Applied Computer Science 

About: Applied Computer Science is an academic journal published by Polish Association for Knowledge Promotion. The journal publishes majorly in the area(s): Computer science & Decision support system. It has an ISSN identifier of 1895-3735. Over the lifetime, 423 publications have been published receiving 1194 citations. The journal is also known as: ACS & Applied Computer Science (Lublin).

Choice of best possible metaheuristic algorithm for the travelling salesman problem with limited computational time: quality, uncertainty and speed

Abstract: We compare six metaheuristic optimization algorithms applied to solving the travelling salesman problem. We focus on three classical approaches: genetic algorithms, simulated annealing and tabu search, and compare them with three recently developed ones: quantum annealing, particle swarm optimization and harmony search. On top of that we compare all results with those obtained with a greedy 2-opt interchange algorithm. We are interested in short-term performance of the algorithms and use three criteria to evaluate them: solution quality, standard deviation of results and time needed to reach the optimum. Following the results from simulation experiments we conclude that simulated annealing and tabu search outperform newly developed approaches in short simulation runs with respect to all three criteria. Simulated annealing finds best solutions, yet tabu search has lower variance of re- sults and converges faster.

Is the conventional interval arithmetic correct

Abstract: Interval arithmetic as part of interval mathematics and Granular Computing is unusually im- portant for development of science and engineering in connection with necessity of taking into account uncertainty and approximativeness of data occurring in almost all calculations. Interval arithmetic also conditions development of Artificial Intelligence and especially of automatic think- ing, Computing with Words, grey systems, fuzzy arithmetic and probabilistic arithmetic. However, the mostly used conventional Moore-arithmetic has evident weak-points. These weak-points are well known, but nonetheless it is further on frequently used. The paper presents basic operations of RDM-arithmetic that does not possess faults of Moore-arithmetic. The RDM-arithmetic is based on multi-dimensional approach, the Moore-arithmetic on one-dimensional approach to interval calculations. The paper also presents a testing method, which allows for clear checking whether results of any interval arithmetic are correct or not. The paper contains many examples and illustrations for better understanding of the RDM-arithmetic. In the paper, because of volume limitations only operations of addition and subtraction are discussed. Operations of multiplica- tion and division of intervals will be presented in next publication. Author of the RDM-arithmetic concept is Andrzej Piegat.

Intelligent video surveillance systems for public spaces – a survey

Abstract: In recent years, a large number of cameras have been installed in public spaces as a part of intelligent video surveillance systems. Such systems are being continuously developed due to the advancements in the Video Content Analysis algorithms. In this paper, some of the latest state-of-the-art intelligent video surveillance systems will be presented in the context of their most desirable characteristics and features. Due to the variety of the solutions the following categories have been taken into consideration: systems based on object detection, tracking and movement analysis, systems able to warn against, detect and identify abnormal and alarming situations, systems based on vehicle detection and traffic or parking lots analysis, object counting systems, systems based on multiple integrated camera views, privacy preserving systems and systems based on cloud environment. The paper describes several solutions for each category and underlines main functionalities of the current intelligent surveillance systems.

Comparative study of shape, intensity and texture features and support vector machine for white blood cell classification

Abstract: The complete blood count (CBC) is widely used test for counting and categorizing various pe- ripheral particles in the blood. The main goal of the paper is to count and classify white blood cells (leukocytes) in microscopic images into five major categories using features such as shape, intensity and texture features. The first critical step of counting and classification procedure in- volves segmentation of individual cells in cytological images of thin blood smears. The quality of segmentation has significant impact on the cell type identification, but poor quality, noise, and/or low resolution images make segmentation less reliable. We analyze the performance of our system for three different sets of features and we determine that the best performance is achieved by wavelet features using the Dual-Tree Complex Wavelet Transform (DT-CWT) which is based on multi-resolution characteristics of the image. These features are combined with the Support Vector Machine (SVM) which classifies white blood cells into their five primary types. This approach was validated with experiments conducted on digital normal blood smear images with low resolution.

The mean error estimation of TOPSIS method using a fuzzy reference models

Abstract: The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a commonly used multi-criteria decision-making method. A number of authors have proposed improvements, known as extensions, of the TOPSIS method, but these extensions have not been examined with respect to accuracy. Accuracy estimation is very difficult because reference values for the ob- tained results are not known, therefore, the results of each extension are compared to one another. In this paper, the author propose a new method to estimate the mean error of TOPSIS with the use of a fuzzy reference model (FRM). This method provides reference values. In experiments involving 1,000 models, 28 million cases are simulated to estimate the mean error. Results of four commonly used normalization procedures were compared. Additionally, the author demonstrated the relationship between the value of the mean error and the nonlinearity of models and a number of alternatives.