<abstract xmlns="http://www.w3.org/1999/xhtml">In this note, we propose a game-theoretic approach for benchmarking computational problems and their solvers. The approach takes an assessment matrix as a payoff matrix for some zero-sum matrix game in which the first player chooses a problem and the second player chooses a solver. The solution in mixed strategies of this game is used to construct a notionally objective ranking of the problems and solvers under consideration. The proposed approach is illustrated in terms of an example to demonstrate its viability and its suitability for applications.</abstract>

Benchmarking of Problems and Solvers: a Game-Theoretic Approach

<abstract xmlns="http://www.w3.org/1999/xhtml">Sentiment classification is an important task which gained extensive attention both in academia and in industry. Many issues related to this task such as handling of negation or of sarcastic utterances were analyzed and accordingly addressed in previous works. However, the issue of class imbalance which often compromises the prediction capabilities of learning algorithms was scarcely studied. In this work, we aim to bridge the gap between imbalanced learning and sentiment analysis. An experimental study including twelve imbalanced learning preprocessing methods, four feature representations, and a dozen of datasets, is carried out in order to analyze the usefulness of imbalanced learning methods for sentiment classification. Moreover, the data difficulty factors — commonly studied in imbalanced learning — are investigated on sentiment corpora to evaluate the impact of class imbalance.</abstract>

Tackling the Problem of Class Imbalance in Multi-class Sentiment Classification: An Experimental Study

<abstract xmlns="http://www.w3.org/1999/xhtml">We consider a single-machine bi-objective scheduling problem with rejection. In this problem, it is possible to reject some jobs. Four algorithms are provided to solve this scheduling problem. The two objectives are the total weighted completion time and the total rejection cost. The aim is to determine the set of efficient solutions. Four heuristics are described; they are implicit enumeration algorithms forming a branching tree, each one having two versions according to the root of the tree corresponding either to acceptance or rejection of all the jobs. The algorithms are first illustrated by a didactic example. Then they are compared on a large set of instances of various dimension and their respective performances are analysed.</abstract>

Toward an Efficient Resolution for a Single-machine Bi-objective Scheduling Problem with Rejection

<abstract xmlns="http://www.w3.org/1999/xhtml">Pixel art is aesthetics that emulates the graphical style of old computer systems. Graphics created with this style needs to be scaled up for presentation on modern displays. The authors proposed two new modifications of image scaling for this purpose: a proximity-based coefficient correction and a transition area restriction. Moreover a new interpolation kernel has been introduced. The presented approaches are aimed at reliable and flexible bitmap scaling while overcoming limitations of existing methods. The new techniques were introduced in an extensible. NET application that serves as both an executable program and a library. The project is designed for prototyping and testing interpolation operations and can be easily expanded with new functionality by adding it to the code or by using the provided interface.</abstract>

Extensible Implementation of Reliable Pixel Art Interpolation

<abstract xmlns="http://www.w3.org/1999/xhtml">In the 1970s, computer scientists began to engage in research in the field of structural biology. The first structural databases, as well as models and methods supporting the analysis of biomolecule structures, started to be created. RNA was put at the centre of scientific interest quite late. However, more and more methods dedicated to this molecule are currently being developed. This paper presents RNApolis - a new computing platform, which offers access to seven bioinformatic tools developed to support the RNA structure study. The set of tools include a structural database and systems for predicting, modelling, annotating and evaluating the RNA structure. RNApolis supports research at different structural levels and allows the discovery, establishment, and validation of relationships between the primary, secondary and tertiary structure of RNAs. The platform is freely available at <ext-link ext-link-type="uri" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="http://rnapolis.pl">http://rnapolis.pl</ext-link></abstract>

RNApolis: Computational Platform for RNA Structure Analysis

AHEAD OF PRINT

Volume 49 (2024): Issue 1 (February 2024)

Volume 48 (2023): Issue 4 (December 2023)

Volume 48 (2023): Issue 3 (September 2023)

Volume 48 (2023): Issue 2 (June 2023)

Volume 48 (2023): Issue 1 (March 2023)

Volume 47 (2022): Issue 4 (December 2022) Special issue: “Recent advances on supply chain network design”

Volume 47 (2022): Issue 3 (September 2022)

Volume 47 (2022): Issue 2 (June 2022)

Volume 47 (2022): Issue 1 (February 2022)

Volume 46 (2021): Issue 4 (December 2021)

Volume 46 (2021): Issue 3 (September 2021)

Volume 46 (2021): Issue 2 (June 2021)

Volume 46 (2021): Issue 1 (March 2021)

Volume 45 (2020): Issue 4 (December 2020)

Volume 45 (2020): Issue 3 (September 2020)

Volume 45 (2020): Issue 2 (June 2020)

Volume 45 (2020): Issue 1 (March 2020)

Volume 44 (2019): Issue 4 (December 2019)

Volume 44 (2019): Issue 3 (September 2019)

Volume 44 (2019): Issue 2 (June 2019)

Volume 44 (2019): Issue 1 (March 2019)

Volume 43 (2018): Issue 4 (December 2018)

Volume 43 (2018): Issue 3 (September 2018)

Volume 43 (2018): Issue 2 (June 2018)

Volume 43 (2018): Issue 1 (March 2018)

Volume 42 (2017): Issue 4 (December 2017)

Volume 42 (2017): Issue 3 (September 2017)

Volume 42 (2017): Issue 2 (June 2017)

Volume 42 (2017): Issue 1 (February 2017)

Volume 41 (2016): Issue 4 (November 2016)

Volume 41 (2016): Issue 3 (September 2016)

Volume 41 (2016): Issue 2 (June 2016)

Volume 41 (2016): Issue 1 (March 2016)

Volume 40 (2015): Issue 4 (December 2015)

Volume 40 (2015): Issue 3 (September 2015)

Volume 40 (2015): Issue 2 (June 2015)

Volume 40 (2015): Issue 1 (March 2015)

Volume 39 (2014): Issue 4 (December 2014)

Volume 39 (2014): Issue 3 (September 2014)

Volume 39 (2014): Issue 2 (June 2014)

Volume 39 (2014): Issue 1 (February 2014)

Volume 38 (2013): Issue 4 (December 2013)

Volume 38 (2013): Issue 3 (September 2013)

Volume 38 (2013): Issue 2 (June 2013)

Volume 38 (2013): Issue 1 (March 2013)

Volume 37 (2012): Issue 4 (December 2012)

Volume 37 (2012): Issue 3 (September 2012)

Volume 37 (2012): Issue 2 (June 2012)

Volume 37 (2012): Issue 1 (March 2012)

Foundations of Computing and Decision Sciences

ISSN: 0867-6356 (print version)  Foundations of Computing and Decision Sciences (until 1990 Foundations of Control Engineering) is a quarterly peer-reviewed international journal published since 1975. One of its main aims is its focus on the links between Computing (understood in the sense defined in the report of the ACM Task Force on the Core of Computer Science chaired by Peter J. Denning: Computing as a Discipline, CACM, Vol. 32, No. 1, 1989) and broadly understood Decision Sciences.  Scope of topics  The journal provides a forum for exchange of ideas for researchers in the fields of computing and decision sciences. The scope of the journal covers various areas of computing and decision sciences, particularly:    approximate reasoning,  artificial intelligence,  combinatorial optimization,  computational complexity theory,  databases and data warehouses,  intelligent decision support,  knowledge engineering,  machine learning and data mining,  metaheuristics,  multiple criteria decision analysis,  networking and distributed systems,  parallel computing and concurrency,  production and project scheduling,  scheduling theory,  soft and granular computing,  software engineering.     Why submit   International editorial board composed of distinguished scholars highly representative of the field of computing and decision sciences,  Quick turnaround,  Comprehensive peer review with at least two highly competent referees assessing each manuscript,  Promotion of published papers in the vast scientific community of researchers working in the field.   Rejection Rate   ca. 60%   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 (iThenticate, https://www.ithenticate.com/ ). 