. Arsia Mons is the dark, oval feature near the limb, just to the left of the 'T' in the 'Tharsis Montes' label. The dark, nearly circular feature above the 'S' in 'Tharsis' is the volcano, Pavonis Mons, and the other dark circular feature, above and to the right of 's' in 'Montes,' is Ascraeus Mons. Illumination is from the left/lower left. Season: Northern Autumn/Southern Spring

Computing in the Clouds

Science.gov (United States)

Johnson, Doug

2010-01-01

Web-based applications offer teachers, students, and school districts a convenient way to accomplish a wide range of tasks, from accounting to word processing, for free. Cloud computing has the potential to offer staff and students better services at a lower cost than the technology deployment models they're using now. Saving money and improving…

A New Method of Cloud Detection Based on Cascaded AdaBoost

International Nuclear Information System (INIS)

Ma, C; Chen, F; Liu, J; Duan, J

2014-01-01

Cloud detection of remote sensing image is a critical step in the processing of the remote sensing images. How to quickly, accurately and effectively detect cloud on remote sensing images, is still a challenging issue in this area. In order to avoid disadvantages of the current algorithms, the cascaded AdaBoost classifier algorithm is successfully applied to the cloud detection. A new algorithm combined cascaded AdaBoost classifier and multi-features, is proposed in this paper. First, multi-features based on the color, texture and spectral features are extracted from the remote sensing image. Second, the automatic cloud detection model is obtained based on the cascaded AdaBoost algorithm. In this paper, the results show that the new algorithm can determine cloud detection model and threshold values adaptively for different resolution remote sensing training data. The accuracy of cloud detection is improved. So it is a new effective algorithm for the cloud detection of remote sensing images

A study on strategic provisioning of cloud computing services.

Science.gov (United States)

Whaiduzzaman, Md; Haque, Mohammad Nazmul; Rejaul Karim Chowdhury, Md; Gani, Abdullah

2014-01-01

Cloud computing is currently emerging as an ever-changing, growing paradigm that models "everything-as-a-service." Virtualised physical resources, infrastructure, and applications are supplied by service provisioning in the cloud. The evolution in the adoption of cloud computing is driven by clear and distinct promising features for both cloud users and cloud providers. However, the increasing number of cloud providers and the variety of service offerings have made it difficult for the customers to choose the best services. By employing successful service provisioning, the essential services required by customers, such as agility and availability, pricing, security and trust, and user metrics can be guaranteed by service provisioning. Hence, continuous service provisioning that satisfies the user requirements is a mandatory feature for the cloud user and vitally important in cloud computing service offerings. Therefore, we aim to review the state-of-the-art service provisioning objectives, essential services, topologies, user requirements, necessary metrics, and pricing mechanisms. We synthesize and summarize different provision techniques, approaches, and models through a comprehensive literature review. A thematic taxonomy of cloud service provisioning is presented after the systematic review. Finally, future research directions and open research issues are identified.

A Study on Strategic Provisioning of Cloud Computing Services

Directory of Open Access Journals (Sweden)

Md Whaiduzzaman

2014-01-01

Full Text Available Cloud computing is currently emerging as an ever-changing, growing paradigm that models “everything-as-a-service.” Virtualised physical resources, infrastructure, and applications are supplied by service provisioning in the cloud. The evolution in the adoption of cloud computing is driven by clear and distinct promising features for both cloud users and cloud providers. However, the increasing number of cloud providers and the variety of service offerings have made it difficult for the customers to choose the best services. By employing successful service provisioning, the essential services required by customers, such as agility and availability, pricing, security and trust, and user metrics can be guaranteed by service provisioning. Hence, continuous service provisioning that satisfies the user requirements is a mandatory feature for the cloud user and vitally important in cloud computing service offerings. Therefore, we aim to review the state-of-the-art service provisioning objectives, essential services, topologies, user requirements, necessary metrics, and pricing mechanisms. We synthesize and summarize different provision techniques, approaches, and models through a comprehensive literature review. A thematic taxonomy of cloud service provisioning is presented after the systematic review. Finally, future research directions and open research issues are identified.

A Registration Method Based on Contour Point Cloud for 3D Whole-Body PET and CT Images

Directory of Open Access Journals (Sweden)

Zhiying Song

2017-01-01

Full Text Available The PET and CT fusion image, combining the anatomical and functional information, has important clinical meaning. An effective registration of PET and CT images is the basis of image fusion. This paper presents a multithread registration method based on contour point cloud for 3D whole-body PET and CT images. Firstly, a geometric feature-based segmentation (GFS method and a dynamic threshold denoising (DTD method are creatively proposed to preprocess CT and PET images, respectively. Next, a new automated trunk slices extraction method is presented for extracting feature point clouds. Finally, the multithread Iterative Closet Point is adopted to drive an affine transform. We compare our method with a multiresolution registration method based on Mattes Mutual Information on 13 pairs (246~286 slices per pair of 3D whole-body PET and CT data. Experimental results demonstrate the registration effectiveness of our method with lower negative normalization correlation (NC = −0.933 on feature images and less Euclidean distance error (ED = 2.826 on landmark points, outperforming the source data (NC = −0.496, ED = 25.847 and the compared method (NC = −0.614, ED = 16.085. Moreover, our method is about ten times faster than the compared one.

Opaque cloud detection

Science.gov (United States)

Roskovensky, John K [Albuquerque, NM

2009-01-20

A method of detecting clouds in a digital image comprising, for an area of the digital image, determining a reflectance value in at least three discrete electromagnetic spectrum bands, computing a first ratio of one reflectance value minus another reflectance value and the same two values added together, computing a second ratio of one reflectance value and another reflectance value, choosing one of the reflectance values, and concluding that an opaque cloud exists in the area if the results of each of the two computing steps and the choosing step fall within three corresponding predetermined ranges.

Cloud Detection by Fusing Multi-Scale Convolutional Features

Science.gov (United States)

Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang

2018-04-01

Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.

Foundations of Blueprint for Cloud-based Service Engineering

OpenAIRE

Nguyen, D.K.

2011-01-01

Current cloud-based service offerings are often provided as one-size-fits-all solution and give little or no room for customization. This limits the ability for application developers to pick and choose offerings from multiple software, platform and infrastructure service providers and configure them dynamically and in an optimal fashion to address their application requirements. Furthermore, combining different independent cloud-based services necessitates a uniform description format that f...

Factors influencing the organizational adoption of cloud computing: a survey among cloud workers

Directory of Open Access Journals (Sweden)

Mark Stieninger

2018-01-01

Full Text Available Cloud computing presents an opportunity for organizations to leverage affordable, scalable, and agile technologies. However, even with the demonstrated value of cloud computing, organizations have been hesitant to adopt such technologies. Based on a multi-theoretical research model, this paper provides an empirical study targeted to better understand the adoption of cloud services. An online survey addressing the factors derived from literature for three specific popular cloud application types (cloud storage, cloud mail and cloud office was undertaken. The research model was analyzed by using variance-based structural equation modelling. Results show that the factors of compatibility, relative advantage, security and trust, as well as, a lower level of complexity lead to a more positive attitude towards cloud adoption. Complexity, compatibility, image and security and trust have direct and indirect effects on relative advantage. These factors further explain a large part of the attitude towards cloud adoption but not of its usage.

Eleven quick tips for architecting biomedical informatics workflows with cloud computing

Science.gov (United States)

Moore, Jason H.

2018-01-01

Cloud computing has revolutionized the development and operations of hardware and software across diverse technological arenas, yet academic biomedical research has lagged behind despite the numerous and weighty advantages that cloud computing offers. Biomedical researchers who embrace cloud computing can reap rewards in cost reduction, decreased development and maintenance workload, increased reproducibility, ease of sharing data and software, enhanced security, horizontal and vertical scalability, high availability, a thriving technology partner ecosystem, and much more. Despite these advantages that cloud-based workflows offer, the majority of scientific software developed in academia does not utilize cloud computing and must be migrated to the cloud by the user. In this article, we present 11 quick tips for architecting biomedical informatics workflows on compute clouds, distilling knowledge gained from experience developing, operating, maintaining, and distributing software and virtualized appliances on the world’s largest cloud. Researchers who follow these tips stand to benefit immediately by migrating their workflows to cloud computing and embracing the paradigm of abstraction. PMID:29596416

Eleven quick tips for architecting biomedical informatics workflows with cloud computing.

Science.gov (United States)

Cole, Brian S; Moore, Jason H

2018-03-01

Cloud computing has revolutionized the development and operations of hardware and software across diverse technological arenas, yet academic biomedical research has lagged behind despite the numerous and weighty advantages that cloud computing offers. Biomedical researchers who embrace cloud computing can reap rewards in cost reduction, decreased development and maintenance workload, increased reproducibility, ease of sharing data and software, enhanced security, horizontal and vertical scalability, high availability, a thriving technology partner ecosystem, and much more. Despite these advantages that cloud-based workflows offer, the majority of scientific software developed in academia does not utilize cloud computing and must be migrated to the cloud by the user. In this article, we present 11 quick tips for architecting biomedical informatics workflows on compute clouds, distilling knowledge gained from experience developing, operating, maintaining, and distributing software and virtualized appliances on the world's largest cloud. Researchers who follow these tips stand to benefit immediately by migrating their workflows to cloud computing and embracing the paradigm of abstraction.

Eleven quick tips for architecting biomedical informatics workflows with cloud computing.

Directory of Open Access Journals (Sweden)

Brian S Cole

2018-03-01

Full Text Available Cloud computing has revolutionized the development and operations of hardware and software across diverse technological arenas, yet academic biomedical research has lagged behind despite the numerous and weighty advantages that cloud computing offers. Biomedical researchers who embrace cloud computing can reap rewards in cost reduction, decreased development and maintenance workload, increased reproducibility, ease of sharing data and software, enhanced security, horizontal and vertical scalability, high availability, a thriving technology partner ecosystem, and much more. Despite these advantages that cloud-based workflows offer, the majority of scientific software developed in academia does not utilize cloud computing and must be migrated to the cloud by the user. In this article, we present 11 quick tips for architecting biomedical informatics workflows on compute clouds, distilling knowledge gained from experience developing, operating, maintaining, and distributing software and virtualized appliances on the world's largest cloud. Researchers who follow these tips stand to benefit immediately by migrating their workflows to cloud computing and embracing the paradigm of abstraction.

Mesoscale circulation at the upper cloud level at middle latitudes from the imaging by Venus Monitoring Camera onboard Venus Express

Science.gov (United States)

Patsaeva, Marina; Ignatiev, Nikolay; Markiewicz, Wojciech; Khatuntsev, Igor; Titov, Dmitrij; Patsaev, Dmitry

The Venus Monitoring Camera onboard ESA Venus Express spacecraft acquired a great number of UV images (365 nm) allowing us to track the motion of cloud features at the upper cloud layer of Venus. A digital method developed to analyze correlation functions between two UV images provided wind vector fields on the Venus day side (9-16 hours local time) from the equator to high latitudes. Sizes and regions for the correlation were chosen empirically, as a trade-off of sensitivity against noise immunity and vary from 10(°) x7.5(°) to 20(°) x10(°) depending on the grid step, making this method suitable to investigate the mesoscale circulation. Previously, the digital method was used for investigation of the circulation at low latitudes and provided good agreement with manual tracking of the motion of cloud patterns. Here we present first results obtained by this method for middle latitudes (25(°) S-75(°) S) on the basis of 270 orbits. Comparing obtained vector fields with images for certain orbits, we found a relationship between morphological patterns of the cloud cover at middle latitudes and parameters of the circulation. Elongated cloud features, so-called streaks, are typical for middle latitudes, and their orientation varies over wide range. The behavior of the vector field of velocities depends on the angle between the streak and latitude circles. In the middle latitudes the average angle of the flow deviation from the zonal direction is equal to -5.6(°) ± 1(°) (the sign “-“ means the poleward flow, the standard error is given). For certain orbits, this angle varies from -15.6(°) ± 1(°) to 1.4(°) ± 1(°) . In some regions at latitudes above 60(°) S the meridional wind is equatorward in the morning. The relationship between the cloud cover morphology and circulation peculiarity can be attributed to the motion of the Y-feature in the upper cloud layer due to the super-rotation of the atmosphere.

CIMIDx: Prototype for a Cloud-Based System to Support Intelligent Medical Image Diagnosis With Efficiency.

Science.gov (United States)

Bhavani, Selvaraj Rani; Senthilkumar, Jagatheesan; Chilambuchelvan, Arul Gnanaprakasam; Manjula, Dhanabalachandran; Krishnamoorthy, Ramasamy; Kannan, Arputharaj

2015-03-27

The Internet has greatly enhanced health care, helping patients stay up-to-date on medical issues and general knowledge. Many cancer patients use the Internet for cancer diagnosis and related information. Recently, cloud computing has emerged as a new way of delivering health services but currently, there is no generic and fully automated cloud-based self-management intervention for breast cancer patients, as practical guidelines are lacking. We investigated the prevalence and predictors of cloud use for medical diagnosis among women with breast cancer to gain insight into meaningful usage parameters to evaluate the use of generic, fully automated cloud-based self-intervention, by assessing how breast cancer survivors use a generic self-management model. The goal of this study was implemented and evaluated with a new prototype called "CIMIDx", based on representative association rules that support the diagnosis of medical images (mammograms). The proposed Cloud-Based System Support Intelligent Medical Image Diagnosis (CIMIDx) prototype includes two modules. The first is the design and development of the CIMIDx training and test cloud services. Deployed in the cloud, the prototype can be used for diagnosis and screening mammography by assessing the cancers detected, tumor sizes, histology, and stage of classification accuracy. To analyze the prototype's classification accuracy, we conducted an experiment with data provided by clients. Second, by monitoring cloud server requests, the CIMIDx usage statistics were recorded for the cloud-based self-intervention groups. We conducted an evaluation of the CIMIDx cloud service usage, in which browsing functionalities were evaluated from the end-user's perspective. We performed several experiments to validate the CIMIDx prototype for breast health issues. The first set of experiments evaluated the diagnostic performance of the CIMIDx framework. We collected medical information from 150 breast cancer survivors from hospitals

CloudMC: a cloud computing application for Monte Carlo simulation.

Science.gov (United States)

Miras, H; Jiménez, R; Miras, C; Gomà, C

2013-04-21

This work presents CloudMC, a cloud computing application-developed in Windows Azure®, the platform of the Microsoft® cloud-for the parallelization of Monte Carlo simulations in a dynamic virtual cluster. CloudMC is a web application designed to be independent of the Monte Carlo code in which the simulations are based-the simulations just need to be of the form: input files → executable → output files. To study the performance of CloudMC in Windows Azure®, Monte Carlo simulations with penelope were performed on different instance (virtual machine) sizes, and for different number of instances. The instance size was found to have no effect on the simulation runtime. It was also found that the decrease in time with the number of instances followed Amdahl's law, with a slight deviation due to the increase in the fraction of non-parallelizable time with increasing number of instances. A simulation that would have required 30 h of CPU on a single instance was completed in 48.6 min when executed on 64 instances in parallel (speedup of 37 ×). Furthermore, the use of cloud computing for parallel computing offers some advantages over conventional clusters: high accessibility, scalability and pay per usage. Therefore, it is strongly believed that cloud computing will play an important role in making Monte Carlo dose calculation a reality in future clinical practice.

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Daytime Cloud Optical and Microphysical Properties (DCOMP) from NDE

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains a high quality Environmental Data Record (EDR) of daytime cloud optical and microphysical properties (DCOMP) from the Visible Infrared Imaging...

Research on cloud computing solutions

Directory of Open Access Journals (Sweden)

Liudvikas Kaklauskas

2015-07-01

Full Text Available Cloud computing can be defined as a new style of computing in which dynamically scala-ble and often virtualized resources are provided as a services over the Internet. Advantages of the cloud computing technology include cost savings, high availability, and easy scalability. Voas and Zhang adapted six phases of computing paradigms, from dummy termi-nals/mainframes, to PCs, networking computing, to grid and cloud computing. There are four types of cloud computing: public cloud, private cloud, hybrid cloud and community. The most common and well-known deployment model is Public Cloud. A Private Cloud is suited for sensitive data, where the customer is dependent on a certain degree of security.According to the different types of services offered, cloud computing can be considered to consist of three layers (services models: IaaS (infrastructure as a service, PaaS (platform as a service, SaaS (software as a service. Main cloud computing solutions: web applications, data hosting, virtualization, database clusters and terminal services. The advantage of cloud com-puting is the ability to virtualize and share resources among different applications with the objective for better server utilization and without a clustering solution, a service may fail at the moment the server crashes.DOI: 10.15181/csat.v2i2.914

Analysis of co-located MODIS and CALIPSO observations near clouds

Directory of Open Access Journals (Sweden)

T. Várnai

2012-02-01

Full Text Available This paper aims at helping synergistic studies in combining data from different satellites for gaining new insights into two critical yet poorly understood aspects of anthropogenic climate change, aerosol-cloud interactions and aerosol radiative effects. In particular, the paper examines the way cloud information from the MODIS (MODerate resolution Imaging Spectroradiometer imager can refine our perceptions based on CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization lidar measurements about the systematic aerosol changes that occur near clouds.

The statistical analysis of a yearlong dataset of co-located global maritime observations from the Aqua and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation satellites reveals that MODIS's multispectral imaging ability can greatly help the interpretation of CALIOP observations. The results show that imagers on Aqua and CALIPSO yield very similar pictures, and that the discrepancies – due mainly to wind drift and differences in view angle – do not significantly hinder aerosol measurements near clouds. By detecting clouds outside the CALIOP track, MODIS reveals that clouds are usually closer to clear areas than CALIOP data alone would suggest. The paper finds statistical relationships between the distances to clouds in MODIS and CALIOP data, and proposes a rescaling approach to statistically account for the impact of clouds outside the CALIOP track even when MODIS cannot reliably detect low clouds, for example at night or over sea ice. Finally, the results show that the typical distance to clouds depends on both cloud coverage and cloud type, and accordingly varies with location and season. In maritime areas perceived cloud free, the global median distance to clouds below 3 km altitude is in the 4–5 km range.

Cloud Computing Security Issues and Challenges

OpenAIRE

Kuyoro S. O.; Ibikunle F; Awodele O

2011-01-01

Cloud computing is a set of IT services that are provided to a customer over a network on a leased basis and with the ability to scale up or down their service requirements. Usually cloud computing services are delivered by a third party provider who owns the infrastructure. It advantages to mention but a few include scalability, resilience, flexibility, efficiency and outsourcing non-core activities. Cloud computing offers an innovative business model for organizations to adopt IT services w...

Sahara Dust Cloud

Science.gov (United States)

2005-01-01

[figure removed for brevity, see original site] Dust Particles Click on the image for Quicktime movie from 7/15-7/24 A continent-sized cloud of hot air and dust originating from the Sahara Desert crossed the Atlantic Ocean and headed towards Florida and the Caribbean. A Saharan Air Layer, or SAL, forms when dry air and dust rise from Africa's west coast and ride the trade winds above the Atlantic Ocean. These dust clouds are not uncommon, especially during the months of July and August. They start when weather patterns called tropical waves pick up dust from the desert in North Africa, carry it a couple of miles into the atmosphere and drift westward. In a sequence of images created by data acquired by the Earth-orbiting Atmospheric Infrared Sounder ranging from July 15 through July 24, we see the distribution of the cloud in the atmosphere as it swirls off of Africa and heads across the ocean to the west. Using the unique silicate spectral signatures of dust in the thermal infrared, AIRS can detect the presence of dust in the atmosphere day or night. This detection works best if there are no clouds present on top of the dust; when clouds are present, they can interfere with the signal, making it much harder to detect dust as in the case of July 24, 2005. In the Quicktime movie, the scale at the bottom of the images shows +1 for dust definitely detected, and ranges down to -1 for no dust detected. The plots are averaged over a number of AIRS observations falling within grid boxes, and so it is possible to obtain fractional numbers. [figure removed for brevity, see original site] Total Water Vapor in the Atmosphere Around the Dust Cloud Click on the image for Quicktime movie The dust cloud is contained within a dry adiabatic layer which originates over the Sahara Desert. This Saharan Air Layer (SAL) advances Westward over the Atlantic Ocean, overriding the cool, moist air nearer the surface. This burst of very dry air is visible in the AIRS retrieved total water

Prior-Based Quantization Bin Matching for Cloud Storage of JPEG Images.

Science.gov (United States)

Liu, Xianming; Cheung, Gene; Lin, Chia-Wen; Zhao, Debin; Gao, Wen

2018-07-01

Millions of user-generated images are uploaded to social media sites like Facebook daily, which translate to a large storage cost. However, there exists an asymmetry in upload and download data: only a fraction of the uploaded images are subsequently retrieved for viewing. In this paper, we propose a cloud storage system that reduces the storage cost of all uploaded JPEG photos, at the expense of a controlled increase in computation mainly during download of requested image subset. Specifically, the system first selectively re-encodes code blocks of uploaded JPEG images using coarser quantization parameters for smaller storage sizes. Then during download, the system exploits known signal priors-sparsity prior and graph-signal smoothness prior-for reverse mapping to recover original fine quantization bin indices, with either deterministic guarantee (lossless mode) or statistical guarantee (near-lossless mode). For fast reverse mapping, we use small dictionaries and sparse graphs that are tailored for specific clusters of similar blocks, which are classified via tree-structured vector quantizer. During image upload, cluster indices identifying the appropriate dictionaries and graphs for the re-quantized blocks are encoded as side information using a differential distributed source coding scheme to facilitate reverse mapping during image download. Experimental results show that our system can reap significant storage savings (up to 12.05%) at roughly the same image PSNR (within 0.18 dB).

Risk and reward in the cloud. Choosing a cloud vendor involves weighing risks versus benefits.

Science.gov (United States)

Degaspari, John

2012-05-01

More hospitals are looking to the cloud as a viable way to store clinical, imaging, and financial data. Experts acknowledge its advantages, but caution it's a step that requires careful planning and vetting of potential cloud vendors.

Simplified cloud-oriented virtual machine management with MLN

OpenAIRE

Begnum, Kyrre

2010-01-01

System administrators are faced with the challenge of making their existing systems power-efficient and scalable. Although Cloud Computing is offered as a solution to this challenge by many, we argue that having multiple interfaces and cloud providers can result in more complexity than before. This paper addresses cloud computing from a user perspective. We show how complex scenarios, such as an on-demand render farm and scaling web-service, can be achieved utilizing clouds ...

Life in the clouds: are tropical montane cloud forests responding to changes in climate?

Science.gov (United States)

Hu, Jia; Riveros-Iregui, Diego A

2016-04-01

The humid tropics represent only one example of the many places worldwide where anthropogenic disturbance and climate change are quickly affecting the feedbacks between water and trees. In this article, we address the need for a more long-term perspective on the effects of climate change on tropical montane cloud forests (TMCF) in order to fully assess the combined vulnerability and long-term response of tropical trees to changes in precipitation regimes, including cloud immersion. We first review the ecophysiological benefits that cloud water interception offers to trees in TMCF and then examine current climatological evidence that suggests changes in cloud base height and impending changes in cloud immersion for TMCF. Finally, we propose an experimental approach to examine the long-term dynamics of tropical trees in TMCF in response to environmental conditions on decade-to-century time scales. This information is important to assess the vulnerability and long-term response of TMCF to changes in cloud cover and fog frequency and duration.

A Study of Application Layer Paradigm for Lower Layer Energy Saving Potentials in Cloud-Edge Social User Wireless Image Sharing

Directory of Open Access Journals (Sweden)

Wei Wang

2015-08-01

Full Text Available Energy saving becomes critical in modern cloud wireless multimedia and mobile communication systems. In this paper we propose to study a new paradigm named application layer Position-Value diversity for wireless image sharing for cloud-edge communications, which has significant energy saving potentials for modern wireless networking systems. In this new paradigm, saving energy is achieved by looking into application layer imaging traffic, in stead of MAC-PHY protocols at lower layers, and partitioning it into important positions and unimportant values. This paradigm could be integrated to existing wavelet-based tree compression, and truncation of image bit streams could be performed with regards to wireless communication energy budget estimation. Simulation results demonstrated that there are significant potentials of communication energy efficiency gain and Quality of Experience (QoE enhancement in wireless image communication systems.

First correlated measurements of the shape and scattering properties of cloud particles using the new Particle Habit Imaging and Polar Scattering (PHIPS) probe

Science.gov (United States)

Abdelmonem, A.; Schnaiter, M.; Amsler, P.; Hesse, E.; Meyer, J.; Leisner, T.

2011-05-01

Studying the radiative impact of cirrus clouds requires the knowledge of the link between their microphysics and the single scattering properties of the cloud particles. Usually, this link is created by modeling the optical scattering properties from in situ measurements of ice crystal size distributions. The measured size distribution and the assumed particle shape might be erroneous in case of non-spherical ice particles. We present here a novel optical sensor (the Particle Habit Imaging and Polar Scattering probe, PHIPS) designed to measure the 3-D morphology and the corresponding optical and microphysical parameters of individual cloud particles, simultaneously. Clouds containing particles ranging in size from a few micrometers to about 800 μm diameter can be systematically characterized with an optical resolution power of 2 μm and polar scattering resolution of 1° for forward scattering directions (from 1° to 10°) and 8° for side and backscattering directions (from 18° to 170°). The maximum acquisition rates for scattering phase functions and images are 262 KHz and 10 Hz, respectively. Some preliminary results collected in two ice cloud campaigns which were conducted in the AIDA cloud simulation chamber are presented. PHIPS showed reliability in operation and produced comparable size distributions and images to those given by other certified cloud particles instruments. A 3-D model of a hexagonal ice plate is constructed and the corresponding scattering phase function is compared to that modeled using the Ray Tracing with Diffraction on Facets (RTDF) program. PHIPS is candidate to be a novel air borne optical sensor for studying the radiative impact of cirrus clouds and correlating the particle habit-scattering properties which will serve as a reference for other single, or multi-independent, measurements instruments.

All your clouds are belong to us - Security analysis of cloud management interfaces

DEFF Research Database (Denmark)

Somorovsky, Juraj; Heiderich, Mario; Jensen, Meiko

2011-01-01

a complete power over the victim's account, with all the stored data included. In this paper, we provide a security analysis pertaining to the control interfaces of a large Public Cloud (Amazon) and a widely used Private Cloud software (Eucalyptus). Our research results are alarming: in regards to the Amazon......Cloud Computing resources are handled through control interfaces. It is through these interfaces that the new machine images can be added, existing ones can be modified, and instances can be started or ceased. Effectively, a successful attack on a Cloud control interface grants the attacker...... discoveries, we additionally describe the countermea-sures against these attacks, as well as introduce a novel "black box" analysis methodology for public Cloud interfaces....

Privacy-preserving security solution for cloud services

OpenAIRE

L. Malina; J. Hajny; P. Dzurenda; V. Zeman

2015-01-01

We propose a novel privacy-preserving security solution for cloud services. Our solution is based on an efficient non-bilinear group signature scheme providing the anonymous access to cloud services and shared storage servers. The novel solution offers anonymous authenticationfor registered users. Thus, users' personal attributes (age, valid registration, successful payment) can be proven without revealing users' identity, and users can use cloud services without any threat of profiling their...

On Cloud-Based Engineering of Dependable Systems

OpenAIRE

Alajrami, Sami

2014-01-01

The cloud computing paradigm is being adopted by many organizations in different application domains as it is cost effective and offers a virtually unlimited pool of resources. Engineering critical systems can benefit from clouds in attaining all dependability means: fault tolerance, fault prevention, fault removal and fault forecasting. Our research aims to investigate the potential of supporting engineering of dependable software systems with cloud computing and proposes an open, extensible...

CloudGC: Recycling Idle Virtual Machines in the Cloud

OpenAIRE

Zhang , Bo; Al-Dhuraibi , Yahya; Rouvoy , Romain; Paraiso , Fawaz; Seinturier , Lionel

2017-01-01

International audience; Cloud computing conveys the image of a pool of unlimited virtual resources that can be quickly and easily provisioned to accommodate the user requirements. However, this flexibility may require to adjust physical resources at the infrastructure level to keep the pace of user requests. While elasticity can be considered as the de facto solution to support this issue, this elasticity can still be broken by budget requirements or physical limitations of a private cloud. I...

Automated Detection of Cloud and Cloud Shadow in Single-Date Landsat Imagery Using Neural Networks and Spatial Post-Processing

Directory of Open Access Journals (Sweden)

M. Joseph Hughes

2014-05-01

Full Text Available The use of Landsat data to answer ecological questions is greatly increased by the effective removal of cloud and cloud shadow from satellite images. We develop a novel algorithm to identify and classify clouds and cloud shadow, SPARCS: Spatial Procedures for Automated Removal of Cloud and Shadow. The method uses a neural network approach to determine cloud, cloud shadow, water, snow/ice and clear sky classification memberships of each pixel in a Landsat scene. It then applies a series of spatial procedures to resolve pixels with ambiguous membership by using information, such as the membership values of neighboring pixels and an estimate of cloud shadow locations from cloud and solar geometry. In a comparison with FMask, a high-quality cloud and cloud shadow classification algorithm currently available, SPARCS performs favorably, with substantially lower omission errors for cloud shadow (8.0% and 3.2%, only slightly higher omission errors for clouds (0.9% and 1.3%, respectively and fewer errors of commission (2.6% and 0.3%. Additionally, SPARCS provides a measure of uncertainty in its classification that can be exploited by other algorithms that require clear sky pixels. To illustrate this, we present an application that constructs obstruction-free composites of images acquired on different dates in support of a method for vegetation change detection.

Benefits of cloud computing for PACS and archiving.

Science.gov (United States)

Koch, Patrick

2012-01-01

The goal of cloud-based services is to provide easy, scalable access to computing resources and IT services. The healthcare industry requires a private cloud that adheres to government mandates designed to ensure privacy and security of patient data while enabling access by authorized users. Cloud-based computing in the imaging market has evolved from a service that provided cost effective disaster recovery for archived data to fully featured PACS and vendor neutral archiving services that can address the needs of healthcare providers of all sizes. Healthcare providers worldwide are now using the cloud to distribute images to remote radiologists while supporting advanced reading tools, deliver radiology reports and imaging studies to referring physicians, and provide redundant data storage. Vendor managed cloud services eliminate large capital investments in equipment and maintenance, as well as staffing for the data center--creating a reduction in total cost of ownership for the healthcare provider.

Integrated cloud-aerosol-radiation product using CERES, MODIS, CALIPSO, and CloudSat data

Science.gov (United States)

Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Gibson, Sharon; Yi, Yuhong; Trepte, Qing; Wielicki, Bruce; Kato, Seiji; Winker, Dave; Stephens, Graeme; Partain, Philip

2007-10-01

This paper documents the development of the first integrated data set of global vertical profiles of clouds, aerosols, and radiation using the combined NASA A-Train data from the Aqua Clouds and Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat. As part of this effort, cloud data from the CALIPSO lidar and the CloudSat radar are merged with the integrated column cloud properties from the CERES-MODIS analyses. The active and passive datasets are compared to determine commonalities and differences in order to facilitate the development of a 3-dimensional cloud and aerosol dataset that will then be integrated into the CERES broadband radiance footprint. Preliminary results from the comparisons for April 2007 reveal that the CERES-MODIS global cloud amounts are, on average, 0.14 less and 0.15 greater than those from CALIPSO and CloudSat, respectively. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.

Validation of Cloud Properties From Multiple Satellites Using CALIOP Data

Science.gov (United States)

Yost, Christopher R.; Minnis, Patrick; Bedka, Kristopher M.; Heck, Patrick W.; Palikonda, Rabindra; Sun-Mack, Sunny; Trepte, Qing

2016-01-01

The NASA Langley Satellite ClOud and Radiative Property retrieval System (SatCORPS) is routinely applied to multispectral imagery from several geostationary and polar-orbiting imagers to retrieve cloud properties for weather and climate applications. Validation of the retrievals with independent datasets is continuously ongoing in order to understand differences caused by calibration, spatial resolution, viewing geometry, and other factors. The CALIOP instrument provides a decade of detailed cloud observations which can be used to evaluate passive imager retrievals of cloud boundaries, thermodynamic phase, cloud optical depth, and water path on a global scale. This paper focuses on comparisons of CALIOP retrievals to retrievals from MODIS, VIIRS, AVHRR, GOES, SEVIRI, and MTSAT. CALIOP is particularly skilled at detecting weakly-scattering cirrus clouds with optical depths less than approx. 0.5. These clouds are often undetected by passive imagers and the effect this has on the property retrievals is discussed.

Terrestrial laser scanning point clouds time series for the monitoring of slope movements: displacement measurement using image correlation and 3D feature tracking

Science.gov (United States)

Bornemann, Pierrick; Jean-Philippe, Malet; André, Stumpf; Anne, Puissant; Julien, Travelletti

2016-04-01

Dense multi-temporal point clouds acquired with terrestrial laser scanning (TLS) have proved useful for the study of structure and kinematics of slope movements. Most of the existing deformation analysis methods rely on the use of interpolated data. Approaches that use multiscale image correlation provide a precise and robust estimation of the observed movements; however, for non-rigid motion patterns, these methods tend to underestimate all the components of the movement. Further, for rugged surface topography, interpolated data introduce a bias and a loss of information in some local places where the point cloud information is not sufficiently dense. Those limits can be overcome by using deformation analysis exploiting directly the original 3D point clouds assuming some hypotheses on the deformation (e.g. the classic ICP algorithm requires an initial guess by the user of the expected displacement patterns). The objective of this work is therefore to propose a deformation analysis method applied to a series of 20 3D point clouds covering the period October 2007 - October 2015 at the Super-Sauze landslide (South East French Alps). The dense point clouds have been acquired with a terrestrial long-range Optech ILRIS-3D laser scanning device from the same base station. The time series are analyzed using two approaches: 1) a method of correlation of gradient images, and 2) a method of feature tracking in the raw 3D point clouds. The estimated surface displacements are then compared with GNSS surveys on reference targets. Preliminary results tend to show that the image correlation method provides a good estimation of the displacement fields at first order, but shows limitations such as the inability to track some deformation patterns, and the use of a perspective projection that does not maintain original angles and distances in the correlated images. Results obtained with 3D point clouds comparison algorithms (C2C, ICP, M3C2) bring additional information on the

Studi Perbandingan Layanan Cloud Computing

Directory of Open Access Journals (Sweden)

Afdhal Afdhal

2014-03-01

Full Text Available In the past few years, cloud computing has became a dominant topic in the IT area. Cloud computing offers hardware, infrastructure, platform and applications without requiring end-users knowledge of the physical location and the configuration of providers who deliver the services. It has been a good solution to increase reliability, reduce computing cost, and make opportunities to IT industries to get more advantages. The purpose of this article is to present a better understanding of cloud delivery service, correlation and inter-dependency. This article compares and contrasts the different levels of delivery services and the development models, identify issues, and future directions on cloud computing. The end-users comprehension of cloud computing delivery service classification will equip them with knowledge to determine and decide which business model that will be chosen and adopted securely and comfortably. The last part of this article provides several recommendations for cloud computing service providers and end-users.

Lost in Cloud

Science.gov (United States)

Maluf, David A.; Shetye, Sandeep D.; Chilukuri, Sri; Sturken, Ian

2012-01-01

Cloud computing can reduce cost significantly because businesses can share computing resources. In recent years Small and Medium Businesses (SMB) have used Cloud effectively for cost saving and for sharing IT expenses. With the success of SMBs, many perceive that the larger enterprises ought to move into Cloud environment as well. Government agency s stove-piped environments are being considered as candidates for potential use of Cloud either as an enterprise entity or pockets of small communities. Cloud Computing is the delivery of computing as a service rather than as a product, whereby shared resources, software, and information are provided to computers and other devices as a utility over a network. Underneath the offered services, there exists a modern infrastructure cost of which is often spread across its services or its investors. As NASA is considered as an Enterprise class organization, like other enterprises, a shift has been occurring in perceiving its IT services as candidates for Cloud services. This paper discusses market trends in cloud computing from an enterprise angle and then addresses the topic of Cloud Computing for NASA in two possible forms. First, in the form of a public Cloud to support it as an enterprise, as well as to share it with the commercial and public at large. Second, as a private Cloud wherein the infrastructure is operated solely for NASA, whether managed internally or by a third-party and hosted internally or externally. The paper addresses the strengths and weaknesses of both paradigms of public and private Clouds, in both internally and externally operated settings. The content of the paper is from a NASA perspective but is applicable to any large enterprise with thousands of employees and contractors.

All-sky photogrammetry techniques to georeference a cloud field

Science.gov (United States)

Crispel, Pierre; Roberts, Gregory

2018-01-01

In this study, we present a novel method of identifying and geolocalizing cloud field elements from a portable all-sky camera stereo network based on the ground and oriented towards zenith. The methodology is mainly based on stereophotogrammetry which is a 3-D reconstruction technique based on triangulation from corresponding stereo pixels in rectified images. In cases where clouds are horizontally separated, identifying individual positions is performed with segmentation techniques based on hue filtering and contour detection algorithms. Macroscopic cloud field characteristics such as cloud layer base heights and velocity fields are also deduced. In addition, the methodology is fitted to the context of measurement campaigns which impose simplicity of implementation, auto-calibration, and portability. Camera internal geometry models are achieved a priori in the laboratory and validated to ensure a certain accuracy in the peripheral parts of the all-sky image. Then, stereophotogrammetry with dense 3-D reconstruction is applied with cameras spaced 150 m apart for two validation cases. The first validation case is carried out with cumulus clouds having a cloud base height at 1500 m a.g.l. The second validation case is carried out with two cloud layers: a cumulus fractus layer with a base height at 1000 m a.g.l. and an altocumulus stratiformis layer with a base height of 2300 m a.g.l. Velocity fields at cloud base are computed by tracking image rectangular patterns through successive shots. The height uncertainty is estimated by comparison with a Vaisala CL31 ceilometer located on the site. The uncertainty on the horizontal coordinates and on the velocity field are theoretically quantified by using the experimental uncertainties of the cloud base height and camera orientation. In the first cumulus case, segmentation of the image is performed to identify individuals clouds in the cloud field and determine the horizontal positions of the cloud centers.

ASPECTS OF USING CLOUD TECHNOLOGIES IN VIRTUAL LEARNING ENVIRONMENT

OpenAIRE

ZHVANIA, Taliko; KAPANADZE, David; KIKNADZE, Mzia; TANDILASHVILI, George

2016-01-01

Thereare increased using the e-Learning technologies at the modern institutions ofhigher education, which favored to integrate the various instruments in thevirtual learning environment. Recently,the cloud technologies have become the most popular, which offer e-Learninginternet technologies based dynamical and actual new opportunities to theeducational institutions. The cloud technologies provide a high level of theservice and they impact on the design of the training courses, offered servic...

Migrating enterprise storage applications to the cloud

OpenAIRE

Vrable, Michael Daniel

2011-01-01

Cloud computing has emerged as a model for hosting computing infrastructure and outsourcing management of that infrastructure. It offers the promise of simplified provisioning and management, lower costs, and access to resources that scale up and down with demand. Cloud computing has seen growing use for Web site hosting, large batch processing jobs, and similar tasks. Despite potential advantages, however, cloud computing is not much used for enterprise applications such as backup, shared fi...

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Base Height (CBH) Environmental Data Record (EDR) from IDPS

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of Cloud Base Heights (CBH) from the Visible Infrared Imaging Radiometer Suite...

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Cover Layer (CCL) Environmental Data Record (EDR) from IDPS

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality Environmental Data Record (EDR) of Cloud Cover Layers (CCL) from the Visible Infrared Imaging Radiometer Suite (VIIRS)...

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Optical Thickness (COT) Environmental Data Record (EDR) from IDPS

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of Cloud Optical Thickness (COT) from the Visible Infrared Imaging Radiometer Suite...

Distributed Processing in Cloud Computing

OpenAIRE

Mavridis, Ilias; Karatza, Eleni

2016-01-01

Proceedings of the First PhD Symposium on Sustainable Ultrascale Computing Systems (NESUS PhD 2016) Timisoara, Romania. February 8-11, 2016. Cloud computing offers a wide range of resources and services through the Internet that can been used for various purposes. The rapid growth of cloud computing has exempted many companies and institutions from the burden of maintaining expensive hardware and software infrastructure. With characteristics like high scalability, availability ...

Programming Microsoft's Clouds Windows Azure and Office 365

CERN Document Server

Rizzo, Thomas; van Otegem, Michiel; Bishop, Darrin; Durzi, George; Tejada, Zoiner; Mann, David

2012-01-01

A detailed look at a diverse set of Cloud topics, particularly Azure and Office 365 More and more companies are realizing the power and potential of Cloud computing as a viable way to save energy and money. This valuable book offers an in-depth look at a wide range of Cloud topics unlike any other book on the market. Examining how Cloud services allows users to pay as they go for exactly what they use, this guide explains how companies can easily scale their Cloud use up and down to fit their business requirements. After an introduction to Cloud computing, you'll discover how to prepare your e

Point Cloud Classification of Tesserae from Terrestrial Laser Data Combined with Dense Image Matching for Archaeological Information Extraction

Science.gov (United States)

Poux, F.; Neuville, R.; Billen, R.

2017-08-01

Reasoning from information extraction given by point cloud data mining allows contextual adaptation and fast decision making. However, to achieve this perceptive level, a point cloud must be semantically rich, retaining relevant information for the end user. This paper presents an automatic knowledge-based method for pre-processing multi-sensory data and classifying a hybrid point cloud from both terrestrial laser scanning and dense image matching. Using 18 features including sensor's biased data, each tessera in the high-density point cloud from the 3D captured complex mosaics of Germigny-des-prés (France) is segmented via a colour multi-scale abstraction-based featuring extracting connectivity. A 2D surface and outline polygon of each tessera is generated by a RANSAC plane extraction and convex hull fitting. Knowledge is then used to classify every tesserae based on their size, surface, shape, material properties and their neighbour's class. The detection and semantic enrichment method shows promising results of 94% correct semantization, a first step toward the creation of an archaeological smart point cloud.

CloudMC: a cloud computing application for Monte Carlo simulation

International Nuclear Information System (INIS)

Miras, H; Jiménez, R; Miras, C; Gomà, C

2013-01-01

This work presents CloudMC, a cloud computing application—developed in Windows Azure®, the platform of the Microsoft® cloud—for the parallelization of Monte Carlo simulations in a dynamic virtual cluster. CloudMC is a web application designed to be independent of the Monte Carlo code in which the simulations are based—the simulations just need to be of the form: input files → executable → output files. To study the performance of CloudMC in Windows Azure®, Monte Carlo simulations with penelope were performed on different instance (virtual machine) sizes, and for different number of instances. The instance size was found to have no effect on the simulation runtime. It was also found that the decrease in time with the number of instances followed Amdahl's law, with a slight deviation due to the increase in the fraction of non-parallelizable time with increasing number of instances. A simulation that would have required 30 h of CPU on a single instance was completed in 48.6 min when executed on 64 instances in parallel (speedup of 37 ×). Furthermore, the use of cloud computing for parallel computing offers some advantages over conventional clusters: high accessibility, scalability and pay per usage. Therefore, it is strongly believed that cloud computing will play an important role in making Monte Carlo dose calculation a reality in future clinical practice. (note)

Use of the ARM Measurements of Spectral Zenith Radiance for Better Understanding of 3D Cloud-Radiation Processes & Aerosol-Cloud Interaction

Energy Technology Data Exchange (ETDEWEB)

Alexander Marshak; Warren Wiscombe; Yuri Knyazikhin; Christine Chiu

2011-05-24

We proposed a variety of tasks centered on the following question: what can we learn about 3D cloud-radiation processes and aerosol-cloud interaction from rapid-sampling ARM measurements of spectral zenith radiance? These ARM measurements offer spectacular new and largely unexploited capabilities in both the temporal and spectral domains. Unlike most other ARM instruments, which average over many seconds or take samples many seconds apart, the new spectral zenith radiance measurements are fast enough to resolve natural time scales of cloud change and cloud boundaries as well as the transition zone between cloudy and clear areas. In the case of the shortwave spectrometer, the measurements offer high time resolution and high spectral resolution, allowing new discovery-oriented science which we intend to pursue vigorously. Research objectives are, for convenience, grouped under three themes: • Understand radiative signature of the transition zone between cloud-free and cloudy areas using data from ARM shortwave radiometers, which has major climatic consequences in both aerosol direct and indirect effect studies. • Provide cloud property retrievals from the ARM sites and the ARM Mobile Facility for studies of aerosol-cloud interactions. • Assess impact of 3D cloud structures on aerosol properties using passive and active remote sensing techniques from both ARM and satellite measurements.

Cloud fraction and cloud base measurements from scanning Doppler lidar during WFIP-2

Science.gov (United States)

Bonin, T.; Long, C.; Lantz, K. O.; Choukulkar, A.; Pichugina, Y. L.; McCarty, B.; Banta, R. M.; Brewer, A.; Marquis, M.

2017-12-01

The second Wind Forecast Improvement Project (WFIP-2) consisted of an 18-month field deployment of a variety of instrumentation with the principle objective of validating and improving NWP forecasts for wind energy applications in complex terrain. As a part of the set of instrumentation, several scanning Doppler lidars were installed across the study domain to primarily measure profiles of the mean wind and turbulence at high-resolution within the planetary boundary layer. In addition to these measurements, Doppler lidar observations can be used to directly quantify the cloud fraction and cloud base, since clouds appear as a high backscatter return. These supplementary measurements of clouds can then be used to validate cloud cover and other properties in NWP output. Herein, statistics of the cloud fraction and cloud base height from the duration of WFIP-2 are presented. Additionally, these cloud fraction estimates from Doppler lidar are compared with similar measurements from a Total Sky Imager and Radiative Flux Analysis (RadFlux) retrievals at the Wasco site. During mostly cloudy to overcast conditions, estimates of the cloud radiating temperature from the RadFlux methodology are also compared with Doppler lidar measured cloud base height.

Cloud portability and interoperability issues and current trends

CERN Document Server

Di Martino, Beniamino; Esposito, Antonio

2015-01-01

This book offers readers a quick, comprehensive and up-to-date overview of the most important methodologies, technologies, APIs and standards related to the portability and interoperability of cloud applications and services, illustrated by a number of use cases representing a variety of interoperability and portability scenarios. The lack of portability and interoperability between cloud platforms at different service levels is the main issue affecting cloud-based services today. The brokering, negotiation, management, monitoring and reconfiguration of cloud resources are challenging tasks

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Type and Phase Environmental Data Record (EDR) from NDE

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of cloud type and phase from the Visible Infrared Imaging Radiometer Suite (VIIRS)...

GPU-accelerated micromagnetic simulations using cloud computing

Energy Technology Data Exchange (ETDEWEB)

Jermain, C.L., E-mail: clj72@cornell.edu [Cornell University, Ithaca, NY 14853 (United States); Rowlands, G.E.; Buhrman, R.A. [Cornell University, Ithaca, NY 14853 (United States); Ralph, D.C. [Cornell University, Ithaca, NY 14853 (United States); Kavli Institute at Cornell, Ithaca, NY 14853 (United States)

2016-03-01

Highly parallel graphics processing units (GPUs) can improve the speed of micromagnetic simulations significantly as compared to conventional computing using central processing units (CPUs). We present a strategy for performing GPU-accelerated micromagnetic simulations by utilizing cost-effective GPU access offered by cloud computing services with an open-source Python-based program for running the MuMax3 micromagnetics code remotely. We analyze the scaling and cost benefits of using cloud computing for micromagnetics. - Highlights: • The benefits of cloud computing for GPU-accelerated micromagnetics are examined. • We present the MuCloud software for running simulations on cloud computing. • Simulation run times are measured to benchmark cloud computing performance. • Comparison benchmarks are analyzed between CPU and GPU based solvers.

GPU-accelerated micromagnetic simulations using cloud computing

International Nuclear Information System (INIS)

Jermain, C.L.; Rowlands, G.E.; Buhrman, R.A.; Ralph, D.C.

2016-01-01

Highly parallel graphics processing units (GPUs) can improve the speed of micromagnetic simulations significantly as compared to conventional computing using central processing units (CPUs). We present a strategy for performing GPU-accelerated micromagnetic simulations by utilizing cost-effective GPU access offered by cloud computing services with an open-source Python-based program for running the MuMax3 micromagnetics code remotely. We analyze the scaling and cost benefits of using cloud computing for micromagnetics. - Highlights: • The benefits of cloud computing for GPU-accelerated micromagnetics are examined. • We present the MuCloud software for running simulations on cloud computing. • Simulation run times are measured to benchmark cloud computing performance. • Comparison benchmarks are analyzed between CPU and GPU based solvers.

Ten Years of Cloud Properties from MODIS: Global Statistics and Use in Climate Model Evaluation

Science.gov (United States)

Platnick, Steven E.

2011-01-01

The NASA Moderate Resolution Imaging Spectroradiometer (MODIS), launched onboard the Terra and Aqua spacecrafts, began Earth observations on February 24, 2000 and June 24,2002, respectively. Among the algorithms developed and applied to this sensor, a suite of cloud products includes cloud masking/detection, cloud-top properties (temperature, pressure), and optical properties (optical thickness, effective particle radius, water path, and thermodynamic phase). All cloud algorithms underwent numerous changes and enhancements between for the latest Collection 5 production version; this process continues with the current Collection 6 development. We will show example MODIS Collection 5 cloud climatologies derived from global spatial . and temporal aggregations provided in the archived gridded Level-3 MODIS atmosphere team product (product names MOD08 and MYD08 for MODIS Terra and Aqua, respectively). Data sets in this Level-3 product include scalar statistics as well as 1- and 2-D histograms of many cloud properties, allowing for higher order information and correlation studies. In addition to these statistics, we will show trends and statistical significance in annual and seasonal means for a variety of the MODIS cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a MODIS cloud simulator with an accompanying netCDF file containing subsetted monthly Level-3 statistical data sets that correspond to the simulator output. Correlations of cloud properties with ENSO offer the potential to evaluate model cloud sensitivity; initial results will be discussed.

Inside Dropbox: Understanding Personal Cloud Storage Services

NARCIS (Netherlands)

Drago, Idilio; Mellia, Marco; Munafò, Maurizio M.; Sperotto, Anna; Sadre, R.; Pras, Aiko

2012-01-01

Personal cloud storage services are gaining popularity. With a rush of providers to enter the market and an increasing offer of cheap storage space, it is to be expected that cloud storage will soon generate a high amount of Internet traffic. Very little is known about the architecture and the

Cloud computing development in Armenia

Directory of Open Access Journals (Sweden)

Vazgen Ghazaryan

2014-10-01

Full Text Available Purpose – The purpose of the research is to clarify benefits and risks in regards with data protection, cost; business can have by the use of this new technologies for the implementation and management of organization’s information systems.Design/methodology/approach – Qualitative case study of the results obtained via interviews. Three research questions were raised: Q1: How can company benefit from using Cloud Computing compared to other solutions?; Q2: What are possible issues that occur with Cloud Computing?; Q3: How would Cloud Computing change an organizations’ IT infrastructure?Findings – The calculations provided in the interview section prove the financial advantages, even though the precise degree of flexibility and performance has not been assessed. Cloud Computing offers great scalability. Another benefit that Cloud Computing offers, in addition to better performance and flexibility, is reliable and simple backup data storage, physically distributed and so almost invulnerable to damage. Although the advantages of Cloud Computing more than compensate for the difficulties associated with it, the latter must be carefully considered. Since the cloud architecture is relatively new, so far the best guarantee against all risks it entails, from a single company's perspective, is a well-formulated service-level agreement, where the terms of service and the shared responsibility and security roles between the client and the provider are defined.Research limitations/implications – study was carried out on the bases of two companies, which gives deeper view, but for more widely applicable results, a wider analysis is necessary.Practical implications:Originality/Value – novelty of the research depends on the fact that existing approaches on this problem mainly focus on technical side of computing.Research type: case study

Understanding Cloud Requirements - A Supply Chain Lifecycle Approach

OpenAIRE

Lindner, Mark; McDonald, Fiona; Conway, Gerry; Curry, Edward

2011-01-01

Cloud Computing is offering competitive advantages to companies through flexible and, scalable access to computing resources. More and more companies are moving to cloud environments; therefore understanding the requirements for this process is both important and beneficial. The requirements for migrating from a traditional computing environment to a cloud hosting environment are discussed in this paper, considering this migration from a supply chain lifecycle perspective...

Cloud Infrastructures for In Silico Drug Discovery: Economic and Practical Aspects

Science.gov (United States)

Clematis, Andrea; Quarati, Alfonso; Cesini, Daniele; Milanesi, Luciano; Merelli, Ivan

2013-01-01

Cloud computing opens new perspectives for small-medium biotechnology laboratories that need to perform bioinformatics analysis in a flexible and effective way. This seems particularly true for hybrid clouds that couple the scalability offered by general-purpose public clouds with the greater control and ad hoc customizations supplied by the private ones. A hybrid cloud broker, acting as an intermediary between users and public providers, can support customers in the selection of the most suitable offers, optionally adding the provisioning of dedicated services with higher levels of quality. This paper analyses some economic and practical aspects of exploiting cloud computing in a real research scenario for the in silico drug discovery in terms of requirements, costs, and computational load based on the number of expected users. In particular, our work is aimed at supporting both the researchers and the cloud broker delivering an IaaS cloud infrastructure for biotechnology laboratories exposing different levels of nonfunctional requirements. PMID:24106693

Cloud Infrastructures for In Silico Drug Discovery: Economic and Practical Aspects

Directory of Open Access Journals (Sweden)

Daniele D'Agostino

2013-01-01

Full Text Available Cloud computing opens new perspectives for small-medium biotechnology laboratories that need to perform bioinformatics analysis in a flexible and effective way. This seems particularly true for hybrid clouds that couple the scalability offered by general-purpose public clouds with the greater control and ad hoc customizations supplied by the private ones. A hybrid cloud broker, acting as an intermediary between users and public providers, can support customers in the selection of the most suitable offers, optionally adding the provisioning of dedicated services with higher levels of quality. This paper analyses some economic and practical aspects of exploiting cloud computing in a real research scenario for the in silico drug discovery in terms of requirements, costs, and computational load based on the number of expected users. In particular, our work is aimed at supporting both the researchers and the cloud broker delivering an IaaS cloud infrastructure for biotechnology laboratories exposing different levels of nonfunctional requirements.

First correlated measurements of the shape and light scattering properties of cloud particles using the new Particle Habit Imaging and Polar Scattering (PHIPS probe

Directory of Open Access Journals (Sweden)

A. Abdelmonem

2011-10-01

Full Text Available Studying the radiative impact of cirrus clouds requires knowledge of the relationship between their microphysics and the single scattering properties of cloud particles. Usually, this relationship is obtained by modeling the optical scattering properties from in situ measurements of ice crystal size distributions. The measured size distribution and the assumed particle shape might be erroneous in case of non-spherical ice particles. We present here a novel optical sensor (the Particle Habit Imaging and Polar Scattering probe, PHIPS designed to measure simultaneously the 3-D morphology and the corresponding optical and microphysical parameters of individual cloud particles. Clouds containing particles ranging from a few micrometers to about 800 μm diameter in size can be characterized systematically with an optical resolution power of 2 μm and polar scattering resolution of 1° for forward scattering directions (from 1° to 10° and 8° for side and backscattering directions (from 18° to 170°. The maximum acquisition rates for scattering phase functions and images are 262 KHz and 10 Hz, respectively. Some preliminary results collected in two ice cloud campaigns conducted in the AIDA cloud simulation chamber are presented. PHIPS showed reliability in operation and produced size distributions and images comparable to those given by other certified cloud particles instruments. A 3-D model of a hexagonal ice plate is constructed and the corresponding scattering phase function is compared to that modeled using the Ray Tracing with Diffraction on Facets (RTDF program. PHIPS is a highly promising novel airborne optical sensor for studying the radiative impact of cirrus clouds and correlating the particle habit-scattering properties which will serve as a reference for other single, or multi-independent, measurement instruments.

First correlated measurements of the shape and light scattering properties of cloud particles using the new Particle Habit Imaging and Polar Scattering (PHIPS) probe

Science.gov (United States)

Abdelmonem, A.; Schnaiter, M.; Amsler, P.; Hesse, E.; Meyer, J.; Leisner, T.

2011-10-01

Studying the radiative impact of cirrus clouds requires knowledge of the relationship between their microphysics and the single scattering properties of cloud particles. Usually, this relationship is obtained by modeling the optical scattering properties from in situ measurements of ice crystal size distributions. The measured size distribution and the assumed particle shape might be erroneous in case of non-spherical ice particles. We present here a novel optical sensor (the Particle Habit Imaging and Polar Scattering probe, PHIPS) designed to measure simultaneously the 3-D morphology and the corresponding optical and microphysical parameters of individual cloud particles. Clouds containing particles ranging from a few micrometers to about 800 μm diameter in size can be characterized systematically with an optical resolution power of 2 μm and polar scattering resolution of 1° for forward scattering directions (from 1° to 10°) and 8° for side and backscattering directions (from 18° to 170°). The maximum acquisition rates for scattering phase functions and images are 262 KHz and 10 Hz, respectively. Some preliminary results collected in two ice cloud campaigns conducted in the AIDA cloud simulation chamber are presented. PHIPS showed reliability in operation and produced size distributions and images comparable to those given by other certified cloud particles instruments. A 3-D model of a hexagonal ice plate is constructed and the corresponding scattering phase function is compared to that modeled using the Ray Tracing with Diffraction on Facets (RTDF) program. PHIPS is a highly promising novel airborne optical sensor for studying the radiative impact of cirrus clouds and correlating the particle habit-scattering properties which will serve as a reference for other single, or multi-independent, measurement instruments.

INFRARED DARK CLOUDS IN THE SMALL MAGELLANIC CLOUD?

International Nuclear Information System (INIS)

Lee, Min-Young; Stanimirovic, Snezana; Devine, Kathryn E.; Ott, Juergen; Van Loon, Jacco Th.; Oliveira, Joana M.; Bolatto, Alberto D.; Jones, Paul A.; Cunningham, Maria R.

2009-01-01

We have applied the unsharp-masking technique to the 24 μm image of the Small Magellanic Cloud (SMC), obtained with the Spitzer Space Telescope, to search for high-extinction regions. This technique has been used to locate very dense and cold interstellar clouds in the Galaxy, particularly infrared dark clouds (IRDCs). Fifty-five candidate regions of high extinction, namely, high-contrast regions (HCRs), have been identified from the generated decremental contrast image of the SMC. Most HCRs are located in the southern bar region and mainly distributed in the outskirts of CO clouds, but most likely contain a significant amount of H 2 . HCRs have a peak contrast at 24 μm of 2%-2.5% and a size of 8-14 pc. This corresponds to the size of typical and large Galactic IRDCs, but Galactic IRDCs are 2-3 times darker at 24 μm than our HCRs. To constrain the physical properties of the HCRs, we have performed NH 3 , N 2 H + , HNC, HCO + , and HCN observations toward one of the HCRs, HCR LIRS36-east, using the Australia Telescope Compact Array and the Mopra single-dish radio telescope. We did not detect any molecular line emission, however, our upper limits to the column densities of molecular species suggest that HCRs are most likely moderately dense with n ∼ 10 3 cm -3 . This volume density is in agreement with predictions for the cool atomic phase in low-metallicity environments. We suggest that HCRs may be tracing clouds at the transition from atomic to molecule-dominated medium, and could be a powerful way to study early stages of gas condensation in low-metallicity galaxies. Alternatively, if made up of dense molecular clumps <0.5 pc in size, HCRs could be counterparts of Galactic IRDCs, and/or regions with highly unusual abundance of very small dust grains.

Measurement of optical blurring in a turbulent cloud chamber

Science.gov (United States)

Packard, Corey D.; Ciochetto, David S.; Cantrell, Will H.; Roggemann, Michael C.; Shaw, Raymond A.

2016-10-01

Earth's atmosphere can significantly impact the propagation of electromagnetic radiation, degrading the performance of imaging systems. Deleterious effects of the atmosphere include turbulence, absorption and scattering by particulates. Turbulence leads to blurring, while absorption attenuates the energy that reaches imaging sensors. The optical properties of aerosols and clouds also impact radiation propagation via scattering, resulting in decorrelation from unscattered light. Models have been proposed for calculating a point spread function (PSF) for aerosol scattering, providing a method for simulating the contrast and spatial detail expected when imaging through atmospheres with significant aerosol optical depth. However, these synthetic images and their predicating theory would benefit from comparison with measurements in a controlled environment. Recently, Michigan Technological University (MTU) has designed a novel laboratory cloud chamber. This multiphase, turbulent "Pi Chamber" is capable of pressures down to 100 hPa and temperatures from -55 to +55°C. Additionally, humidity and aerosol concentrations are controllable. These boundary conditions can be combined to form and sustain clouds in an instrumented laboratory setting for measuring the impact of clouds on radiation propagation. This paper describes an experiment to generate mixing and expansion clouds in supersaturated conditions with salt aerosols, and an example of measured imagery viewed through the generated cloud is shown. Aerosol and cloud droplet distributions measured during the experiment are used to predict scattering PSF and MTF curves, and a methodology for validating existing theory is detailed. Measured atmospheric inputs will be used to simulate aerosol-induced image degradation for comparison with measured imagery taken through actual cloud conditions. The aerosol MTF will be experimentally calculated and compared to theoretical expressions. The key result of this study is the

Cloud computing as a new technology trend in education

OpenAIRE

Шамина, Ольга Борисовна; Буланова, Татьяна Валентиновна

2014-01-01

The construction and operation of extremely large-scale, commodity-computer datacenters was the key necessary enabler of Cloud Computing. Cloud Computing could offer services make a good profit for using in education. With Cloud Computing it is possible to increase the quality of education, improve communicative culture and give to teachers and students new application opportunities.

The Global and Local Characters of Mars Perihelion Cloud Trails

Science.gov (United States)

Clancy, R. T.; Wolff, M. J.; Smith, M. D.; Cantor, B. A.; Spiga, A.

2014-12-01

We present the seasonal and spatial distribution of Mars perihelion cloud trails as mapped from Mars Reconnaissance Orbiter (MRO) MARCI (Mars Color Imager) imaging observations in 2 ultraviolet and 3 visible filters. The extended 2007-2013 period of MARCI daily global image maps reveals the widespread distribution of these high altitude clouds, which are somewhat paradoxically associated with specific surface regions. They appear as longitudinally extended (300-700 km) cloud trails with distinct leading plumes of substantial ice cloud optical depths (0.02-0.2) for such high altitudes of occurrence (40-50 km, from cloud surface shadow measurements). These plumes generate small ice particles (Reff~1 to reflect locally elevated mesospheric water ice formation that may impact the global expression of mesospheric water ice aerosols.

Multilayered Clouds Identification and Retrieval for CERES Using MODIS

Science.gov (United States)

Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Yi, Yuhong; Huang, Jainping; Lin, Bin; Fan, Alice; Gibson, Sharon; Chang, Fu-Lung

2006-01-01

Traditionally, analyses of satellite data have been limited to interpreting the radiances in terms of single layer clouds. Generally, this results in significant errors in the retrieved properties for multilayered cloud systems. Two techniques for detecting overlapped clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. The first technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other method uses microwave (MWR) data. The use of BTD, the 11-12 micrometer brightness temperature difference, in conjunction with tau, the retrieved visible optical depth, was suggested by Kawamoto et al. (2001) and used by Pavlonis et al. (2004) as a means to detect multilayered clouds. Combining visible (VIS; 0.65 micrometer) and infrared (IR) retrievals of cloud properties with microwave (MW) retrievals of cloud water temperature Tw and liquid water path LWP retrieved from satellite microwave imagers appears to be a fruitful approach for detecting and retrieving overlapped clouds (Lin et al., 1998, Ho et al., 2003, Huang et al., 2005). The BTD method is limited to optically thin cirrus over low clouds, while the MWR method is limited to ocean areas only. With the availability of VIS and IR data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and MW data from the Advanced Microwave Scanning Radiometer EOS (AMSR-E), both on Aqua, it is now possible to examine both approaches simultaneously. This paper explores the use of the BTD method as applied to MODIS and AMSR-E data taken from the Aqua satellite over non-polar ocean surfaces.

Privacy and legal issues in cloud computing

CERN Document Server

Weber, Rolf H

2015-01-01

Adopting a multi-disciplinary and comparative approach, this book focuses on emerging and innovative attempts to tackle privacy and legal issues in cloud computing, such as personal data privacy, security and intellectual property protection. Leading international academics and practitioners in the fields of law and computer science examine the specific legal implications of cloud computing pertaining to jurisdiction, biomedical practice and information ownership. This collection offers original and critical responses to the rising challenges posed by cloud computing.

Mapping low- and high-density clouds in astrophysical nebulae by imaging forbidden line emission

Science.gov (United States)

Steiner, J. E.; Menezes, R. B.; Ricci, T. V.; Oliveira, A. S.

2009-06-01

Emission line ratios have been essential for determining physical parameters such as gas temperature and density in astrophysical gaseous nebulae. With the advent of panoramic spectroscopic devices, images of regions with emission lines related to these physical parameters can, in principle, also be produced. We show that, with observations from modern instruments, it is possible to transform images taken from density-sensitive forbidden lines into images of emission from high- and low-density clouds by applying a transformation matrix. In order to achieve this, images of the pairs of density-sensitive lines as well as the adjacent continuum have to be observed and combined. We have computed the critical densities for a series of pairs of lines in the infrared, optical, ultraviolet and X-rays bands, and calculated the pair line intensity ratios in the high- and low-density limit using a four- and five-level atom approximation. In order to illustrate the method, we applied it to Gemini Multi-Object Spectrograph (GMOS) Integral Field Unit (GMOS-IFU) data of two galactic nuclei. We conclude that this method provides new information of astrophysical interest, especially for mapping low- and high-density clouds; for this reason, we call it `the ld/hd imaging method'. Based on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the National Science Foundation on behalf of the Gemini partnership: the National Science Foundation (United States); the Science and Technology Facilities Council (United Kingdom); the National Research Council (Canada), CONICYT (Chile); the Australian Research Council (Australia); Ministério da Ciência e Tecnologia (Brazil) and Secretaria de Ciencia y Tecnologia (Argentina). E-mail: steiner@astro.iag.usp.br

Cloud Spirals and Outflow in Tropical Storm Katrina

Science.gov (United States)

2005-01-01

On Tuesday, August 30, 2005, NASA's Multi-angle Imaging SpectroRadiometer retrieved cloud-top heights and cloud-tracked wind velocities for Tropical Storm Katrina, as the center of the storm was situated over the Tennessee valley. At this time Katrina was weakening and no longer classified as a hurricane, and would soon become an extratropical depression. Measurements such as these can help atmospheric scientists compare results of computer-generated hurricane simulations with observed conditions, ultimately allowing them to better represent and understand physical processes occurring in hurricanes. Because air currents are influenced by the Coriolis force (caused by the rotation of the Earth), Northern Hemisphere hurricanes are characterized by an inward counterclockwise (cyclonic) rotation towards the center. It is less widely known that, at high altitudes, outward-spreading bands of cloud rotate in a clockwise (anticyclonic) direction. The image on the left shows the retrieved cloud-tracked winds as red arrows superimposed across the natural color view from MISR's nadir (vertical-viewing) camera. Both the counter-clockwise motion for the lower-level storm clouds and the clockwise motion for the upper clouds are apparent in these images. The speeds for the clockwise upper level winds have typical values between 40 and 45 m/s (144-162 km/hr). The low level counterclockwise winds have typical values between 7 and 24 m/s (25-86 km/hr), weakening with distance from the storm center. The image on the right displays the cloud-top height retrievals. Areas where cloud heights could not be retrieved are shown in dark gray. Both the wind velocity vectors and the cloud-top height field were produced by automated computer recognition of displacements in spatial features within successive MISR images acquired at different view angles and at slightly different times. The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously, viewing the entire globe

Imaging and mapping the impact of clouds on skyglow with all-sky photometry.

Science.gov (United States)

Jechow, Andreas; Kolláth, Zoltán; Ribas, Salvador J; Spoelstra, Henk; Hölker, Franz; Kyba, Christopher C M

2017-07-27

Artificial skyglow is constantly growing on a global scale, with potential ecological consequences ranging up to affecting biodiversity. To understand these consequences, worldwide mapping of skyglow for all weather conditions is urgently required. In particular, the amplification of skyglow by clouds needs to be studied, as clouds can extend the reach of skyglow into remote areas not affected by light pollution on clear nights. Here we use commercial digital single lens reflex cameras with fisheye lenses for all-sky photometry. We track the reach of skyglow from a peri-urban into a remote area on a clear and a partly cloudy night by performing transects from the Spanish town of Balaguer towards Montsec Astronomical Park. From one single all-sky image, we extract zenith luminance, horizontal and scalar illuminance. While zenith luminance reaches near-natural levels at 5 km distance from the town on the clear night, similar levels are only reached at 27 km on the partly cloudy night. Our results show the dramatic increase of the reach of skyglow even for moderate cloud coverage at this site. The powerful and easy-to-use method promises to be widely applicable for studies of ecological light pollution on a global scale also by non-specialists in photometry.

Building Tag Clouds in Perl and PHP

CERN Document Server

Bumgardner, Jim

2006-01-01

Tag clouds are everywhere on the web these days. First popularized by the web sites Flickr, Technorati, and del.icio.us, these amorphous clumps of words now appear on a slew of web sites as visual evidence of their membership in the elite corps of "Web 2.0." This PDF analyzes what is and isn't a tag cloud, offers design tips for using them effectively, and then goes on to show how to collect tags and display them in the tag cloud format. Scripts are provided in Perl and PHP. Yes, some have said tag clouds are a fad. But as you will see, tag clouds, when used properly, have real merits. More

Strategies for cloud-top phase determination: differentiation between thin cirrus clouds and snow in manual (ground truth) analyses

Science.gov (United States)

Hutchison, Keith D.; Etherton, Brian J.; Topping, Phillip C.

1996-12-01

Quantitative assessments on the performance of automated cloud analysis algorithms require the creation of highly accurate, manual cloud, no cloud (CNC) images from multispectral meteorological satellite data. In general, the methodology to create ground truth analyses for the evaluation of cloud detection algorithms is relatively straightforward. However, when focus shifts toward quantifying the performance of automated cloud classification algorithms, the task of creating ground truth images becomes much more complicated since these CNC analyses must differentiate between water and ice cloud tops while ensuring that inaccuracies in automated cloud detection are not propagated into the results of the cloud classification algorithm. The process of creating these ground truth CNC analyses may become particularly difficult when little or no spectral signature is evident between a cloud and its background, as appears to be the case when thin cirrus is present over snow-covered surfaces. In this paper, procedures are described that enhance the researcher's ability to manually interpret and differentiate between thin cirrus clouds and snow-covered surfaces in daytime AVHRR imagery. The methodology uses data in up to six AVHRR spectral bands, including an additional band derived from the daytime 3.7 micron channel, which has proven invaluable for the manual discrimination between thin cirrus clouds and snow. It is concluded that while the 1.6 micron channel remains essential to differentiate between thin ice clouds and snow. However, this capability that may be lost if the 3.7 micron data switches to a nighttime-only transmission with the launch of future NOAA satellites.

Limb clouds and dust on Mars from images obtained by the Visual Monitoring Camera (VMC) onboard Mars Express

Science.gov (United States)

Sánchez-Lavega, A.; Chen-Chen, H.; Ordoñez-Etxeberria, I.; Hueso, R.; del Río-Gaztelurrutia, T.; Garro, A.; Cardesín-Moinelo, A.; Titov, D.; Wood, S.

2018-01-01

The Visual Monitoring Camera (VMC) onboard the Mars Express (MEx) spacecraft is a simple camera aimed to monitor the release of the Beagle-2 lander on Mars Express and later used for public outreach. Here, we employ VMC as a scientific instrument to study and characterize high altitude aerosols events (dust and condensates) observed at the Martian limb. More than 21,000 images taken between 2007 and 2016 have been examined to detect and characterize elevated layers of dust in the limb, dust storms and clouds. We report a total of 18 events for which we give their main properties (areographic location, maximum altitude, limb projected size, Martian solar longitude and local time of occurrence). The top altitudes of these phenomena ranged from 40 to 85 km and their horizontal extent at the limb ranged from 120 to 2000 km. They mostly occurred at Equatorial and Tropical latitudes (between ∼30°N and 30°S) at morning and afternoon local times in the southern fall and northern winter seasons. None of them are related to the orographic clouds that typically form around volcanoes. Three of these events have been studied in detail using simultaneous images taken by the MARCI instrument onboard Mars Reconnaissance Orbiter (MRO) and studying the properties of the atmosphere using the predictions from the Mars Climate Database (MCD) General Circulation Model. This has allowed us to determine the three-dimensional structure and nature of these events, with one of them being a regional dust storm and the two others water ice clouds. Analyses based on MCD and/or MARCI images for the other cases studied indicate that the rest of the events correspond most probably to water ice clouds.

CONTOURS BASED APPROACH FOR THERMAL IMAGE AND TERRESTRIAL POINT CLOUD REGISTRATION

Directory of Open Access Journals (Sweden)

A. Bennis

2013-07-01

Full Text Available Building energetic performances strongly depend on the thermal insulation. However the performance of the insulation materials tends to decrease over time which necessitates the continuous monitoring of the building in order to detect and repair the anomalous zones. In this paper, it is proposed to couple 2D infrared images representing the surface temperature of the building with 3D point clouds acquired with Terrestrial Laser Scanner (TLS resulting in a semi-automatic approach allowing the texturation of TLS data with infrared image of buildings. A contour-based algorithm is proposed whose main features are : 1 the extraction of high level primitive is not required 2 the use of projective transform allows to handle perspective effects 3 a point matching refinement procedure allows to cope with approximate control point selection. The procedure is applied to test modules aiming at investigating the thermal properties of material.

Active probing of cloud multiple scattering, optical depth, vertical thickness, and liquid water content using wide-angle imaging lidar

Science.gov (United States)

Love, Steven P.; Davis, Anthony B.; Rohde, Charles A.; Tellier, Larry; Ho, Cheng

2002-09-01

At most optical wavelengths, laser light in a cloud lidar experiment is not absorbed but merely scattered out of the beam, eventually escaping the cloud via multiple scattering. There is much information available in this light scattered far from the input beam, information ignored by traditional 'on-beam' lidar. Monitoring these off-beam returns in a fully space- and time-resolved manner is the essence of our unique instrument, Wide Angle Imaging Lidar (WAIL). In effect, WAIL produces wide-field (60-degree full-angle) 'movies' of the scattering process and records the cloud's radiative Green functions. A direct data product of WAIL is the distribution of photon path lengths resulting from multiple scattering in the cloud. Following insights from diffusion theory, we can use the measured Green functions to infer the physical thickness and optical depth of the cloud layer, and, from there, estimate the volume-averaged liquid water content. WAIL is notable in that it is applicable to optically thick clouds, a regime in which traditional lidar is reduced to ceilometry. Here we present recent WAIL data on various clouds and discuss the extension of WAIL to full diurnal monitoring by means of an ultra-narrow magneto-optic atomic line filter for daytime measurements.

Active probing of cloud multiple scattering, optical depth, vertical thickness, and liquid water content using wide-angle imaging LIDAR

International Nuclear Information System (INIS)

Love, Steven P.; Davis, Anthony B.; Rohde, Charles A.; Tellier, Larry L.; Ho, Cheng

2002-01-01

At most optical wavelengths, laser light in a cloud lidar experiment is not absorbed but merely scattered out of the beam, eventually escaping the cloud via multiple scattering. There is much information available in this light scattered far from the input beam, information ignored by traditional 'on-beam' lidar. Monitoring these off-beam returns in a fully space- and time-resolved manner is the essence of our unique instrument, Wide Angle Imaging Lidar (WAIL). In effect, WAIL produces wide-field (60-degree full-angle) 'movies' of the scattering process and records the cloud's radiative Green functions. A direct data product of WAIL is the distribution of photon path lengths resulting from multiple scattering in the cloud. Following insights from diffusion theory, we can use the measured Green functions to infer the physical thickness and optical depth of the cloud layer, and, from there, estimate the volume-averaged liquid water content. WAIL is notable in that it is applicable to optically thick clouds, a regime in which traditional lidar is reduced to ceilometry. Here we present recent WAIL data oti various clouds and discuss the extension of WAIL to full diurnal monitoring by means of an ultra-narrow magneto-optic atomic line filter for daytime measurements.

A Review on Broker Based Cloud Service Model

Directory of Open Access Journals (Sweden)

Nagarajan Rajganesh

2016-09-01

Full Text Available Cloud computing emerged as a utility oriented computing that facilitates resource sharing under pay-as-you-go model. Nowadays, cloud offerings are not limited to range of services and anything can be shared as a service through the Internet. In this work, a detailed literature survey with respect to cloud service discovery and composition has been accounted. A proposed architecture with the inclusion of cloud broker is presented in our work. It focuses the importance of suitable service selection and its ranking towards fulfilling the customer’s service requirements. The proposed cloud broker advocates techniques such as reasoning and decision making capabilities for the improved cloud service selection and composition.

Automatic registration of iPhone images to laser point clouds of urban structures using shape features

NARCIS (Netherlands)

Sirmacek, B.; Lindenbergh, R.C.; Menenti, M.

2013-01-01

Fusion of 3D airborne laser (LIDAR) data and terrestrial optical imagery can be applied in 3D urban modeling and model up-dating. The most challenging aspect of the fusion procedure is registering the terrestrial optical images on the LIDAR point clouds. In this article, we propose an approach for

ATLAS Computing on the Swiss Cloud SWITCHengines

CERN Document Server

AUTHOR|(INSPIRE)INSPIRE-00215485; The ATLAS collaboration; Sciacca, Gianfranco

2016-01-01

Consolidation towards more computing at flat budgets beyond what pure chip technology can offer, is a requirement for the full scientific exploitation of the future data from the Large Hadron Collider. One consolidation measure is to exploit cloud infrastructures whenever they are financially competitive. We report on the technical solutions and the performance used and achieved running ATLAS production on SWITCHengines. SWITCHengines is the new cloud infrastructure offered to Swiss academia by the National Research and Education Network SWITCH. While solutions and performances are general, financial considerations and policies, which we also report on, are country specific.

Global Software Development with Cloud Platforms

Science.gov (United States)

Yara, Pavan; Ramachandran, Ramaseshan; Balasubramanian, Gayathri; Muthuswamy, Karthik; Chandrasekar, Divya

Offshore and outsourced distributed software development models and processes are facing challenges, previously unknown, with respect to computing capacity, bandwidth, storage, security, complexity, reliability, and business uncertainty. Clouds promise to address these challenges by adopting recent advances in virtualization, parallel and distributed systems, utility computing, and software services. In this paper, we envision a cloud-based platform that addresses some of these core problems. We outline a generic cloud architecture, its design and our first implementation results for three cloud forms - a compute cloud, a storage cloud and a cloud-based software service- in the context of global distributed software development (GSD). Our ”compute cloud” provides computational services such as continuous code integration and a compile server farm, ”storage cloud” offers storage (block or file-based) services with an on-line virtual storage service, whereas the on-line virtual labs represent a useful cloud service. We note some of the use cases for clouds in GSD, the lessons learned with our prototypes and identify challenges that must be conquered before realizing the full business benefits. We believe that in the future, software practitioners will focus more on these cloud computing platforms and see clouds as a means to supporting a ecosystem of clients, developers and other key stakeholders.

Performance and Cost Analysis of the Supernova Factory on the Amazon AWS Cloud

Directory of Open Access Journals (Sweden)

Keith R. Jackson

2011-01-01

Full Text Available Today, our picture of the Universe radically differs from that of just over a decade ago. We now know that the Universe is not only expanding as Hubble discovered in 1929, but that the rate of expansion is accelerating, propelled by mysterious new physics dubbed “Dark Energy”. This revolutionary discovery was made by comparing the brightness of nearby Type Ia supernovae (which exploded in the past billion years to that of much more distant ones (from up to seven billion years ago. The reliability of this comparison hinges upon a very detailed understanding of the physics of the nearby events. To further this understanding, the Nearby Supernova Factory (SNfactory relies upon a complex pipeline of serial processes that execute various image processing algorithms in parallel on ~10 TBs of data. This pipeline traditionally runs on a local cluster. Cloud computing [Above the clouds: a Berkeley view of cloud computing, Technical Report UCB/EECS-2009-28, University of California, 2009] offers many features that make it an attractive alternative. The ability to completely control the software environment in a cloud is appealing when dealing with a community developed science pipeline with many unique library and platform requirements. In this context we study the feasibility of porting the SNfactory pipeline to the Amazon Web Services environment. Specifically we: describe the tool set we developed to manage a virtual cluster on Amazon EC2, explore the various design options available for application data placement, and offer detailed performance results and lessons learned from each of the above design options.

A cloud-based multimodality case file for mobile devices.

Science.gov (United States)

Balkman, Jason D; Loehfelm, Thomas W

2014-01-01

Recent improvements in Web and mobile technology, along with the widespread use of handheld devices in radiology education, provide unique opportunities for creating scalable, universally accessible, portable image-rich radiology case files. A cloud database and a Web-based application for radiologic images were developed to create a mobile case file with reasonable usability, download performance, and image quality for teaching purposes. A total of 75 radiology cases related to breast, thoracic, gastrointestinal, musculoskeletal, and neuroimaging subspecialties were included in the database. Breast imaging cases are the focus of this article, as they best demonstrate handheld display capabilities across a wide variety of modalities. This case subset also illustrates methods for adapting radiologic content to cloud platforms and mobile devices. Readers will gain practical knowledge about storage and retrieval of cloud-based imaging data, an awareness of techniques used to adapt scrollable and high-resolution imaging content for the Web, and an appreciation for optimizing images for handheld devices. The evaluation of this software demonstrates the feasibility of adapting images from most imaging modalities to mobile devices, even in cases of full-field digital mammograms, where high resolution is required to represent subtle pathologic features. The cloud platform allows cases to be added and modified in real time by using only a standard Web browser with no application-specific software. Challenges remain in developing efficient ways to generate, modify, and upload radiologic and supplementary teaching content to this cloud-based platform. Online supplemental material is available for this article. ©RSNA, 2014.

Secure Authentication of Cloud Data Mining API

OpenAIRE

Bhadauria, Rohit; Borgohain, Rajdeep; Biswas, Abirlal; Sanyal, Sugata

2013-01-01

Cloud computing is a revolutionary concept that has brought a paradigm shift in the IT world. This has made it possible to manage and run businesses without even setting up an IT infrastructure. It offers multi-fold benefits to the users moving to a cloud, while posing unknown security and privacy issues. User authentication is one such growing concern and is greatly needed in order to ensure privacy and security in a cloud computing environment. This paper discusses the security at different...

A Survey On Biometric Security Technologies From Cloud Computing Perspective

Directory of Open Access Journals (Sweden)

Shivashish Ratnam

2015-08-01

Full Text Available Cloud computing is one of the rising technologies that takes set of connections users to the next level. Cloud is a technology where resources are paid as per usage rather than owned. One of the major challenges in this technology is Security. Biometric systems provide the answer to ensure that the rendered services are accessed only by a legal user or an authorized user and no one else. Biometric systems recognize users based on behavioral or physiological characteristics. The advantages of such systems over traditional validation methods such as passwords and IDs are well known and hence biometric systems are progressively gaining ground in terms of usage. This paper brings about a new replica of a security system where in users have to offer multiple biometric finger prints during Enrollment for a service. These templates are stored at the cloud providers section. The users are authenticated based on these finger print designed templates which have to be provided in the order of arbitrary numbers or imaginary numbers that are generated every time continuously. Both finger prints templates and images are present and they provided every time duration are encrypted or modified for enhanced security.

Moving image analysis to the cloud: A case study with a genome-scale tomographic study

Energy Technology Data Exchange (ETDEWEB)

Mader, Kevin [4Quant Ltd., Switzerland & Institute for Biomedical Engineering at University and ETH Zurich (Switzerland); Stampanoni, Marco [Institute for Biomedical Engineering at University and ETH Zurich, Switzerland & Swiss Light Source at Paul Scherrer Institut, Villigen (Switzerland)

2016-01-28

Over the last decade, the time required to measure a terabyte of microscopic imaging data has gone from years to minutes. This shift has moved many of the challenges away from experimental design and measurement to scalable storage, organization, and analysis. As many scientists and scientific institutions lack training and competencies in these areas, major bottlenecks have arisen and led to substantial delays and gaps between measurement, understanding, and dissemination. We present in this paper a framework for analyzing large 3D datasets using cloud-based computational and storage resources. We demonstrate its applicability by showing the setup and costs associated with the analysis of a genome-scale study of bone microstructure. We then evaluate the relative advantages and disadvantages associated with local versus cloud infrastructures.

Moving image analysis to the cloud: A case study with a genome-scale tomographic study

International Nuclear Information System (INIS)

Mader, Kevin; Stampanoni, Marco

2016-01-01

Over the last decade, the time required to measure a terabyte of microscopic imaging data has gone from years to minutes. This shift has moved many of the challenges away from experimental design and measurement to scalable storage, organization, and analysis. As many scientists and scientific institutions lack training and competencies in these areas, major bottlenecks have arisen and led to substantial delays and gaps between measurement, understanding, and dissemination. We present in this paper a framework for analyzing large 3D datasets using cloud-based computational and storage resources. We demonstrate its applicability by showing the setup and costs associated with the analysis of a genome-scale study of bone microstructure. We then evaluate the relative advantages and disadvantages associated with local versus cloud infrastructures

Benchmarking personal cloud storage

NARCIS (Netherlands)

Drago, Idilio; Bocchi, Enrico; Mellia, Marco; Slatman, Herman; Pras, Aiko

2013-01-01

Personal cloud storage services are data-intensive applications already producing a significant share of Internet traffic. Several solutions offered by different companies attract more and more people. However, little is known about each service capabilities, architecture and - most of all -

Neural network cloud top pressure and height for MODIS

Science.gov (United States)

Håkansson, Nina; Adok, Claudia; Thoss, Anke; Scheirer, Ronald; Hörnquist, Sara

2018-06-01

Cloud top height retrieval from imager instruments is important for nowcasting and for satellite climate data records. A neural network approach for cloud top height retrieval from the imager instrument MODIS (Moderate Resolution Imaging Spectroradiometer) is presented. The neural networks are trained using cloud top layer pressure data from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) dataset. Results are compared with two operational reference algorithms for cloud top height: the MODIS Collection 6 Level 2 height product and the cloud top temperature and height algorithm in the 2014 version of the NWC SAF (EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Satellite Application Facility on Support to Nowcasting and Very Short Range Forecasting) PPS (Polar Platform System). All three techniques are evaluated using both CALIOP and CPR (Cloud Profiling Radar for CloudSat (CLOUD SATellite)) height. Instruments like AVHRR (Advanced Very High Resolution Radiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) contain fewer channels useful for cloud top height retrievals than MODIS, therefore several different neural networks are investigated to test how infrared channel selection influences retrieval performance. Also a network with only channels available for the AVHRR1 instrument is trained and evaluated. To examine the contribution of different variables, networks with fewer variables are trained. It is shown that variables containing imager information for neighboring pixels are very important. The error distributions of the involved cloud top height algorithms are found to be non-Gaussian. Different descriptive statistic measures are presented and it is exemplified that bias and SD (standard deviation) can be misleading for non-Gaussian distributions. The median and mode are found to better describe the tendency of the error distributions and IQR (interquartile range) and MAE (mean absolute error) are found

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Effective Particle Size (CEPS) Environmental Data Record (EDR) from IDPS

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of Cloud Effective Particle Size (CEPS) from the Visible Infrared Imaging Radiometer...

Temporal co-registration for TROPOMI cloud clearing

Directory of Open Access Journals (Sweden)

I. Genkova

2012-03-01

Full Text Available The TROPOspheric Monitoring Instrument (TROPOMI is anticipated to provide high-quality and timely global atmospheric composition information through observations of atmospheric constituents such as ozone, nitrogen dioxide, sulfur dioxide, carbon monoxide, methane, formaldehyde and aerosol properties. The methane and the aerosol retrievals require very precise cloud clearing, which is difficult to achieve at the TROPOMI spatial resolution (7 by 7 km and without thermal IR measurements. The TROPOMI carrier – the Sentinel 5 Precursor (S5P, does not include a cloud imager, thus it is planned to fly the S5P mission in a constellation with an instrument yielding an accurate cloud mask. The cloud imagery data will be provided by the US NPOESS Preparatory Project (NPP mission, which will have the Visible Infrared Imager Radiometer Suite (VIIRS on board (Scalione, 2004. This paper investigates the temporal co-registration requirements for suitable time differences between the VIIRS measurements of clouds and the TROPOMI methane and aerosol measurements, so that the former could be used for cloud clearing. The temporal co-registration is studied using Meteosat Second Generation (MSG Spinning Enhanced Visible and Infrared Imager (SEVIRI data with 15 min temporal resolution (Veefkind, 2008b, and with data from the Geostationary Operational Environmental Satellite – 10 (GOES-10 having 1 min temporal resolution. The aim is to understand and assess the relation between the amount of allowed cloud contamination and the required time difference between the two satellites' overflights. Quantitative analysis shows that a time difference of approximately 5 min is sufficient (in most conditions to use the cloud information from the first instrument for cloud clearing in the retrievals using data from the second instrument. In recent years the A-train constellation demonstrated the benefit of flying satellites in formation. Therefore this study's findings will be

Detection and retrieval of multi-layered cloud properties using satellite data

Science.gov (United States)

Minnis, Patrick; Sun-Mack, Sunny; Chen, Yan; Yi, Helen; Huang, Jianping; Nguyen, Louis; Khaiyer, Mandana M.

2005-10-01

Four techniques for detecting multilayered clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. A new technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other methods examined here use atmospheric sounding data (CO2-slicing, CO2), BTD, or microwave data. The CO2 and BTD methods are limited to optically thin cirrus over low clouds, while the MWR methods are limited to ocean areas only. This paper explores the use of the BTD and CO2 methods as applied to Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer EOS (AMSR-E) data taken from the Aqua satellite over ocean surfaces. Cloud properties derived from MODIS data for the Clouds and the Earth's Radiant Energy System (CERES) Project are used to classify cloud phase and optical properties. The preliminary results focus on a MODIS image taken off the Uruguayan coast. The combined MW visible infrared (MVI) method is assumed to be the reference for detecting multilayered ice-over-water clouds. The BTD and CO2 techniques accurately match the MVI classifications in only 51 and 41% of the cases, respectively. Much additional study is need to determine the uncertainties in the MVI method and to analyze many more overlapped cloud scenes.

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Height (Top and Base) Environmental Data Record (EDR) from NDE

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of cloud height (top and base) from the Visible Infrared Imaging Radiometer Suite...

The Ethics of Cloud Computing.

Science.gov (United States)

de Bruin, Boudewijn; Floridi, Luciano

2017-02-01

Cloud computing is rapidly gaining traction in business. It offers businesses online services on demand (such as Gmail, iCloud and Salesforce) and allows them to cut costs on hardware and IT support. This is the first paper in business ethics dealing with this new technology. It analyzes the informational duties of hosting companies that own and operate cloud computing datacentres (e.g., Amazon). It considers the cloud services providers leasing 'space in the cloud' from hosting companies (e.g., Dropbox, Salesforce). And it examines the business and private 'clouders' using these services. The first part of the paper argues that hosting companies, services providers and clouders have mutual informational (epistemic) obligations to provide and seek information about relevant issues such as consumer privacy, reliability of services, data mining and data ownership. The concept of interlucency is developed as an epistemic virtue governing ethically effective communication. The second part considers potential forms of government restrictions on or proscriptions against the development and use of cloud computing technology. Referring to the concept of technology neutrality, it argues that interference with hosting companies and cloud services providers is hardly ever necessary or justified. It is argued, too, however, that businesses using cloud services (e.g., banks, law firms, hospitals etc. storing client data in the cloud) will have to follow rather more stringent regulations.

Colors of Alien Worlds from Direct Imaging Exoplanet Missions

Science.gov (United States)

Hu, Renyu

2016-01-01

Future direct-imaging exoplanet missions such as WFIRST will measure the reflectivity of exoplanets at visible wavelengths. Most of the exoplanets to be observed will be located further away from their parent stars than is Earth from the Sun. These "cold" exoplanets have atmospheric environments conducive for the formation of water and/or ammonia clouds, like Jupiter in the Solar System. I find the mixing ratio of methane and the pressure level of the uppermost cloud deck on these planets can be uniquely determined from their reflection spectra, with moderate spectral resolution, if the cloud deck is between 0.6 and 1.5 bars. The existence of this unique solution is useful for exoplanet direct imaging missions for several reasons. First, the weak bands and strong bands of methane enable the measurement of the methane mixing ratio and the cloud pressure, although an overlying haze layer can bias the estimate of the latter. Second, the cloud pressure, once derived, yields an important constraint on the internal heat flux from the planet, and thus indicating its thermal evolution. Third, water worlds having H2O-dominated atmospheres are likely to have water clouds located higher than the 10-3 bar pressure level, and muted spectral absorption features. These planets would occupy a confined phase space in the color-color diagrams, likely distinguishable from H2-rich giant exoplanets by broadband observations. Therefore, direct-imaging exoplanet missions may offer the capability to broadly distinguish H2-rich giant exoplanets versus H2O-rich super-Earth exoplanets, and to detect ammonia and/or water clouds and methane gas in their atmospheres.

Stakeholder interactions to support service creation in cloud computing

NARCIS (Netherlands)

Wang, Lei; Ferreira Pires, Luis; Wombacher, Andreas; van Sinderen, Marten J.; Chi, Chihung

2010-01-01

Cloud computing is already a major trend in IT. Cloud services are being offered at application (software), platform and infrastructure levels. This paper presents our initial modeling efforts towards service creation at the infrastructure level. The purpose of these modeling efforts is to

Cloud chamber photographs of the cosmic radiation

CERN Document Server

Rochester, George Dixon

1952-01-01

Cloud Chamber Photographs of the Cosmic Radiation focuses on cloud chamber and photographic emulsion wherein the tracks of individual subatomic particles of high energy are studied. The publication first offers information on the technical features of operation and electrons and cascade showers. Discussions focus on the relationship in time and space of counter-controlled tracks; techniques of internal control of the cloud chamber; cascade processes with artificially-produced electrons and photons; and nuclear interaction associated with an extensive shower. The manuscript then elaborates on

Crushing data silos with ownCloud

CERN Multimedia

CERN. Geneva

2013-01-01

More and more people store their personal files and documents in cloud services like Dropbox, Google Drive, Skydrive or iCloud. The reason is that they provide convenient features to sync your files between devices and share them with others. We are heading full speed into a future where a huge piece of the personal information of the world is stored in very few centralized services. Questions emerge what the impact on user privacy, surveillance, lawfulness of content and storage cost will be in in the long run. I don't think that a world where most of the personal data of the world is stored on servers of a hand full companies is a good one. This talk will discuss the problems of a future with centralized cloud file sync and share services and will present ownCloud as a possible solution. ownCloud is a free software project that offers a decentralized alternative to proprietary cloud services where everybody can run an own cloud service comparable with Dropbox but on own hardware and with full ...

PREVENTIVE SIGNATURE MODEL FOR SECURE CLOUD DEPLOYMENT THROUGH FUZZY DATA ARRAY COMPUTATION

Directory of Open Access Journals (Sweden)

R. Poorvadevi

2017-01-01

Full Text Available Cloud computing is a resource pool which offers boundless services by the form of resources to its end users whoever heavily depends on cloud service providers. Cloud is providing the service access across the geographic locations in an efficient way. However it is offering numerous services, client end system is not having adequate methods, security policies and other protocols for using the cloud customer secret level transactions and other privacy related information. So, this proposed model brings the solution for securing the cloud user confidential data, Application deployment and also identifying the genuineness of the user by applying the scheme which is referred as fuzzy data array computation. Fuzzy data array computation provides an effective system is called signature retrieval and evaluation system through which customer’s data can be safeguarded along with their application. This signature system can be implemented on the cloud environment using the cloud sim 3.0 simulator tools. It facilitates the security operation over the data centre and cloud vendor locations in an effective manner.

An assessment of thin cloud detection by applying bidirectional reflectance distribution function model-based background surface reflectance using Geostationary Ocean Color Imager (GOCI): A case study for South Korea

Science.gov (United States)

Kim, Hye-Won; Yeom, Jong-Min; Shin, Daegeun; Choi, Sungwon; Han, Kyung-Soo; Roujean, Jean-Louis

2017-08-01

In this study, a new assessment of thin cloud detection with the application of bidirectional reflectance distribution function (BRDF) model-based background surface reflectance was undertaken by interpreting surface spectra characterized using the Geostationary Ocean Color Imager (GOCI) over a land surface area. Unlike cloud detection over the ocean, the detection of cloud over land surfaces is difficult due to the complicated surface scattering characteristics, which vary among land surface types. Furthermore, in the case of thin clouds, in which the surface and cloud radiation are mixed, it is difficult to detect the clouds in both land and atmospheric fields. Therefore, to interpret background surface reflectance, especially underneath cloud, the semiempirical BRDF model was used to simulate surface reflectance by reflecting solar angle-dependent geostationary sensor geometry. For quantitative validation, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data were used to make a comparison with the proposed cloud masking result. As a result, the new cloud masking scheme resulted in a high probability of detection (POD = 0.82) compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) (POD = 0.808) for all cloud cases. In particular, the agreement between the CALIPSO cloud product and new GOCI cloud mask was over 94% when detecting thin cloud (e.g., altostratus and cirrus) from January 2014 to June 2015. This result is relatively high in comparison with the result from the MODIS Collection 6 cloud mask product (MYD35).

Making and Breaking Clouds

Science.gov (United States)

Kohler, Susanna

2017-10-01

Molecular clouds which youre likely familiar with from stunning popular astronomy imagery lead complicated, tumultuous lives. A recent study has now found that these features must be rapidly built and destroyed.Star-Forming CollapseA Hubble view of a molecular cloud, roughly two light-years long, that has broken off of the Carina Nebula. [NASA/ESA, N. Smith (University of California, Berkeley)/The Hubble Heritage Team (STScI/AURA)]Molecular gas can be found throughout our galaxy in the form of eminently photogenic clouds (as featured throughout this post). Dense, cold molecular gas makes up more than 20% of the Milky Ways total gas mass, and gravitational instabilities within these clouds lead them to collapse under their own weight, resulting in the formation of our galaxys stars.How does this collapse occur? The simplest explanation is that the clouds simply collapse in free fall, with no source of support to counter their contraction. But if all the molecular gas we observe collapsed on free-fall timescales, star formation in our galaxy would churn a rate thats at least an order of magnitude higher than the observed 12 solar masses per year in the Milky Way.Destruction by FeedbackAstronomers have theorized that there may be some mechanism that supports these clouds against gravity, slowing their collapse. But both theoretical studies and observations of the clouds have ruled out most of these potential mechanisms, and mounting evidence supports the original interpretation that molecular clouds are simply gravitationally collapsing.A sub-mm image from ESOs APEX telescope of part of the Taurus molecular cloud, roughly ten light-years long, superimposed on a visible-light image of the region. [ESO/APEX (MPIfR/ESO/OSO)/A. Hacar et al./Digitized Sky Survey 2. Acknowledgment: Davide De Martin]If this is indeed the case, then one explanation for our low observed star formation rate could be that molecular clouds are rapidly destroyed by feedback from the very stars

Automatic Mosaicking of Satellite Imagery Considering the Clouds

Science.gov (United States)

Kang, Yifei; Pan, Li; Chen, Qi; Zhang, Tong; Zhang, Shasha; Liu, Zhang

2016-06-01

With the rapid development of high resolution remote sensing for earth observation technology, satellite imagery is widely used in the fields of resource investigation, environment protection, and agricultural research. Image mosaicking is an important part of satellite imagery production. However, the existence of clouds leads to lots of disadvantages for automatic image mosaicking, mainly in two aspects: 1) Image blurring may be caused during the process of image dodging, 2) Cloudy areas may be passed through by automatically generated seamlines. To address these problems, an automatic mosaicking method is proposed for cloudy satellite imagery in this paper. Firstly, modified Otsu thresholding and morphological processing are employed to extract cloudy areas and obtain the percentage of cloud cover. Then, cloud detection results are used to optimize the process of dodging and mosaicking. Thus, the mosaic image can be combined with more clear-sky areas instead of cloudy areas. Besides, clear-sky areas will be clear and distortionless. The Chinese GF-1 wide-field-of-view orthoimages are employed as experimental data. The performance of the proposed approach is evaluated in four aspects: the effect of cloud detection, the sharpness of clear-sky areas, the rationality of seamlines and efficiency. The evaluation results demonstrated that the mosaic image obtained by our method has fewer clouds, better internal color consistency and better visual clarity compared with that obtained by traditional method. The time consumed by the proposed method for 17 scenes of GF-1 orthoimages is within 4 hours on a desktop computer. The efficiency can meet the general production requirements for massive satellite imagery.

A REVIEW ON SECURITY AND PRIVACY ISSUES IN CLOUD COMPUTING

OpenAIRE

Gulshan Kumar*, Dr.Vijay Laxmi

2017-01-01

Cloud computing is an upcoming paradigm that offers tremendous advantages in economical aspects, such as reduced time to market, flexible computing capabilities, and limitless computing power. To use the full potential of cloud computing, data is transferred, processed and stored by external cloud providers. However, data owners are very skeptical to place their data outside their own control sphere. Cloud computing is a new development of grid, parallel, and distributed computing with visual...

The value of accountability in the cloud : Individuals’ willingness to pay for transparency

NARCIS (Netherlands)

Steijn, Wouter; Niezen, Maartje

2015-01-01

Accountability tools increasingly are introduced in the cloud market in order to offer cloud customers more insight in the use of their data in the cloud and to promote responsible data stewardship. The underlying assumption of tool developers is that people are willing to pay for cloud services

Fast Molecular Cloud Destruction Requires Fast Cloud Formation

Energy Technology Data Exchange (ETDEWEB)

Mac Low, Mordecai-Mark [American Museum of Natural History, 79th Street at Central Park West, New York, NY 10024 (United States); Burkert, Andreas [Universitäts Sternwarte München, Ludwigs-Maximilian-Universität, D-81679 München (Germany); Ibáñez-Mejía, Juan C., E-mail: mordecai@amnh.org, E-mail: burkert@usm.lmu.de, E-mail: ibanez@ph1.uni-koeln.de [Max-Planck-Institut für Extraterrestrische Physik, D-85748 Garching bei München (Germany)

2017-09-20

A large fraction of the gas in the Galaxy is cold, dense, and molecular. If all this gas collapsed under the influence of gravity and formed stars in a local free-fall time, the star formation rate in the Galaxy would exceed that observed by more than an order of magnitude. Other star-forming galaxies behave similarly. Yet, observations and simulations both suggest that the molecular gas is indeed gravitationally collapsing, albeit hierarchically. Prompt stellar feedback offers a potential solution to the low observed star formation rate if it quickly disrupts star-forming clouds during gravitational collapse. However, this requires that molecular clouds must be short-lived objects, raising the question of how so much gas can be observed in the molecular phase. This can occur only if molecular clouds form as quickly as they are destroyed, maintaining a global equilibrium fraction of dense gas. We therefore examine cloud formation timescales. We first demonstrate that supernova and superbubble sweeping cannot produce dense gas at the rate required to match the cloud destruction rate. On the other hand, Toomre gravitational instability can reach the required production rate. We thus argue that, although dense, star-forming gas may last only around a single global free-fall time; the dense gas in star-forming galaxies can globally exist in a state of dynamic equilibrium between formation by gravitational instability and disruption by stellar feedback. At redshift z ≳ 2, the Toomre instability timescale decreases, resulting in a prediction of higher molecular gas fractions at early times, in agreement with the observations.

Preparation of Ultracold Atom Clouds at the Shot Noise Level

DEFF Research Database (Denmark)

Gajdacz, M.; Hilliard, A. J.; Kristensen, Mick

2016-01-01

We prepare number stabilized ultracold atom clouds through the real-time analysis of nondestructive images and the application of feedback. In our experiments, the atom number N∼10^6 is determined by high precision Faraday imaging with uncertainty ΔN below the shot noise level, i.e., ΔN... on this measurement, feedback is applied to reduce the atom number to a user-defined target, whereupon a second imaging series probes the number stabilized cloud. By this method, we show that the atom number in ultracold clouds can be prepared below the shot noise level....

Using MODIS Cloud Regimes to Sort Diagnostic Signals of Aerosol-Cloud-Precipitation Interactions.

Science.gov (United States)

Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin

2017-05-27

Coincident multi-year measurements of aerosol, cloud, precipitation and radiation at near-global scales are analyzed to diagnose their apparent relationships as suggestive of interactions previously proposed based on theoretical, observational, and model constructs. Specifically, we examine whether differences in aerosol loading in separate observations go along with consistently different precipitation, cloud properties, and cloud radiative effects. Our analysis uses a cloud regime (CR) framework to dissect and sort the results. The CRs come from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and are defined as distinct groups of cloud systems with similar co-variations of cloud top pressure and cloud optical thickness. Aerosol optical depth used as proxy for aerosol loading comes from two sources, MODIS observations, and the MERRA-2 re-analysis, and its variability is defined with respect to local seasonal climatologies. The choice of aerosol dataset impacts our results substantially. We also find that the responses of the marine and continental component of a CR are frequently quite disparate. Overall, CRs dominated by warm clouds tend to exhibit less ambiguous signals, but also have more uncertainty with regard to precipitation changes. Finally, we find weak, but occasionally systematic co-variations of select meteorological indicators and aerosol, which serves as a sober reminder that ascribing changes in cloud and cloud-affected variables solely to aerosol variations is precarious.

ID based cryptography for secure cloud data storage

OpenAIRE

Kaaniche , Nesrine; Boudguiga , Aymen; Laurent , Maryline

2013-01-01

International audience; This paper addresses the security issues of storing sensitive data in a cloud storage service and the need for users to trust the commercial cloud providers. It proposes a cryptographic scheme for cloud storage, based on an original usage of ID-Based Cryptography. Our solution has several advantages. First, it provides secrecy for encrypted data which are stored in public servers. Second, it offers controlled data access and sharing among users, so that unauthorized us...

Merging Agents and Cloud Services in Industrial Applications

OpenAIRE

Francisco P. Maturana; Juan L. Asenjo; Neethu S. Philip; Shweta Chatrola

2014-01-01

A novel idea to combine agent technology and cloud computing for monitoring a plant floor system is presented. Cloud infrastructure has been leveraged as the main mechanism for hosting the data and processing needs of a modern industrial information system. The cloud offers unlimited storage and data processing in a near real-time fashion. This paper presents a software-as-a-service (SaaS) architecture for augmenting industrial plant-floor reporting capabilities. This reporting capability has...

Exploring the factors influencing the cloud computing adoption: a systematic study on cloud migration.

Science.gov (United States)

Rai, Rashmi; Sahoo, Gadadhar; Mehfuz, Shabana

2015-01-01

Today, most of the organizations trust on their age old legacy applications, to support their business-critical systems. However, there are several critical concerns, as maintainability and scalability issues, associated with the legacy system. In this background, cloud services offer a more agile and cost effective platform, to support business applications and IT infrastructure. As the adoption of cloud services has been increasing recently and so has been the academic research in cloud migration. However, there is a genuine need of secondary study to further strengthen this research. The primary objective of this paper is to scientifically and systematically identify, categorize and compare the existing research work in the area of legacy to cloud migration. The paper has also endeavored to consolidate the research on Security issues, which is prime factor hindering the adoption of cloud through classifying the studies on secure cloud migration. SLR (Systematic Literature Review) of thirty selected papers, published from 2009 to 2014 was conducted to properly understand the nuances of the security framework. To categorize the selected studies, authors have proposed a conceptual model for cloud migration which has resulted in a resource base of existing solutions for cloud migration. This study concludes that cloud migration research is in seminal stage but simultaneously it is also evolving and maturing, with increasing participation from academics and industry alike. The paper also identifies the need for a secure migration model, which can fortify organization's trust into cloud migration and facilitate necessary tool support to automate the migration process.

Measuring cloud service health using NetFlow/IPFIX: the WikiLeaks case

NARCIS (Netherlands)

Drago, Idilio; Hofstede, R.J.; Sadre, R.; Sperotto, Anna; Pras, Aiko

The increasing trend of outsourcing services to cloud providers is changing the way computing power is delivered to enterprises and end users. Although cloud services offer several advantages, they also make cloud consumers strongly dependent on providers. Hence, consumers have a vital interest to

Cloud computing and patient engagement: leveraging available technology.

Science.gov (United States)

Noblin, Alice; Cortelyou-Ward, Kendall; Servan, Rosa M

2014-01-01

Cloud computing technology has the potential to transform medical practices and improve patient engagement and quality of care. However, issues such as privacy and security and "fit" can make incorporation of the cloud an intimidating decision for many physicians. This article summarizes the four most common types of clouds and discusses their ideal uses, how they engage patients, and how they improve the quality of care offered. This technology also can be used to meet Meaningful Use requirements 1 and 2; and, if speculation is correct, the cloud will provide the necessary support needed for Meaningful Use 3 as well.

Point cloud data management (extended abstract)

NARCIS (Netherlands)

Van Oosterom, P.J.M.; Ravada, S.; Horhammer, M.; Martinez Rubi, O.; Ivanova, M.; Kodde, M.; Tijssen, T.P.M.

2014-01-01

Point cloud data are important sources for 3D geo-information. The point cloud data sets are growing in popularity and in size. Modern Big Data acquisition and processing technologies, such as laser scanning from airborne, mobile, or static platforms, dense image matching from photos, multi-beam

Cloud Based Earth Observation Data Exploitation Platforms

Science.gov (United States)

Romeo, A.; Pinto, S.; Loekken, S.; Marin, A.

2017-12-01

In the last few years data produced daily by several private and public Earth Observation (EO) satellites reached the order of tens of Terabytes, representing for scientists and commercial application developers both a big opportunity for their exploitation and a challenge for their management. New IT technologies, such as Big Data and cloud computing, enable the creation of web-accessible data exploitation platforms, which offer to scientists and application developers the means to access and use EO data in a quick and cost effective way. RHEA Group is particularly active in this sector, supporting the European Space Agency (ESA) in the Exploitation Platforms (EP) initiative, developing technology to build multi cloud platforms for the processing and analysis of Earth Observation data, and collaborating with larger European initiatives such as the European Plate Observing System (EPOS) and the European Open Science Cloud (EOSC). An EP is a virtual workspace, providing a user community with access to (i) large volume of data, (ii) algorithm development and integration environment, (iii) processing software and services (e.g. toolboxes, visualization routines), (iv) computing resources, (v) collaboration tools (e.g. forums, wiki, etc.). When an EP is dedicated to a specific Theme, it becomes a Thematic Exploitation Platform (TEP). Currently, ESA has seven TEPs in a pre-operational phase dedicated to geo-hazards monitoring and prevention, costal zones, forestry areas, hydrology, polar regions, urban areas and food security. On the technology development side, solutions like the multi cloud EO data processing platform provides the technology to integrate ICT resources and EO data from different vendors in a single platform. In particular it offers (i) Multi-cloud data discovery, (ii) Multi-cloud data management and access and (iii) Multi-cloud application deployment. This platform has been demonstrated with the EGI Federated Cloud, Innovation Platform Testbed Poland

Automated 3D-Objectdocumentation on the Base of an Image Set

Directory of Open Access Journals (Sweden)

Sebastian Vetter

2011-12-01

Full Text Available Digital stereo-photogrammetry allows users an automatic evaluation of the spatial dimension and the surface texture of objects. The integration of image analysis techniques simplifies the automation of evaluation of large image sets and offers a high accuracy [1]. Due to the substantial similarities of stereoscopic image pairs, correlation techniques provide measurements of subpixel precision for corresponding image points. With the help of an automated point search algorithm in image sets identical points are used to associate pairs of images to stereo models and group them. The found identical points in all images are basis for calculation of the relative orientation of each stereo model as well as defining the relation of neighboured stereo models. By using proper filter strategies incorrect points are removed and the relative orientation of the stereo model can be made automatically. With the help of 3D-reference points or distances at the object or a defined distance of camera basis the stereo model is orientated absolute. An adapted expansion- and matching algorithm offers the possibility to scan the object surface automatically. The result is a three dimensional point cloud; the scan resolution depends on image quality. With the integration of the iterative closest point- algorithm (ICP these partial point clouds are fitted to a total point cloud. In this way, 3D-reference points are not necessary. With the help of the implemented triangulation algorithm a digital surface models (DSM can be created. The texturing can be made automatically by the usage of the images that were used for scanning the object surface. It is possible to texture the surface model directly or to generate orthophotos automatically. By using of calibrated digital SLR cameras with full frame sensor a high accuracy can be reached. A big advantage is the possibility to control the accuracy and quality of the 3d-objectdocumentation with the resolution of the images. The

Verifying Air Force Weather Passive Satellite Derived Cloud Analysis Products

Science.gov (United States)

Nobis, T. E.

2017-12-01

Air Force Weather (AFW) has developed an hourly World-Wide Merged Cloud Analysis (WWMCA) using imager data from 16 geostationary and polar-orbiting satellites. The analysis product contains information on cloud fraction, height, type and various optical properties including optical depth and integrated water path. All of these products are derived using a suite of algorithms which rely exclusively on passively sensed data from short, mid and long wave imager data. The system integrates satellites with a wide-range of capabilities, from the relatively simple two-channel OLS imager to the 16 channel ABI/AHI to create a seamless global analysis in real time. Over the last couple of years, AFW has started utilizing independent verification data from active sensed cloud measurements to better understand the performance limitations of the WWMCA. Sources utilized include space based lidars (CALIPSO, CATS) and radar (CloudSat) as well as ground based lidars from the Department of Energy ARM sites and several European cloud radars. This work will present findings from our efforts to compare active and passive sensed cloud information including comparison techniques/limitations as well as performance of the passive derived cloud information against the active.

Delivering Unidata Technology via the Cloud

Science.gov (United States)

Fisher, Ward; Oxelson Ganter, Jennifer

2016-04-01

Over the last two years, Docker has emerged as the clear leader in open-source containerization. Containerization technology provides a means by which software can be pre-configured and packaged into a single unit, i.e. a container. This container can then be easily deployed either on local or remote systems. Containerization is particularly advantageous when moving software into the cloud, as it simplifies the process. Unidata is adopting containerization as part of our commitment to migrate our technologies to the cloud. We are using a two-pronged approach in this endeavor. In addition to migrating our data-portal services to a cloud environment, we are also exploring new and novel ways to use cloud-specific technology to serve our community. This effort has resulted in several new cloud/Docker-specific projects at Unidata: "CloudStream," "CloudIDV," and "CloudControl." CloudStream is a docker-based technology stack for bringing legacy desktop software to new computing environments, without the need to invest significant engineering/development resources. CloudStream helps make it easier to run existing software in a cloud environment via a technology called "Application Streaming." CloudIDV is a CloudStream-based implementation of the Unidata Integrated Data Viewer (IDV). CloudIDV serves as a practical example of application streaming, and demonstrates how traditional software can be easily accessed and controlled via a web browser. Finally, CloudControl is a web-based dashboard which provides administrative controls for running docker-based technologies in the cloud, as well as providing user management. In this work we will give an overview of these three open-source technologies and the value they offer to our community.

[Application of single-band brightness variance ratio to the interference dissociation of cloud for satellite data].

Science.gov (United States)

Qu, Wei-ping; Liu, Wen-qing; Liu, Jian-guo; Lu, Yi-huai; Zhu, Jun; Qin, Min; Liu, Cheng

2006-11-01

In satellite remote-sensing detection, cloud as an interference plays a negative role in data retrieval. How to discern the cloud fields with high fidelity thus comes as a need to the following research. A new method rooting in atmospheric radiation characteristics of cloud layer, in the present paper, presents a sort of solution where single-band brightness variance ratio is used to detect the relative intensity of cloud clutter so as to delineate cloud field rapidly and exactly, and the formulae of brightness variance ratio of satellite image, image reflectance variance ratio, and brightness temperature variance ratio of thermal infrared image are also given to enable cloud elimination to produce data free from cloud interference. According to the variance of the penetrating capability for different spectra bands, an objective evaluation is done on cloud penetration of them with the factors that influence penetration effect. Finally, a multi-band data fusion task is completed using the image data of infrared penetration from cirrus nothus. Image data reconstruction is of good quality and exactitude to show the real data of visible band covered by cloud fields. Statistics indicates the consistency of waveband relativity with image data after the data fusion.

The State of Cloud-Based Biospecimen and Biobank Data Management Tools.

Science.gov (United States)

Paul, Shonali; Gade, Aditi; Mallipeddi, Sumani

2017-04-01

Biobanks are critical for collecting and managing high-quality biospecimens from donors with appropriate clinical annotation. The high-quality human biospecimens and associated data are required to better understand disease processes. Therefore, biobanks have become an important and essential resource for healthcare research and drug discovery. However, collecting and managing huge volumes of data (biospecimens and associated clinical data) necessitate that biobanks use appropriate data management solutions that can keep pace with the ever-changing requirements of research. To automate biobank data management, biobanks have been investing in traditional Laboratory Information Management Systems (LIMS). However, there are a myriad of challenges faced by biobanks in acquiring traditional LIMS. Traditional LIMS are cost-intensive and often lack the flexibility to accommodate changes in data sources and workflows. Cloud technology is emerging as an alternative that provides the opportunity to small and medium-sized biobanks to automate their operations in a cost-effective manner, even without IT personnel. Cloud-based solutions offer the advantage of heightened security, rapid scalability, dynamic allocation of services, and can facilitate collaboration between different research groups by using a shared environment on a "pay-as-you-go" basis. The benefits offered by cloud technology have resulted in the development of cloud-based data management solutions as an alternative to traditional on-premise software. After evaluating the advantages offered by cloud technology, several biobanks have started adopting cloud-based tools. Cloud-based tools provide biobanks with easy access to biospecimen data for real-time sharing with clinicians. Another major benefit realized by biobanks by implementing cloud-based applications is unlimited data storage on the cloud and automatic backups for protecting any data loss in the face of natural calamities.

Remote Sensing of Clouds for Solar Forecasting Applications

Science.gov (United States)

Mejia, Felipe

A method for retrieving cloud optical depth (tauc) using a UCSD developed ground- based Sky Imager (USI) is presented. The Radiance Red-Blue Ratio (RRBR) method is motivated from the analysis of simulated images of various tauc produced by a Radiative Transfer Model (RTM). From these images the basic parameters affecting the radiance and RBR of a pixel are identified as the solar zenith angle (SZA), tau c , solar pixel an- gle/scattering angle (SPA), and pixel zenith angle/view angle (PZA). The effects of these parameters are described and the functions for radiance, Ilambda (tau c ,SZA,SPA,PZA) , and the red-blue ratio, RBR(tauc ,SZA,SPA,PZA) , are retrieved from the RTM results. RBR, which is commonly used for cloud detection in sky images, provides non-unique solutions for tau c , where RBR increases with tauc up to about tauc = 1 (depending on other parameters) and then decreases. Therefore, the RRBR algorithm uses the measured Imeaslambda (SPA,PZA) , in addition to RBRmeas (SPA,PZA ) to obtain a unique solution for tauc . The RRBR method is applied to images of liquid water clouds taken by a USI at the Oklahoma Atmospheric Radiation Measurement program (ARM) site over the course of 220 days and compared against measurements from a microwave radiometer (MWR) and output from the Min [ MH96a ] method for overcast skies. tau c values ranged from 0-80 with values over 80 being capped and registered as 80. A tauc RMSE of 2.5 between the Min method [ MH96b ] and the USI are observed. The MWR and USI have an RMSE of 2.2 which is well within the uncertainty of the MWR. The procedure developed here provides a foundation to test and develop other cloud detection algorithms. Using the RRBR tauc estimate as an input we then explore the potential of using tomographic techniques for 3-D cloud reconstruction. The Algebraic Reconstruction Technique (ART) is applied to optical depth maps from sky images to reconstruct 3-D cloud extinction coefficients. Reconstruction accuracy

Spectroscopic diagnostics for ablation cloud of tracer-encapsulated solid pellet in LHD

International Nuclear Information System (INIS)

Tamura, N.; Kalinina, D. V.; Sato, K.; Sudo, S.; Sergeev, V. Yu.; Miroshnikov, I. V.; Sharov, I. A.; Bakhareva, O. A.; Ivanova, D. M.; Timokhin, V. M.; Kuteev, B. V.

2008-01-01

In the Large Helical Device (LHD), various spectroscopic diagnostics have been applied to study the ablation process of an advanced impurity pellet, tracer-encapsulated solid pellet (TESPEL). The total light emission from the ablation cloud of TESPEL is measured by photomultipliers equipped with individual interference filters, which provide information about the TESPEL penetration depth. The spectra emitted from the TESPEL ablation cloud are measured with a 250 mm Czerny-Turner spectrometer equipped with an intensified charge coupled device detector, which is operated in the fast kinetic mode. This diagnostic allows us to evaluate the temporal evolution of the electron density in the TESPEL ablation cloud. In order to gain information about the spatial distribution of the cloud parameters, a nine image optical system that can simultaneously acquire nine images of the TESPEL ablation cloud has recently been developed. Several images of the TESPEL ablation cloud in different spectral domains will give us the spatial distribution of the TESPEL cloud density and temperature.

Global cloud database from VIRS and MODIS for CERES

Science.gov (United States)

Minnis, Patrick; Young, David F.; Wielicki, Bruce A.; Sun-Mack, Sunny; Trepte, Qing Z.; Chen, Yan; Heck, Patrick W.; Dong, Xiquan

2003-04-01

The NASA CERES Project has developed a combined radiation and cloud property dataset using the CERES scanners and matched spectral data from high-resolution imagers, the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. The diurnal cycle can be well-characterized over most of the globe using the combinations of TRMM, Aqua, and Terra data. The cloud properties are derived from the imagers using state-of-the-art methods and include cloud fraction, height, optical depth, phase, effective particle size, emissivity, and ice or liquid water path. These cloud products are convolved into the matching CERES fields of view to provide simultaneous cloud and radiation data at an unprecedented accuracy. Results are available for at least 3 years of VIRS data and 1 year of Terra MODIS data. The various cloud products are compared with similar quantities from climatological sources and instantaneous active remote sensors. The cloud amounts are very similar to those from surface observer climatologies and are 6-7% less than those from a satellite-based climatology. Optical depths are 2-3 times smaller than those from the satellite climatology, but are within 5% of those from the surface remote sensing. Cloud droplet sizes and liquid water paths are within 10% of the surface results on average for stratus clouds. The VIRS and MODIS retrievals are very consistent with differences that usually can be explained by sampling, calibration, or resolution differences. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.

Cloud computing and ROI a new framework for it strategy

CERN Document Server

Mohapatra, Sanjay

2014-01-01

This book develops an IT strategy for cloud computing that helps businesses evaluate their readiness for cloud services and calculate the ROI. The framework provided helps reduce risks involved in transitioning from traditional "on site" IT strategy to virtual "cloud computing." Since the advent of cloud computing, many organizations have made substantial gains implementing this innovation. Cloud computing allows companies to focus more on their core competencies, as IT enablement is taken care of through cloud services. Cloud Computing and ROI includes case studies covering retail, automobile and food processing industries. Each of these case studies have successfully implemented the cloud computing framework and their strategies are explained. As cloud computing may not be ideal for all businesses, criteria?are also offered to help determine if this strategy should be adopt.

Cosmic ray decreases affect atmospheric aerosols and clouds

DEFF Research Database (Denmark)

Svensmark, Henrik; Bondo, Torsten; Svensmark, J.

2009-01-01

Close passages of coronal mass ejections from the sun are signaled at the Earth's surface by Forbush decreases in cosmic ray counts. We find that low clouds contain less liquid water following Forbush decreases, and for the most influential events the liquid water in the oceanic atmosphere can...... diminish by as much as 7%. Cloud water content as gauged by the Special Sensor Microwave/Imager (SSM/I) reaches a minimum ≈7 days after the Forbush minimum in cosmic rays, and so does the fraction of low clouds seen by the Moderate Resolution Imaging Spectroradiometer (MODIS) and in the International...

Blueprint template support for engineering cloud-based services

NARCIS (Netherlands)

Nguyen, D.K.; Lelli, F.; Taher, Y.; Parkin, M.S.; Papazoglou, M.; van den Heuvel, W.J.A.M.; Abramowicz, W.; Martín Llorente, I.; Surridge, M.; Zisman, A.; Vayssière, J.

2011-01-01

Current cloud-based service offerings are often provided as one-size-fits-all solutions and give little or no room for customization. This limits the ability for application developers to pick and choose offerings from multiple software, platform, infrastructure service providers and configure them

Foundations of Blueprint for Cloud-based Service Engineering

NARCIS (Netherlands)

Nguyen, D.K.

2011-01-01

Current cloud-based service offerings are often provided as one-size-fits-all solution and give little or no room for customization. This limits the ability for application developers to pick and choose offerings from multiple software, platform and infrastructure service providers and configure

The Feasibility of 3d Point Cloud Generation from Smartphones

Science.gov (United States)

Alsubaie, N.; El-Sheimy, N.

2016-06-01

This paper proposes a new technique for increasing the accuracy of direct geo-referenced image-based 3D point cloud generated from low-cost sensors in smartphones. The smartphone's motion sensors are used to directly acquire the Exterior Orientation Parameters (EOPs) of the captured images. These EOPs, along with the Interior Orientation Parameters (IOPs) of the camera/ phone, are used to reconstruct the image-based 3D point cloud. However, because smartphone motion sensors suffer from poor GPS accuracy, accumulated drift and high signal noise, inaccurate 3D mapping solutions often result. Therefore, horizontal and vertical linear features, visible in each image, are extracted and used as constraints in the bundle adjustment procedure. These constraints correct the relative position and orientation of the 3D mapping solution. Once the enhanced EOPs are estimated, the semi-global matching algorithm (SGM) is used to generate the image-based dense 3D point cloud. Statistical analysis and assessment are implemented herein, in order to demonstrate the feasibility of 3D point cloud generation from the consumer-grade sensors in smartphones.

Tomographic retrieval of cloud liquid water fields from a single scanning microwave radiometer aboard a moving platform – Part 1: Field trial results from the Wakasa Bay experiment

Directory of Open Access Journals (Sweden)

D. Huang

2010-07-01

Full Text Available Tomographic methods offer great potential for retrieving three-dimensional spatial distributions of cloud liquid water from radiometric observations by passive microwave sensors. Fixed tomographic systems require multiple radiometers, while mobile systems can use just a single radiometer. Part 1 (this paper examines the results from a limited cloud tomography trial with a single-radiometer airborne system carried out as part of the 2003 AMSR-E validation campaign over Wakasa Bay of the Sea of Japan. During this trial, the Polarimetric Scanning Radiometer (PSR and Microwave Imaging Radiometer (MIR aboard the NASA P-3 research aircraft provided a useful dataset for testing the cloud tomography method over a system of low-level clouds. We do tomographic retrievals with a constrained inversion algorithm using three configurations: PSR, MIR, and combined PSR and MIR data. The liquid water paths from the PSR retrieval are consistent with those from the MIR retrieval. The retrieved cloud field based on the combined data appears to be physically plausible and consistent with the cloud image obtained by a cloud radar. We find that some vertically-uniform clouds appear at high altitudes in the retrieved field where the radar shows clear sky. This is likely due to the sub-optimal data collection strategy. This sets the stage for Part 2 of this study that aims to define optimal data collection strategies using observation system simulation experiments.

The sensitivities of in cloud and cloud top phase distributions to primary ice formation in ICON-LEM

Science.gov (United States)

Beydoun, H.; Karrer, M.; Tonttila, J.; Hoose, C.

2017-12-01

Mixed phase clouds remain a leading source of uncertainty in our attempt to quantify cloud-climate and aerosol-cloud climate interactions. Nevertheless, recent advances in parametrizing the primary ice formation process, high resolution cloud modelling, and retrievals of cloud phase distributions from satellite data offer an excellent opportunity to conduct closure studies on the sensitivity of the cloud phase to microphysical and dynamical processes. Particularly, the reliability of satellite data to resolve the phase at the top of the cloud provides a promising benchmark to compare model output to. We run large eddy simulations with the new ICOsahedral Non-hydrostatic atmosphere model (ICON) to place bounds on the sensitivity of in cloud and cloud top phase to the primary ice formation process. State of the art primary ice formation parametrizations in the form of the cumulative ice active site density ns are implemented in idealized deep convective cloud simulations. We exploit the ability of ICON-LEM to switch between a two moment microphysics scheme and the newly developed Predicted Particle Properties (P3) scheme by running our simulations in both configurations for comparison. To quantify the sensitivity of cloud phase to primary ice formation, cloud ice content is evaluated against order of magnitude changes in ns at variable convective strengths. Furthermore, we assess differences between in cloud and cloud top phase distributions as well as the potential impact of updraft velocity on the suppression of the Wegener-Bergeron-Findeisen process. The study aims to evaluate our practical understanding of primary ice formation in the context of predicting the structure and evolution of mixed phase clouds.

An overview of cloud services adoption challenges in higher education institutions

OpenAIRE

Alharthi, Abdulrahman; Yahya, Fara; Walters, Robert John; Wills, Gary

2015-01-01

Information Technology (IT) plays an important role in enabling education services be delivered to users. Most education online services in universities have been run on the cloud to provide services to support students, lecturers, researchers and administration staff. These are enabled with the emergence of cloud computing in the world of IT. Cloud computing offers on demand Internet-based computing services. This paper presents an overview of cloud computing adoption in higher education, ma...

Cloud Computing with iPlant Atmosphere.

Science.gov (United States)

McKay, Sheldon J; Skidmore, Edwin J; LaRose, Christopher J; Mercer, Andre W; Noutsos, Christos

2013-10-15

Cloud Computing refers to distributed computing platforms that use virtualization software to provide easy access to physical computing infrastructure and data storage, typically administered through a Web interface. Cloud-based computing provides access to powerful servers, with specific software and virtual hardware configurations, while eliminating the initial capital cost of expensive computers and reducing the ongoing operating costs of system administration, maintenance contracts, power consumption, and cooling. This eliminates a significant barrier to entry into bioinformatics and high-performance computing for many researchers. This is especially true of free or modestly priced cloud computing services. The iPlant Collaborative offers a free cloud computing service, Atmosphere, which allows users to easily create and use instances on virtual servers preconfigured for their analytical needs. Atmosphere is a self-service, on-demand platform for scientific computing. This unit demonstrates how to set up, access and use cloud computing in Atmosphere. Copyright © 2013 John Wiley & Sons, Inc.

The Evolution of Cloud Computing in ATLAS

CERN Document Server

AUTHOR|(INSPIRE)INSPIRE-00224309; The ATLAS collaboration; Berghaus, Frank; Love, Peter; Leblanc, Matthew Edgar; Di Girolamo, Alessandro; Paterson, Michael; Gable, Ian; Sobie, Randall; Field, Laurence

2015-01-01

The ATLAS experiment has successfully incorporated cloud computing technology and cloud resources into its primarily grid-based model of distributed computing. Cloud R&D activities continue to mature and transition into stable production systems, while ongoing evolutionary changes are still needed to adapt and refine the approaches used, in response to changes in prevailing cloud technology. In addition, completely new developments are needed to handle emerging requirements. This work will describe the overall evolution of cloud computing in ATLAS. The current status of the VM management systems used for harnessing IAAS resources will be discussed. Monitoring and accounting systems tailored for clouds are needed to complete the integration of cloud resources within ATLAS' distributed computing framework. We are developing and deploying new solutions to address the challenge of operation in a geographically distributed multi-cloud scenario, including a system for managing VM images across multiple clouds, ...

Fuzzy AutoEncode Based Cloud Detection for Remote Sensing Imagery

Directory of Open Access Journals (Sweden)

Zhenfeng Shao

2017-03-01

Full Text Available Cloud detection of remote sensing imagery is quite challenging due to the influence of complicated underlying surfaces and the variety of cloud types. Currently, most of the methods mainly rely on prior knowledge to extract features artificially for cloud detection. However, these features may not be able to accurately represent the cloud characteristics under complex environment. In this paper, we adopt an innovative model named Fuzzy Autoencode Model (FAEM to integrate the feature learning ability of stacked autoencode networks and the detection ability of fuzzy function for highly accurate cloud detection on remote sensing imagery. Our proposed method begins by selecting and fusing spectral, texture, and structure information. Thereafter, the proposed technique established a FAEM to learn the deep discriminative features from a great deal of selected information. Finally, the learned features are mapped to the corresponding cloud density map with a fuzzy function. To demonstrate the effectiveness of the proposed method, 172 Landsat ETM+ images and 25 GF-1 images with different spatial resolutions are used in this paper. For the convenience of accuracy assessment, ground truth data are manually outlined. Results show that the average RER (ratio of right rate and error rate on Landsat images is greater than 29, while the average RER of Support Vector Machine (SVM is 21.8 and Random Forest (RF is 23. The results on GF-1 images exhibit similar performance as Landsat images with the average RER of 25.9, which is much higher than the results of SVM and RF. Compared to traditional methods, our technique has attained higher average cloud detection accuracy for either different spatial resolutions or various land surfaces.

The application of time series models to cloud field morphology analysis

Science.gov (United States)

Chin, Roland T.; Jau, Jack Y. C.; Weinman, James A.

1987-01-01

A modeling method for the quantitative description of remotely sensed cloud field images is presented. A two-dimensional texture modeling scheme based on one-dimensional time series procedures is adopted for this purpose. The time series procedure used is the seasonal autoregressive, moving average (ARMA) process in Box and Jenkins. Cloud field properties such as directionality, clustering and cloud coverage can be retrieved by this method. It has been demonstrated that a cloud field image can be quantitatively defined by a small set of parameters and synthesized surrogates can be reconstructed from these model parameters. This method enables cloud climatology to be studied quantitatively.

A QR code based zero-watermarking scheme for authentication of medical images in teleradiology cloud.

Science.gov (United States)

Seenivasagam, V; Velumani, R

2013-01-01

Healthcare institutions adapt cloud based archiving of medical images and patient records to share them efficiently. Controlled access to these records and authentication of images must be enforced to mitigate fraudulent activities and medical errors. This paper presents a zero-watermarking scheme implemented in the composite Contourlet Transform (CT)-Singular Value Decomposition (SVD) domain for unambiguous authentication of medical images. Further, a framework is proposed for accessing patient records based on the watermarking scheme. The patient identification details and a link to patient data encoded into a Quick Response (QR) code serves as the watermark. In the proposed scheme, the medical image is not subjected to degradations due to watermarking. Patient authentication and authorized access to patient data are realized on combining a Secret Share with the Master Share constructed from invariant features of the medical image. The Hu's invariant image moments are exploited in creating the Master Share. The proposed system is evaluated with Checkmark software and is found to be robust to both geometric and non geometric attacks.