About: Wrocław University of Technology is a education organization based out in Wrocław, Poland. It is known for research contribution in the topics: Laser & Fuzzy logic. The organization has 13115 authors who have published 31279 publications receiving 338694 citations.
Papers published on a yearly basis
TL;DR: The cclib platform as discussed by the authors is a platform for the development of package-independent computational chemistry algorithms, which can automatically detect, parse, and convert the extracted information into a standard internal representation.
Abstract: There are now a wide variety of packages for electronic structure calculations, each of which differs in the algorithms implemented and the output format. Many computational chemistry algorithms are only available to users of a particular package despite being generally applicable to the results of calculations by any package. Here we present cclib, a platform for the development of package-independent computational chemistry algorithms. Files from several versions of multiple electronic structure packages are automatically detected, parsed, and the extracted information converted to a standard internal representation. A number of population analysis algorithms have been implemented as a proof of principle. In addition, cclib is currently used as an input filter for two GUI applications that analyze output files: PyMOlyze and GaussSum. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2008
TL;DR: The observation of strong coupling of a single two-level solid-state system with a photon, as realized by a single quantum dot in a semiconductor microcavity, may provide a basis for future applications in quantum information processing or schemes for coherent control.
Abstract: Cavity quantum electrodynamics, a central research field in optics and solid-state physics, addresses properties of atom-like emitters in cavities and can be divided into a weak and a strong coupling regime. For weak coupling, the spontaneous emission can be enhanced or reduced compared with its vacuum level by tuning discrete cavity modes in and out of resonance with the emitter. However, the most striking change of emission properties occurs when the conditions for strong coupling are fulfilled. In this case there is a change from the usual irreversible spontaneous emission to a reversible exchange of energy between the emitter and the cavity mode. This coherent coupling may provide a basis for future applications in quantum information processing or schemes for coherent control. Until now, strong coupling of individual two-level systems has been observed only for atoms in large cavities. Here we report the observation of strong coupling of a single two-level solid-state system with a photon, as realized by a single quantum dot in a semiconductor microcavity. The strong coupling is manifest in photoluminescence data that display anti-crossings between the quantum dot exciton and cavity-mode dispersion relations, characterized by a vacuum Rabi splitting of about 140 microeV.
TL;DR: Capacitive deionization (CDI) as mentioned in this paper is a promising technology for energy-efficient water desalination using porous carbon electrodes, which is made of porous carbons optimized for salt storage capacity and ion and electron transport.
TL;DR: Seven vital areas of research in this topic are identified, covering the full spectrum of learning from imbalanced data: classification, regression, clustering, data streams, big data analytics and applications, e.g., in social media and computer vision.
Abstract: Despite more than two decades of continuous development learning from imbalanced data is still a focus of intense research. Starting as a problem of skewed distributions of binary tasks, this topic evolved way beyond this conception. With the expansion of machine learning and data mining, combined with the arrival of big data era, we have gained a deeper insight into the nature of imbalanced learning, while at the same time facing new emerging challenges. Data-level and algorithm-level methods are constantly being improved and hybrid approaches gain increasing popularity. Recent trends focus on analyzing not only the disproportion between classes, but also other difficulties embedded in the nature of data. New real-life problems motivate researchers to focus on computationally efficient, adaptive and real-time methods. This paper aims at discussing open issues and challenges that need to be addressed to further develop the field of imbalanced learning. Seven vital areas of research in this topic are identified, covering the full spectrum of learning from imbalanced data: classification, regression, clustering, data streams, big data analytics and applications, e.g., in social media and computer vision. This paper provides a discussion and suggestions concerning lines of future research for each of them.
15 Mar 2008
TL;DR: In this paper, a general definition and terminology for the Determination of Isotherm Isotherms is defined and a methodology for the determination of the isotherm is presented.
Abstract: The sections in this article are Introduction General Definitions and Terminology Methodology Methods for the Determination of Adsorption Isotherms Operational Definitions of Adsorption Experimental Procedures Outgassing the Adsorbent Determination of the Adsorption Isotherm Evaluation of Adsorption Data Presentation of Primary Data Classification of Adsorption Isotherms Adsorption Hysteresis Determination of Surface Area Application of the BET Method Empirical Procedures for Isotherm Analysis Assessment of Mesoporosity Properties of Porous Materials Application of the Kelvin Equation Computation of Mesopore Size Distribution Assessment of Microporosity Terminology Concept of Surface Area Assessment of Micropore Volume General Conclusions and Recommendations Keywords: physisorption data; IUPAC; adsorption isotherms; surface area; BET isotherm
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|Claude B. Sirlin
|Kim R. Dunbar
|Nitesh V. Chawla
|Edward R. T. Tiekink
|Bobby G. Sumpter
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