<abstract xmlns="http://www.w3.org/1999/xhtml">Time-series are ordered sequences of discrete-time data. Due to their temporal dimension, anomaly detection techniques used in time-series have to take into consideration time correlations and other time-related particularities. Generally, in order to evaluate the quality of an anomaly detection technique, the confusion matrix and its derived metrics such as precision and recall are used. These metrics, however, do not take this temporal dimension into consideration. In this paper, we propose three metrics that can be used to evaluate the quality of a classification, while accounting for the temporal dimension found in time-series data.</abstract>

Evaluation metrics for anomaly detection algorithms in time-series

<abstract xmlns="http://www.w3.org/1999/xhtml">In an earlier work [6] the concept of splitting partition of a graph was introduced in connection with the maximum clique problem. A splitting partition of a graph can be used to replace the graph by two smaller graphs in the course of a clique search algorithm. In other words splitting partitions can serve as a branching rule in an algorithm to compute the clique number of a given graph. In the paper we revisit this branching idea. We will describe a technique to construct not necessary optimal splitting partitions. The given graph can be viewed as a metric space and the geometry of this space plays a guiding role. In order to assess the performance of the procedure we carried out numerical experiments.</abstract>

Metric space method for constructing splitting partitions of graphs

<abstract xmlns="http://www.w3.org/1999/xhtml">The debts’ clearing problem is about clearing all the debts in a group of n entities (banks, companies etc.) using a minimal number of money transaction operations. The problem is known to be NP-hard in the strong sense. As for many intractable problems, techniques from the field of artificial intelligence are useful in finding solutions close to optimum for large inputs. An evolutionary algorithm for solving the debts’ clearing problem is proposed.</abstract>

Evolutionary solving of the debts’ clearing problem

<abstract xmlns="http://www.w3.org/1999/xhtml">A vertex v of a given graph G is said to be in a rainbow neighbourhood of G, with respect to a proper coloring C of G, if the closed neighbourhood N[v] of the vertex v consists of at least one vertex from every color class of G with respect to C. A maximal proper coloring of a graph G is a J-coloring of G such that every vertex of G belongs to a rainbow neighbourhood of G. In this paper, we study certain parameters related to J-coloring of certain Mycielski-type graphs.</abstract>

Universidade Federal de Pernambuco Recife

On J-colorability of certain derived graph classes

<abstract xmlns="http://www.w3.org/1999/xhtml">We prove that for a triangulated plane graph it is NP-complete to determine its domination number and its power domination number.</abstract>

Complexity of domination in triangulated plane graphs

<abstract xmlns="http://www.w3.org/1999/xhtml">Graph coloring can be considered as a random experiment with the color of a randomly selected vertex as the random variable. In this paper, we consider the L(2, 1)-coloring of G as the random experiment and we discuss the concept of two fundamental statistical parameters – mean and variance – with respect to the L(2, 1)-coloring of certain fundamental graph classes.</abstract>

On some L(2, 1)-coloring parameters of certain graph classes

<abstract xmlns="http://www.w3.org/1999/xhtml">The existence of edges is a huge challenge with regards to determining lucky k-polynomials of simple connected graphs in general. In this paper the lucky 3-polynomials of path and cycle graphs of order, 3 ≤ n ≤ 8 are presented as the basis for the heuristic method to determine the lucky k-polynomials for k-colorable graphs. The difficulty of adjacency with graphs is illustrated through these elementary graph structures. The results are also illustratively compared with the results for null graphs (edgeless graphs). The paper could serve as a basis for finding recurrence results through innovative methodology.</abstract>

Heuristic method to determine lucky k-polynomials for k-colorable graphs

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Acta Universitatis Sapientiae, Informatica

Acta Universitatis Sapientiae Informatica publishes peer-reviewed, high-quality original papers and surveys in English, in all areas of Computer Science and allied fields. The papers must be self-contained, including the purpose of the research, the basic definitions, the antecedents of the research, the presentation of the state-of-the-art and novel contributions. The articles must contain sufficient references to give the reader a broad view of the studied subject.  Articles must follow the technical requirements described in the Information for Authors. Please note, that if an article fails to do so, it will be rejected without peer-review.  The corresponding author is responsible for obtaining the permission of coauthors and of the authorities or institutions, if needed, for publication, the Editorial Board is disclaiming any responsibility.  The papers have to be prepared carefully, and must include the relevant keywords. References should be listed alphabetically based on the Instruction for Authors given at the address www.acta.sapientia.ro/acta-info/informatica-main.htm.  Why subscribe and read  The journal publishes papers in all fields of Computer Science, so it can satisfy a lot of interests; the online version is very attractive with the hyperlinks.  Why submit  The issues appear regularly 2 times per year, the waiting time is not too long, the online version contains hyperlinks.  Rejection Rate   56%   Archiving  Sciendo archives the contents of this journal in Portico - digital long-term preservation service of scholarly books, journals and collections.  Plagiarism Policy  The editorial board is participating in a growing community of Similarity Check System's users in order to ensure that the content published is original and trustworthy. Similarity Check is a medium that allows for comprehensive manuscripts screening, aimed to eliminate plagiarism and provide a high standard and quality peer-review process.  Article Processing Charge (APC)  The journal does not have article processing charges (APCs) nor article submission charges. 