Computer Communication & Collaboration

Computer Communication & Collaboration

ISSN:2292-1028 (Print)    ISSN:2292-1036(Online)

Vol. 5, Issue 3 (2017.08)

Table of Contents

Editorial Board of CCC



1. Constructional Theorems of Maximal Left Singular Languages [Download PDF]


Chunhua Cao, Xueping Ji, Di Yang(Corresponding author), Liu Qin


In this paper, we investigate maximal left singular languages and obtain some constructional theorems of a maximal left singular language by using its unique left singular word.


Maximal Left Singular Language, Left Singular Word, Prefix Code, Dense Language

2. Quantitative "Reading" of the Score Matrix Components in the PCA: New General Tool for Electrochemical Data Analysis [Download PDF]


Raoul R. Nigmatullin(Correspondence author), Herman K. Budnikov, Artem V. Sidelnikov, Elza I. Maksyutova


In this paper, we consider the new quantitative features that can be attached to the conventional PCA. It is based on some peculiarities of the Fourier spectra obtained from the vectors forming the score matrix. These peculiarities allow parameterizing the score vectors and fitting them accurately by the segment of the Fourier series. This key moment can be generalized and used for any vector having the leading frequencies in the Fourier spectrum. As a criterion of this specific behavior the neighboring score vectors should form the Lissajous figures that are very well known in the theory of mechanical vibrations. In addition, we found a new source of information related to analysis of the eigenvalues of the diagonal matrix that are appeared in the singular values decomposition. As an example we considered the region of the remnant currents (that was considered before as spurious) of the electrochemical cell background and found the definite differences between two regimes of the glassy carbon electrode usage. We do hope that these new peculiarities will find a proper place in chemometrics and practical electrochemistry for detection of traces and other micro-components on the background of the given macro-components presenting in some electrochemical cell. In addition, this observation will be useful for the PCA at whole; the found parameterization will help "to read" quantitatively the score matrix vectors and, thereby, makes this analysis more informative and efficient.


PCA, Electrochemical Data Analysis, Electronic Tongues