A New Approach to Evaporation

Author(s):  
Derek F. Dinnage

The ever growing need for the removal of water from solutions has brought forward the development of many new techniques. As the state-of-the-art has become more sophisticated, specialist designs have been evolved to cater for particular requirements. Paper published with permission.

2015 ◽  
Author(s):  
Rodrigo Goulart ◽  
Juliano De Carvalho ◽  
Vera De Lima

Word Sense Disambiguation (WSD) is an important task for Biomedicine text-mining. Supervised WSD methods have the best results but they are complex and their cost for testing is too high. This work presents an experiment on WSD using graph-based approaches (unsupervised methods). Three algorithms were tested and compared to the state of the art. Results indicate that similar performance could be reached with different levels of complexity, what may point to a new approach to this problem.


Author(s):  
Tianxing Wu ◽  
Guilin Qi ◽  
Bin Luo ◽  
Lei Zhang ◽  
Haofen Wang

Extracting knowledge from Wikipedia has attracted much attention in recent ten years. One of the most valuable kinds of knowledge is type information, which refers to the axioms stating that an instance is of a certain type. Current approaches for inferring the types of instances from Wikipedia mainly rely on some language-specific rules. Since these rules cannot catch the semantic associations between instances and classes (i.e. candidate types), it may lead to mistakes and omissions in the process of type inference. The authors propose a new approach leveraging attributes to perform language-independent type inference of the instances from Wikipedia. The proposed approach is applied to the whole English and Chinese Wikipedia, which results in the first version of MulType (Multilingual Type Information), a knowledge base describing the types of instances from multilingual Wikipedia. Experimental results show that not only the proposed approach outperforms the state-of-the-art comparison methods, but also MulType contains lots of new and high-quality type information.


2008 ◽  
Vol 142 (1-2) ◽  
pp. 20-42 ◽  
Author(s):  
George D. Panagiotou ◽  
Theano Petsi ◽  
Kyriakos Bourikas ◽  
Christos S. Garoufalis ◽  
Athanassios Tsevis ◽  
...  

2020 ◽  
Vol 13 (7) ◽  
pp. 3909-3922
Author(s):  
Florian Tornow ◽  
Carlos Domenech ◽  
Howard W. Barker ◽  
René Preusker ◽  
Jürgen Fischer

Abstract. Shortwave (SW) fluxes estimated from broadband radiometry rely on empirically gathered and hemispherically resolved fields of outgoing top-of-atmosphere (TOA) radiances. This study aims to provide more accurate and precise fields of TOA SW radiances reflected from clouds over ocean by introducing a novel semiphysical model predicting radiances per narrow sun-observer geometry. This model was statistically trained using CERES-measured radiances paired with MODIS-retrieved cloud parameters as well as reanalysis-based geophysical parameters. By using radiative transfer approximations as a framework to ingest the above parameters, the new approach incorporates cloud-top effective radius and above-cloud water vapor in addition to traditionally used cloud optical depth, cloud fraction, cloud phase, and surface wind speed. A two-stream cloud albedo – serving to statistically incorporate cloud optical thickness and cloud-top effective radius – and Cox–Munk ocean reflectance were used to describe an albedo over each CERES footprint. Effective-radius-dependent asymmetry parameters were obtained empirically and separately for each viewing-illumination geometry. A simple equation of radiative transfer, with this albedo and attenuating above-cloud water vapor as inputs, was used in its log-linear form to allow for statistical optimization. We identified the two-stream functional form that minimized radiance residuals calculated against CERES observations and outperformed the state-of-the-art approach for most observer geometries outside the sun-glint and solar zenith angles between 20 and 70∘, reducing the median SD of radiance residuals per solar geometry by up to 13.2 % for liquid clouds, 1.9 % for ice clouds, and 35.8 % for footprints containing both cloud phases. Geometries affected by sun glint (constituting between 10 % and 1 % of the discretized upward hemisphere for solar zenith angles of 20 and 70∘, respectively), however, often showed weaker performance when handled with the new approach and had increased residuals by as much as 60 % compared to the state-of-the-art approach. Overall, uncertainties were reduced for liquid-phase and mixed-phase footprints by 5.76 % and 10.81 %, respectively, while uncertainties for ice-phase footprints increased by 0.34 %. Tested for a variety of scenes, we further demonstrated the plausibility of scene-wise predicted radiance fields. This new approach may prove useful when employed in angular distribution models and may result in improved flux estimates, in particular dealing with clouds characterized by small or large droplet/crystal sizes.


Author(s):  
Daniel Rehfeldt ◽  
Thorsten Koch

The prize-collecting Steiner tree problem (PCSTP) is a well-known generalization of the classic Steiner tree problem in graphs, with a large number of practical applications. It attracted particular interest during the 11th DIMACS Challenge in 2014, and since then, several PCSTP solvers have been introduced in the literature. Although these new solvers further, and often drastically, improved on the results of the DIMACS Challenge, many PCSTP benchmark instances have remained unsolved. The following article describes further advances in the state of the art in exact PCSTP solving. It introduces new techniques and algorithms for PCSTP, involving various new transformations (or reductions) of PCSTP instances to equivalent problems, for example, to decrease the problem size or to obtain a better integer programming formulation. Several of the new techniques and algorithms provably dominate previous approaches. Further theoretical properties of the new components, such as their complexity, are discussed. Also, new complexity results for the exact solution of PCSTP and related problems are described, which form the base of the algorithm design. Finally, the new developments also translate into a strong computational performance: the resulting exact PCSTP solver outperforms all previous approaches, both in terms of runtime and solvability. In particular, it solves several formerly intractable benchmark instances from the 11th DIMACS Challenge to optimality. Moreover, several recently introduced large-scale instances with up to 10 million edges, previously considered to be too large for any exact approach, can now be solved to optimality in less than two hours. Summary of Contribution: The prize-collecting Steiner tree problem (PCSTP) is a well-known generalization of the classic Steiner tree problem in graphs, with many practical applications. The article introduces and analyses new techniques and algorithms for PCSTP that ultimately aim for improved (practical) exact solution. The algorithmic developments are underpinned by results on theoretical aspects, such as fixed-parameter tractability of PCSTP. Computationally, we considerably push the limits of tractibility, being able to solve PCSTP instances with up to 10 million edges. The new solver, which also considerably outperforms the state of the art on smaller instances, will be made publicly available as part of the SCIP Optimization Suite.


2022 ◽  
pp. 580-606
Author(s):  
Tianxing Wu ◽  
Guilin Qi ◽  
Bin Luo ◽  
Lei Zhang ◽  
Haofen Wang

Extracting knowledge from Wikipedia has attracted much attention in recent ten years. One of the most valuable kinds of knowledge is type information, which refers to the axioms stating that an instance is of a certain type. Current approaches for inferring the types of instances from Wikipedia mainly rely on some language-specific rules. Since these rules cannot catch the semantic associations between instances and classes (i.e. candidate types), it may lead to mistakes and omissions in the process of type inference. The authors propose a new approach leveraging attributes to perform language-independent type inference of the instances from Wikipedia. The proposed approach is applied to the whole English and Chinese Wikipedia, which results in the first version of MulType (Multilingual Type Information), a knowledge base describing the types of instances from multilingual Wikipedia. Experimental results show that not only the proposed approach outperforms the state-of-the-art comparison methods, but also MulType contains lots of new and high-quality type information.


1968 ◽  
Vol 5 (04) ◽  
pp. 410-426
Author(s):  
Arthur Pitchersky ◽  
Arthur Southerland

The increasing demand for a flexible Naval response to a broad spectrum of military situations imposes a demand to carry out missions in increasingly higher sea states. Launching and retrieving buoyant objects or loading cargo into boats responding to the ocean-air interface requires improved technology for successful operations in high sea states. There is an urgent need for handling systems that provide the degree of control necessary for those Navy missions subjected to an increasing all-weather response. Advances in the state of the art or the development of new techniques are needed to support these operational requirements. This paper will discuss present handling systems and proposed new methods.


2016 ◽  
Vol 4 ◽  
pp. 183-196 ◽  
Author(s):  
Ashish Vaswani ◽  
Kenji Sagae

Transition-based approaches based on local classification are attractive for dependency parsing due to their simplicity and speed, despite producing results slightly below the state-of-the-art. In this paper, we propose a new approach for approximate structured inference for transition-based parsing that produces scores suitable for global scoring using local models. This is accomplished with the introduction of error states in local training, which add information about incorrect derivation paths typically left out completely in locally-trained models. Using neural networks for our local classifiers, our approach achieves 93.61% accuracy for transition-based dependency parsing in English.


2022 ◽  
pp. 15-36
Author(s):  
Elhoucine Essefi

Traditionally, forensic geophysics involves the study, search, localization, and mapping of buried objects or elements within soil, buildings, or water using geophysics tools for legal purposes. Recently, with the evolution of environmental crimes, forensic geophysics gave special care to detection, location, and quantification of polluting products. New techniques including the magnetic susceptibility have emerged to investigate this type of crimes. After discussing the state of the art of forensic geophysics, this chapter proposed the magnetic susceptibility as an efficient tool of environmental crimes detection. A case study of pollution detection was proposed from Tunisia. Being a fast and cheap technique, magnetic surveys represent a real promise for environmental forensic geophysics.


Author(s):  
Amelia A. Lewis ◽  
Eric E. Johnson

A number of issues facing the use of XML tree models in Java are enumerated: multiplicity, interoperability, variability, and weight. The gXML API, following the Handle/Body design pattern and conforming to the XQuery Data Model specification XDM, is proposed as a solution to these problems, and as a platform for advancing the state of the art for XML in Java. gXML is not a new tree model, but a unified API and model following a rigorous, external specification, which can be used with any tree model for which a "bridge" has been developed. Applications and processors targeting the gXML API may then use any supported tree model, as appropriate for the task.


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