In this paper, we show the existence of a non-solvable Galois extension of Q which is unramified outside 2. The extension K we construct has degree 2251731094732800 = 2(3 · 5 · 17 · 257) and has root discriminant δK < 2 47 8 = 58.68..., and is totally complex.

Re-identification of individuals across camera networks with limited or no overlapping fields of view remains challenging in spite of significant research efforts. In this paper, we propose the use, and extensively evaluate the performance, of four alternatives for re-ID classification: regularized Pairwise Constrained Component Analysis, kernel Local Fisher Discriminant Analysis, Marginal Fish...

This paper presents a constructive method for deriving an updated discriminant eigenspace for classification, when bursts of new classes of data is being added to an initial discriminant eigenspace in the form of random chunks. The proposed Chunk incremental linear discriminant analysis (I-LDA) can effectively evolve a discriminant eigenspace over a fast and large data stream, and extract featu...

B on an extensive survey conducted on the representative sample of displaced persons from Croatian East the purpose of this paper was to highlight the differences in some sociodemographic characteristics, attitudes and expectations of the displaced who distinguish by their willingness to return home under the conditions of the Plan of Peaceful Reintegration. The majority (about 70%) of the inte...

This paper proposes a combined canonical variate analysis (CVA) and Fisher discriminant analysis (FDA) scheme (denoted as CVA–FDA) for fault diagnosis, which employs CVA for pretreating the data and subsequently utilizes FDA for fault classification. In addition to the improved handling of serial correlations in the data, the utilization of CVA in the first step provides similar or reduced dime...

In the past several years, Linear Discriminant Analysis (LDA) is being replaced by Heteroscedastic Discriminant Analysis (HDA), to improve the performance of a recognition system that uses a mixture of diagonal covariance prototypes to model the data. A specific version HDA, popularly known as Maximum Likelihood Linear Transform (MLLT) is also used, on the features finally obtained. However the...