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Institution

Military Technical Academy

EducationBucharest, Romania
About: Military Technical Academy is a education organization based out in Bucharest, Romania. It is known for research contribution in the topics: Adsorption & Liquid crystal. The organization has 752 authors who have published 1064 publications receiving 10033 citations. The organization is also known as: Technical Military Academy of Bucharest.


Papers
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Journal ArticleDOI
01 Jan 1997-Carbon
TL;DR: The physicochemical properties and the surface chemical structure of the carbon materials obtained by the modification of the commercial activated carbon D43/1 (Carbo-Tech, Essen, Germany) were studied in this article.

1,342 citations

Proceedings ArticleDOI
01 Jun 2018
TL;DR: This paper investigates which configuration and which parameters lead to the best performance of an i-vectors/PLDA based speaker verification system and presents at the end some preliminary experiments in which the utterances comprised in the CSTR VCTK corpus were used besides utterances from MIT-MDSVC for training the total variability covariance matrix and the underlying PLDA matrices.
Abstract: It is known that the performance of the i-vectors/PLDA based speaker verification systems is affected in the cases of short utterances and limited training data The performance degradation appears because the shorter the utterance, the less reliable the extracted i-vector is, and because the total variability covariance matrix and the underlying PLDA matrices need a significant amount of data to be robustly estimated Considering the “MIT Mobile Device Speaker Verification Corpus” (MIT-MDSVC) as a representative dataset for robust speaker verification tasks on limited amount of training data, this paper investigates which configuration and which parameters lead to the best performance of an i-vectors/PLDA based speaker verification The i-vectors/PLDA based system achieved good performance only when the total variability matrix and the underlying PLDA matrices were trained with data belonging to the enrolled speakers This way of training means that the system should be fully retrained when new enrolled speakers were added The performance of the system was more sensitive to the amount of training data of the underlying PLDA matrices than to the amount of training data of the total variability matrix Overall, the Equal Error Rate performance of the i-vectors/PLDA based system was around 1% below the performance of a GMM-UBM system on the chosen dataset The paper presents at the end some preliminary experiments in which the utterances comprised in the CSTR VCTK corpus were used besides utterances from MIT-MDSVC for training the total variability covariance matrix and the underlying PLDA matrices

790 citations

Journal ArticleDOI
01 Jan 2002-Carbon
TL;DR: In this paper, the physicochemical properties, surface chemical structure and some catalytic properties of a series of carbons prepared by nitric acid oxidation of an activated carbon and subsequent heat treatment under vacuum and mild temperature conditions (423 −573 K) were studied.

364 citations

Journal ArticleDOI
01 Jan 2004-Carbon
TL;DR: In this article, the influence of surface chemistry on the electrochemical behavior of granulated and powdered activated carbon samples in the presence of lead(II) ions both in bulk solution and pre-adsorbed on carbon were carried out.

233 citations

Journal ArticleDOI
01 Jul 2008-Carbon
TL;DR: In this article, mesoporous phenolic resin-based carbons were prepared by soft-templating synthesis and activated by KOH, which resulted in a substantial increase of microporosity with simultaneous preservation of mesopural structure.

176 citations


Authors

Showing all 758 results

NameH-indexPapersCitations
Mietek Jaroniec12357179561
Duong D. Do5155815365
Antoni Rogalski4728611516
Roman Dabrowski384696415
Piotr Kowalczyk331643322
Andrzej Bartnik282112495
Jerzy Choma271602783
J. M. D. MacElroy27752268
Tomasz Czujko27922557
Roman Dąbrowski262183394
Krzysztof Czupryński221181458
Przemysław Kula221291448
Joanna Górka22631720
Jerzy Dziaduszek21921527
Paweł Perkowski191111219
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20233
20228
202135
202073
201964
201862