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1

Lipponen, Antti, Tero Mielonen, Mikko R. A. Pitkänen, Robert C. Levy, Virginia R. Sawyer, Sami Romakkaniemi, Ville Kolehmainen, and Antti Arola. "Bayesian aerosol retrieval algorithm for MODIS AOD retrieval over land." Atmospheric Measurement Techniques 11, no. 3 (March 19, 2018): 1529–47. http://dx.doi.org/10.5194/amt-11-1529-2018.

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Abstract. We have developed a Bayesian aerosol retrieval (BAR) algorithm for the retrieval of aerosol optical depth (AOD) over land from the Moderate Resolution Imaging Spectroradiometer (MODIS). In the BAR algorithm, we simultaneously retrieve all dark land pixels in a granule, utilize spatial correlation models for the unknown aerosol parameters, use a statistical prior model for the surface reflectance, and take into account the uncertainties due to fixed aerosol models. The retrieved parameters are total AOD at 0.55 µm, fine-mode fraction (FMF), and surface reflectances at four different w
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Norquist, Donald C., Paul R. Desrochers, Patrick J. McNicholl, and John R. Roadcap. "A Characterization of Cirrus Cloud Properties That Affect Laser Propagation." Journal of Applied Meteorology and Climatology 47, no. 5 (May 1, 2008): 1322–36. http://dx.doi.org/10.1175/2007jamc1756.1.

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Abstract Future high-altitude laser systems may be affected by cirrus clouds. Laser transmission models were applied to measured and retrieved cirrus properties to determine cirrus impact on power incident on a target or receiver. A major goal was to see how well radiosondes and geostationary satellite imagery could specify the required properties. Based on the use of ground-based radar and lidar measurements as a reference, errors in cirrus-top and cirrus-base height estimates from radiosonde observations were 20%–25% of geostationary satellite retrieval errors. Radiosondes had a perfect cirr
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Karthikeyan, Lanka, Ming Pan, Dasika Nagesh Kumar, and Eric F. Wood. "Effect of Structural Uncertainty in Passive Microwave Soil Moisture Retrieval Algorithm." Sensors 20, no. 4 (February 24, 2020): 1225. http://dx.doi.org/10.3390/s20041225.

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Passive microwave sensors use a radiative transfer model (RTM) to retrieve soil moisture (SM) using brightness temperatures (TB) at low microwave frequencies. Vegetation optical depth (VOD) is a key input to the RTM. Retrieval algorithms can analytically invert the RTM using dual-polarized TB measurements to retrieve the VOD and SM concurrently. Algorithms in this regard typically use the τ-ω types of models, which consist of two third-order polynomial equations and, thus, can have multiple solutions. Through this work, we find that uncertainty occurs due to the structural indeterminacy that i
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Field, R. D., C. Risi, G. A. Schmidt, J. Worden, A. Voulgarakis, A. N. LeGrande, A. H. Sobel, and R. J. Healy. "A Tropospheric Emission Spectrometer HDO/H<sub>2</sub>O retrieval simulator for climate models." Atmospheric Chemistry and Physics Discussions 12, no. 6 (June 5, 2012): 13827–80. http://dx.doi.org/10.5194/acpd-12-13827-2012.

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Abstract. Retrievals of the isotopic composition of water vapor from the Aura Tropospheric Emission Spectrometer (TES) have unique value in constraining moist processes in climate models. Accurate comparison between simulated and retrieved values requires that model profiles that would be poorly retrieved are excluded, and that an instrument operator be applied to the remaining profiles. Typically, this is done by sampling model output at satellite measurement points and using the quality flags and averaging kernels from individual retrievals at specific places and times. This approach is not
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Field, R. D., C. Risi, G. A. Schmidt, J. Worden, A. Voulgarakis, A. N. LeGrande, A. H. Sobel, and R. J. Healy. "A Tropospheric Emission Spectrometer HDO/H<sub>2</sub>O retrieval simulator for climate models." Atmospheric Chemistry and Physics 12, no. 21 (November 12, 2012): 10485–504. http://dx.doi.org/10.5194/acp-12-10485-2012.

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Abstract. Retrievals of the isotopic composition of water vapor from the Aura Tropospheric Emission Spectrometer (TES) have unique value in constraining moist processes in climate models. Accurate comparison between simulated and retrieved values requires that model profiles that would be poorly retrieved are excluded, and that an instrument operator be applied to the remaining profiles. Typically, this is done by sampling model output at satellite measurement points and using the quality flags and averaging kernels from individual retrievals at specific places and times. This approach is not
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6

van Diedenhoven, B., O. P. Hasekamp, and I. Aben. "Surface pressure retrieval from SCIAMACHY measurements in the O<sub>2</sub>A Band: validation of the measurements and sensitivity on aerosols." Atmospheric Chemistry and Physics Discussions 5, no. 2 (March 14, 2005): 1469–99. http://dx.doi.org/10.5194/acpd-5-1469-2005.

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Abstract. We perform surface pressure retrievals from cloud-free Oxygen A band measurements of SCIAMACHY. These retrievals can be well validated because surface pressure is a quantity that is, in general, accurately known from meteorological models. Therefore, surface 5 pressure retrievals and their validation provide important insight into the quality of the instrument calibration. Furthermore, they can provide insight into retrievals which are affected by similar radiation transport processes, for example the retrieval of total columns of H2O, CO, CO2 and CH4. In our retrieval aerosols are n
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Gong, J., and D. L. Wu. "CloudSat-constrained cloud ice water path and cloud top height retrievals from MHS 157 and 183.3 GHz radiances." Atmospheric Measurement Techniques 7, no. 6 (June 26, 2014): 1873–90. http://dx.doi.org/10.5194/amt-7-1873-2014.

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Abstract. Ice water path (IWP) and cloud top height (ht) are two of the key variables in determining cloud radiative and thermodynamical properties in climate models. Large uncertainty remains among IWP measurements from satellite sensors, in large part due to the assumptions made for cloud microphysics in these retrievals. In this study, we develop a fast algorithm to retrieve IWP from the 157, 183.3 ± 3 and 190.3 GHz radiances of the Microwave Humidity Sounder (MHS) such that the MHS cloud ice retrieval is consistent with CloudSat IWP measurements. This retrieval is obtained by constraining
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8

Gong, J., and D. L. Wu. "CloudSat-constrained cloud ice water path and cloud top height retrievals from MHS 157 and 183.3 GHz radiances." Atmospheric Measurement Techniques Discussions 6, no. 5 (September 4, 2013): 8187–233. http://dx.doi.org/10.5194/amtd-6-8187-2013.

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Abstract. Ice water path (IWP) and cloud top height (ht) are two of the key variables to determine cloud radiative and thermodynamical properties in the climate models. Large uncertainty remains among IWP measurements from satellite sensors, in large part due to the assumptions made for cloud microphysics in these retrievals. In this study, we develop a fast algorithm to retrieve IWP from the 157, 183.3 ± 3 and 190.3 GHz radiances of Microwave Humidity Sounder (MHS) such that the MHS cloud ice retrieval is consistent with CloudSat IWP measurements. This retrieval is obtained by constraining th
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9

Chimah, Jonathan N., and Friday Ibiam Ude. "Current trends in information retrieval systems: review of fuzzy set theory and fuzzy Boolean retrieval models." Journal of Library Services and Technologies 2, no. 2 (June 2020): 48–56. http://dx.doi.org/10.47524/jlst.v2i2.5.

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This paper reviews the concept and goal of Information Retrieval Systems (IRSs). It also explains the synonymous concepts in Information Retrieval (IR)which include such terms as: imprecision, vagueness, uncertainty, and inconsistency. Current trends in IRSs are discussed. Fuzzy Set Theory, Fuzzy Retrieval Modelsare reviewed. The paper also discusses extensions of Fuzzy Boolean Retrieval Models including Fuzzy techniques for documents’ indexingandFlexible query languages. Fuzzy associative mechanisms were identified to include:(1)fuzzy pseudothesauri and fuzzy ontologies which can be used to c
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10

van Diedenhoven, B., O. P. Hasekamp, and I. Aben. "Surface pressure retrieval from SCIAMACHY measurements in the O<sub>2</sub> A Band: validation of the measurements and sensitivity on aerosols." Atmospheric Chemistry and Physics 5, no. 8 (August 11, 2005): 2109–20. http://dx.doi.org/10.5194/acp-5-2109-2005.

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Abstract. We perform surface pressure retrievals from cloud-free Oxygen A band measurements of SCIAMACHY. These retrievals can be well validated because surface pressure is a quantity that is, in general, accurately known from meteorological models. Therefore, surface pressure retrievals and their validation provide important insight into the quality of the instrument calibration. Furthermore, they can provide insight into retrievals which are affected by similar radiation transport processes, for example the retrieval of total columns of H2O, CO, CO2 and CH4. In our retrieval aerosols are neg
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11

Fang, He, Tao Xie, William Perrie, Guosheng Zhang, Jingsong Yang, and Yijun He. "Comparison of C-Band Quad-Polarization Synthetic Aperture Radar Wind Retrieval Models." Remote Sensing 10, no. 9 (September 11, 2018): 1448. http://dx.doi.org/10.3390/rs10091448.

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This work discusses the accuracy of C-2PO (C-band cross-polarized ocean backscatter) and CMOD4 (C-band model) geophysical model functions (GMF) for sea surface wind speed retrieval from satellite-born Synthetic Aperture Radar (SAR) images over in the Northwest Pacific off the coast of China. In situ observations are used for comparison of the retrieved wind speed using two established wind retrieval models: C-2PO model and CMOD4 GMF. Using 439 samples from 92 RADARSAT-2 fine quad-polarization SAR images and corresponding reference winds, we created two subset wind speed databases: the training
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12

Kolmonen, P., A. M. Sundström, L. Sogacheva, E. Rodriguez, T. Virtanen, and G. de Leeuw. "Uncertainty characterization of AOD for the AATSR dual and single view retrieval algorithms." Atmospheric Measurement Techniques Discussions 6, no. 2 (April 29, 2013): 4039–75. http://dx.doi.org/10.5194/amtd-6-4039-2013.

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Abstract. The uncertainty associated with satellite-retrieved aerosol properties is needed when these data are used to constrain chemical transport or climate models by using data assimilation. Global uncertainty as provided by comparison with independent ground-based observations is usually not adequate for that purpose. Rather the per-pixel uncertainty is needed. In this work we describe how these are determined in the AATSR dual and single view aerosol retrieval algorithms (ADV and ASV) which are used to retrieve aerosol optical properties from reflectance measured at the top of the atmosph
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13

Giang, Lam Tung, Vo Trung Hung, and Huynh Cong Phap. "Building Proximity Models for Cross Language Information Retrieval." Journal of Science and Technology: Issue on Information and Communications Technology 1 (August 31, 2015): 8. http://dx.doi.org/10.31130/jst.2015.5.

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In information retrieval systems, the proximity of query terms has been employed to enable ranking models to go beyond the ”bag of words” assumption and it can promote scores of documents where the matched query terms are close to each other. In this article, we study the integration of proximity models into cross-language information retrieval systems. The new proximity models are proposed and incorporated into existing cross-language information systems by combining the proximity score and the original score to re-rank retrieved documents. The experiment results show that the proposed models
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14

Chen, Yi-Chen, and Chao-Hung Lin. "IMAGE-BASED AIRBORNE LiDAR POINT CLOUD ENCODING FOR 3D BUILDING MODEL RETRIEVAL." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 24, 2016): 1237–42. http://dx.doi.org/10.5194/isprsarchives-xli-b8-1237-2016.

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With the development of Web 2.0 and cyber city modeling, an increasing number of 3D models have been available on web-based model-sharing platforms with many applications such as navigation, urban planning, and virtual reality. Based on the concept of data reuse, a 3D model retrieval system is proposed to retrieve building models similar to a user-specified query. The basic idea behind this system is to reuse these existing 3D building models instead of reconstruction from point clouds. To efficiently retrieve models, the models in databases are compactly encoded by using a shape descriptor ge
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Chen, Yi-Chen, and Chao-Hung Lin. "IMAGE-BASED AIRBORNE LiDAR POINT CLOUD ENCODING FOR 3D BUILDING MODEL RETRIEVAL." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 24, 2016): 1237–42. http://dx.doi.org/10.5194/isprs-archives-xli-b8-1237-2016.

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With the development of Web 2.0 and cyber city modeling, an increasing number of 3D models have been available on web-based model-sharing platforms with many applications such as navigation, urban planning, and virtual reality. Based on the concept of data reuse, a 3D model retrieval system is proposed to retrieve building models similar to a user-specified query. The basic idea behind this system is to reuse these existing 3D building models instead of reconstruction from point clouds. To efficiently retrieve models, the models in databases are compactly encoded by using a shape descriptor ge
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16

Gao, Huilin, Eric F. Wood, Matthias Drusch, and Matthew F. McCabe. "Copula-Derived Observation Operators for Assimilating TMI and AMSR-E Retrieved Soil Moisture into Land Surface Models." Journal of Hydrometeorology 8, no. 3 (June 1, 2007): 413–29. http://dx.doi.org/10.1175/jhm570.1.

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Abstract Assimilating soil moisture from satellite remote sensing into land surface models (LSMs) has potential for improving model predictions by providing real-time information at large scales. However, the majority of the research demonstrating this potential has been limited to datasets based on either airborne data or synthetic observations. The limited availability of satellite-retrieved soil moisture and the observed qualitative difference between satellite-retrieved and modeled soil moisture has posed challenges in demonstrating the potential over large regions in actual applications.
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Jing, Hui, Mei Fa Huang, and Cong Li. "3D Mechanical Models Retrieval Based on Combined Histograms for Rapid Product Design." Applied Mechanics and Materials 16-19 (October 2009): 65–69. http://dx.doi.org/10.4028/www.scientific.net/amm.16-19.65.

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Shape Distribution (3DSD) and Radius Angle Histogram (RAH) are useful methods for retrieving 3D model in mechanical engineering. Through these methods have advantages such as fast speeds and simple operations, the retrieval precision are not very high enough. To improve the retrieval precision, a new method named combined histograms which integrates the advantages of 3DSD and RAH is proposed. This method makes use of the information both of shape and surface of the models to be retrieved. In the retrieval process, the shape histogram and the radius angle histogram of the retrieved model are fi
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Carlin, Jacob T., Alexander V. Ryzhkov, Jeffrey C. Snyder, and Alexander Khain. "Hydrometeor Mixing Ratio Retrievals for Storm-Scale Radar Data Assimilation: Utility of Current Relations and Potential Benefits of Polarimetry." Monthly Weather Review 144, no. 8 (August 1, 2016): 2981–3001. http://dx.doi.org/10.1175/mwr-d-15-0423.1.

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Abstract The assimilation of radar data into storm-scale numerical weather prediction models has been shown to be beneficial for successfully modeling convective storms. Because of the difficulty of directly assimilating reflectivity (Z), hydrometeor mixing ratios, and sometimes rainfall rate, are often retrieved from Z observations using retrieval relations, and are assimilated as state variables. The most limiting (although widely employed) cases of these relations are derived, and their assumptions and limitations are discussed. To investigate the utility of these retrieval relations for li
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Vlemmix, T., A. J. M. Piters, A. J. C. Berkhout, L. F. L. Gast, P. Wang, and P. F. Levelt. "Ability of the MAX-DOAS method to derive profile information for NO<sub>2</sub>: can the boundary layer and free troposphere be separated?" Atmospheric Measurement Techniques 4, no. 12 (December 9, 2011): 2659–84. http://dx.doi.org/10.5194/amt-4-2659-2011.

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Abstract. Multiple Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) instruments can measure from the ground the absorption by nitrogen dioxide (NO2) of scattered sunlight seen in multiple viewing directions. This paper studies the potential of this technique to derive the vertical distribution of NO2 in the troposphere. Such profile information is essential for detailed comparisons of MAX-DOAS retrievals with other measurement techniques for NO2, e.g. with a lidar or from space. The retrieval algorithm used is based on a pre-calculated look-up table and assumes homogeneous mixing o
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Qiao, Ya-nan, Qinghe Du, and Di-fang Wan. "A study on query terms proximity embedding for information retrieval." International Journal of Distributed Sensor Networks 13, no. 2 (February 2017): 155014771769489. http://dx.doi.org/10.1177/1550147717694891.

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Information retrieval is applied widely to models and algorithms in wireless networks for cyber-physical systems. Query terms proximity has proved that it is a very useful information to improve the performance of information retrieval systems. Query terms proximity cannot retrieve documents independently, and it must be incorporated into original information retrieval models. This article proposes the concept of query term proximity embedding, which is a new method to incorporate query term proximity into original information retrieval models. Moreover, term-field-convolutions frequency frame
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Golitsyna, O. L., and N. V. Maksimov. "Information retrieval models in the context of retrieval tasks." Automatic Documentation and Mathematical Linguistics 45, no. 1 (February 2011): 20–32. http://dx.doi.org/10.3103/s0005105511010079.

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Chiaramella, Y., and J. P. Chevallet. "About Retrieval Models and Logic." Computer Journal 35, no. 3 (June 1, 1992): 233–42. http://dx.doi.org/10.1093/comjnl/35.3.233.

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Fuhr, N. "Probabilistic Models in Information Retrieval." Computer Journal 35, no. 3 (June 1, 1992): 243–55. http://dx.doi.org/10.1093/comjnl/35.3.243.

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Arvola, Paavo, Jaana Kekäläinen, and Marko Junkkari. "Contextualization models for XML retrieval." Information Processing & Management 47, no. 5 (September 2011): 762–76. http://dx.doi.org/10.1016/j.ipm.2011.02.006.

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Dr. V. Suma. "A Novel Information retrieval system for distributed cloud using Hybrid Deep Fuzzy Hashing Algorithm." September 2020 02, no. 03 (August 28, 2020): 151–60. http://dx.doi.org/10.36548/jitdw.2020.3.003.

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The recent technology development fascinates the people towards information and its services. Managing the personal and pubic data is a perennial research topic among researchers. In particular retrieval of information gains more attention as it is important similar to data storing. Clustering based, similarity based, graph based information retrieval systems are evolved to reduce the issues in conventional information retrieval systems. Learning based information retrieval is the present trend and in particular deep neural network is widely adopted due to its retrieval performance. However, t
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Kumari, Monisha, and Dimple Nagpal. "Analysis of lifecycle models and Software Component Retrieval." INSIST 3, no. 2 (October 20, 2018): 149. http://dx.doi.org/10.23960/ins.v3i2.149.

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The development of the software component consists of many stages and the lifecycle models show the flow of the stages that the development of the component follows. The development of the new software from the reusable software component has been challenging as it is always a concern to retrieve the relevant software component from the repository. There are lifecycles for making the design and development of the component more efficient. In this paper, an overview of the software component lifecycle models X-model, Y-model, Z-model, knot model and elite model and phases explanation of the lif
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Zamani, Hamed. "Neural models for information retrieval without labeled data." ACM SIGIR Forum 53, no. 2 (December 2019): 104–5. http://dx.doi.org/10.1145/3458553.3458569.

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Recent developments of machine learning models, and in particular deep neural networks, have yielded significant improvements on several computer vision, natural language processing, and speech recognition tasks. Progress with information retrieval (IR) tasks has been slower, however, due to the lack of large-scale training data as well as neural network models specifically designed for effective information retrieval [9]. In this dissertation, we address these two issues by introducing task-specific neural network architectures for a set of IR tasks and proposing novel unsupervised or weakly
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Goodwin, Travis R., and Sanda M. Harabagiu. "Learning relevance models for patient cohort retrieval." JAMIA Open 1, no. 2 (September 28, 2018): 265–75. http://dx.doi.org/10.1093/jamiaopen/ooy010.

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Abstract Objective We explored how judgements provided by physicians can be used to learn relevance models that enhance the quality of patient cohorts retrieved from Electronic Health Records (EHRs) collections. Methods A very large number of features were extracted from patient cohort descriptions as well as EHR collections. The features were used to investigate retrieving (1) neurology-specific patient cohorts from the de-identified Temple University Hospital electroencephalography (EEG) Corpus as well as (2) the more general cohorts evaluated in the TREC Medical Records Track (TRECMed) from
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Chase, Randy J., Stephen W. Nesbitt, and Greg M. McFarquhar. "A Dual-Frequency Radar Retrieval of Two Parameters of the Snowfall Particle Size Distribution Using a Neural Network." Journal of Applied Meteorology and Climatology 60, no. 3 (March 2021): 341–59. http://dx.doi.org/10.1175/jamc-d-20-0177.1.

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AbstractWith the launch of the Global Precipitation Measurement Dual-Frequency Precipitation Radar (GPM-DPR) in 2014, renewed interest in retrievals of snowfall in the atmospheric column has occurred. The current operational GPM-DPR retrieval largely underestimates surface snowfall accumulation. Here, a neural network (NN) trained on data that are synthetically derived from state-of-the-art ice particle scattering models and measured in situ particle size distributions (PSDs) is used to retrieve two parameters of the PSD: liquid equivalent mass-weighted mean diameter and the liquid equivalent
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Boulet, Gilles, Emilie Delogu, Sameh Saadi, Wafa Chebbi, Albert Olioso, Bernard Mougenot, Pascal Fanise, Zohra Lili-Chabaane, and Jean-Pierre Lagouarde. "Evapotranspiration and evaporation/transpiration partitioning with dual source energy balance models in agricultural lands." Proceedings of the International Association of Hydrological Sciences 380 (December 18, 2018): 17–22. http://dx.doi.org/10.5194/piahs-380-17-2018.

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Abstract. EvapoTranspiration (ET) is an important component of the water cycle, especially in semi-arid lands. Its quantification is crucial for a sustainable management of scarce water resources. A way to quantify ET is to exploit the available surface temperature data from remote sensing as a signature of the surface energy balance, including the latent heat flux. Remotely sensed energy balance models enable to estimate stress levels and, in turn, the water status of most continental surfaces. The evaporation and transpiration components of ET are also just as important in agricultural water
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Yao, Zhigang, Jun Li, Jinlong Li, and Hong Zhang. "Surface Emissivity Impact on Temperature and Moisture Soundings from Hyperspectral Infrared Radiance Measurements." Journal of Applied Meteorology and Climatology 50, no. 6 (June 2011): 1225–35. http://dx.doi.org/10.1175/2010jamc2587.1.

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AbstractAn accurate land surface emissivity (LSE) is critical for the retrieval of atmospheric temperature and moisture profiles along with land surface temperature from hyperspectral infrared (IR) sounder radiances; it is also critical to assimilating IR radiances in numerical weather prediction models over land. To investigate the impact of different LSE datasets on Atmospheric Infrared Sounder (AIRS) sounding retrievals, experiments are conducted by using a one-dimensional variational (1DVAR) retrieval algorithm. Sounding retrievals using constant LSE, the LSE dataset from the Infrared Atmo
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Zakariya, S. M., and Imtiaz A. Khan. "Analysis of combined approaches of CBIR systems by clustering at varying precision levels." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 6 (December 1, 2021): 5009. http://dx.doi.org/10.11591/ijece.v11i6.pp5009-5018.

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&lt;span lang="EN-US"&gt;The image retrieving system is used to retrieve images from the image database. Two types of Image retrieval techniques are commonly used: content-based and text-based techniques. One of the well-known image retrieval techniques that extract the images in an unsupervised way, known as the cluster-based image retrieval technique. In this cluster-based image retrieval, all visual features of an image are combined to find a better retrieval rate and precisions. The objectives of the study were to develop a new model by combining the three traits i.e., color, shape, and te
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Evans, K. Franklin, Alexander Marshak, and Tamás Várnai. "The Potential for Improved Boundary Layer Cloud Optical Depth Retrievals from the Multiple Directions of MISR." Journal of the Atmospheric Sciences 65, no. 10 (October 2008): 3179–96. http://dx.doi.org/10.1175/2008jas2627.1.

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The Multiangle Imaging Spectroradiometer (MISR) views the earth with nine cameras, ranging from a 70° zenith angle viewing forward through nadir to 70° viewing aft. MISR does not have an operational cloud optical depth retrieval algorithm, but previous research has hinted that solar reflection measured in multiple directions might improve cloud optical depth retrievals. This study explores the optical depth information content of MISR’s multiple angles using a retrieval simulation approach. Hundreds of realistic boundary-layer cloud fields are generated with large-eddy simulation (LES) models
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Puthukkudy, Anin, J. Vanderlei Martins, Lorraine A. Remer, Xiaoguang Xu, Oleg Dubovik, Pavel Litvinov, Brent McBride, Sharon Burton, and Henrique M. J. Barbosa. "Retrieval of aerosol properties from Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) observations during ACEPOL 2017." Atmospheric Measurement Techniques 13, no. 10 (October 5, 2020): 5207–36. http://dx.doi.org/10.5194/amt-13-5207-2020.

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Abstract. Multi-angle polarimetric (MAP) imaging of Earth scenes can be used for the retrieval of microphysical and optical parameters of aerosols and clouds. The Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) is an aircraft MAP instrument with a hyper-angular imaging capability of 60 along-track viewing angles at 670 nm and 20 along-track viewing angles at other wavelengths – 440, 550, and 870 nm – across the full 114∘ (94∘) along-track (cross-track) field of view. Here we report the retrieval of aerosol properties using the Generalized Retrieval of Aerosols and Surface Properties (GRAS
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35

Poulsen, C. A., P. D. Watts, G. E. Thomas, A. M. Sayer, R. Siddans, R. G. Grainger, B. N. Lawrence, E. Campmany, S. M. Dean, and C. Arnold. "Cloud retrievals from satellite data using optimal estimation: evaluation and application to ATSR." Atmospheric Measurement Techniques Discussions 4, no. 2 (April 28, 2011): 2389–431. http://dx.doi.org/10.5194/amtd-4-2389-2011.

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Abstract. Clouds play an important role in balancing the Earth's radiation budget. Clouds reflect sunlight which cools the Earth, and also trap infrared radiation in the same manner as greenhouse gases. Changes in cloud cover and cloud properties over time can have important consequences for climate. The Intergovernmental Panel for Climate Change (IPCC) has identified current gaps in the understanding of clouds and related climate feedback processes as a leading cause of uncertainty in forecasting climate change. In this paper we present an algorithm that uses optimal estimation to retrieve cl
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36

van Noije, T. P. C., H. J. Eskes, F. J. Dentener, D. S. Stevenson, K. Ellingsen, M. G. Schultz, O. Wild, et al. "Multi-model ensemble simulations of tropospheric NO<sub>2</sub> compared with GOME retrievals for the year 2000." Atmospheric Chemistry and Physics 6, no. 10 (July 17, 2006): 2943–79. http://dx.doi.org/10.5194/acp-6-2943-2006.

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Abstract. We present a systematic comparison of tropospheric NO2 from 17 global atmospheric chemistry models with three state-of-the-art retrievals from the Global Ozone Monitoring Experiment (GOME) for the year 2000. The models used constant anthropogenic emissions from IIASA/EDGAR3.2 and monthly emissions from biomass burning based on the 1997–2002 average carbon emissions from the Global Fire Emissions Database (GFED). Model output is analyzed at 10:30 local time, close to the overpass time of the ERS-2 satellite, and collocated with the measurements to account for sampling biases due to in
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van Noije, T. P. C., H. J. Eskes, F. J. Dentener, D. S. Stevenson, K. Ellingsen, M. G. Schultz, O. Wild, et al. "Multi-model ensemble simulations of tropospheric NO<sub>2</sub> compared with GOME retrievals for the year 2000." Atmospheric Chemistry and Physics Discussions 6, no. 2 (April 12, 2006): 2965–3047. http://dx.doi.org/10.5194/acpd-6-2965-2006.

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Abstract. We present a systematic comparison of tropospheric NO2 from 17 global atmospheric chemistry models with three state-of-the-art retrievals from the Global Ozone Monitoring Experiment (GOME) for the year 2000. The models used constant anthropogenic emissions from IIASA/EDGAR3.2 and monthly emissions from biomass burning based on the 1997–2002 average carbon emissions from the Global Fire Emissions Database (GFED). Model output is analyzed at 10:30 local time, close to the overpass time of the ERS-2 satellite, and collocated with the measurements to account for sampling biases due to in
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38

Liu, Song. "Inversion Models for the Retrieval of Total and Tropospheric NO2 Columns." Atmosphere 10, no. 10 (October 9, 2019): 607. http://dx.doi.org/10.3390/atmos10100607.

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Inversion models for retrieving the total and tropospheric nitrogen dioxide ( NO 2 ) columns from spaceborne remote sensing data are presented. For total column retrieval, we propose the so-called differential radiance models with internal and external closure and solve the underlying nonlinear equations by using the method of Tikhonov regularization and the iteratively regularized Gauss–Newton method. For tropospheric column retrieval, we design a nonlinear and a linear model by using the results of the total column retrieval and the value of the stratospheric NO 2 column delivered by a strat
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39

Li, Chong, Jing Li, Oleg Dubovik, Zhao-Cheng Zeng, and Yuk L. Yung. "Impact of Aerosol Vertical Distribution on Aerosol Optical Depth Retrieval from Passive Satellite Sensors." Remote Sensing 12, no. 9 (May 11, 2020): 1524. http://dx.doi.org/10.3390/rs12091524.

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When retrieving Aerosol Optical Depth (AOD) from passive satellite sensors, the vertical distribution of aerosols usually needs to be assumed, potentially causing uncertainties in the retrievals. In this study, we use the Moderate Resolution Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) sensors as examples to investigate the impact of aerosol vertical distribution on AOD retrievals. A series of sensitivity experiments was conducted using radiative transfer models with different aerosol profiles and surface conditions. Assuming a 0.2 AOD, we found that the AOD
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Bashir, Shariq. "Evaluating retrieval models using retrievability measurement." ACM SIGIR Forum 46, no. 1 (May 20, 2012): 81. http://dx.doi.org/10.1145/2215676.2215688.

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41

Turtle, H. R., and W. B. Croft. "A Comparison of Text Retrieval Models." Computer Journal 35, no. 3 (June 1, 1992): 279–90. http://dx.doi.org/10.1093/comjnl/35.3.279.

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Bimbo, Alberto Del, and Pietro Pala. "Content-based retrieval of 3D models." ACM Transactions on Multimedia Computing, Communications, and Applications 2, no. 1 (February 2006): 20–43. http://dx.doi.org/10.1145/1126004.1126006.

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Fang, Hui, Tao Tao, and Chengxiang Zhai. "Diagnostic Evaluation of Information Retrieval Models." ACM Transactions on Information Systems 29, no. 2 (April 2011): 1–42. http://dx.doi.org/10.1145/1961209.1961210.

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Nie, Jian-Yun, Guihong Cao, and Jing Bai. "Inferential language models for information retrieval." ACM Transactions on Asian Language Information Processing 5, no. 4 (December 2006): 296–322. http://dx.doi.org/10.1145/1236181.1236183.

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Brainerd, C. J., V. F. Reyna, C. F. A. Gomes, A. E. Kenney, C. J. Gross, E. S. Taub, and R. N. Spreng. "Dual-retrieval models and neurocognitive impairment." Journal of Experimental Psychology: Learning, Memory, and Cognition 40, no. 1 (January 2014): 41–65. http://dx.doi.org/10.1037/a0034057.

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Zhai, ChengXiang. "Statistical Language Models for Information Retrieval." Synthesis Lectures on Human Language Technologies 1, no. 1 (January 2008): 1–141. http://dx.doi.org/10.2200/s00158ed1v01y200811hlt001.

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Roelleke, Thomas. "Information Retrieval Models: Foundations and Relationships." Synthesis Lectures on Information Concepts, Retrieval, and Services 5, no. 3 (July 26, 2013): 1–163. http://dx.doi.org/10.2200/s00494ed1v01y201304icr027.

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Wong, S. K. M., and Y. Y. Yao. "Query formulation in linear retrieval models." Journal of the American Society for Information Science 41, no. 5 (July 1990): 334–41. http://dx.doi.org/10.1002/(sici)1097-4571(199007)41:5<334::aid-asi4>3.0.co;2-2.

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Wilbur, W. John. "Retrieval testing with hypergeometric document models." Journal of the American Society for Information Science 44, no. 6 (July 1993): 340–51. http://dx.doi.org/10.1002/(sici)1097-4571(199307)44:6<340::aid-asi4>3.0.co;2-z.

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Efthimiadis, Efthimis N., David G. Hendry, Efthimis N. Efthimiadis, Pamela Savage-Knepshield, Carol Tenopir, and Peiling Wang. "Mental models of information retrieval systems." Proceedings of the American Society for Information Science and Technology 41, no. 1 (September 22, 2005): 580–81. http://dx.doi.org/10.1002/meet.1450410186.

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