2016 Federated Conference on Computer Science and Information Systems (FedCSIS)

IN THIS presentation we will argue that Big Data technologies can contribute in an important way to an unprecedented breakthrough in the understanding of oceans as a factor in climate change, in transportation, and in supplying humanity with its important food component. View full abstract»

DIGITAL transformation is a major challenge for many organizations. IT managers in particular not only wonder what the next digital trends in their industry will be, they also need to understand how today's IT organizations will change in light of digital transformation. I will first discuss some foundations of digital transformation and will then present 10 theses on how digital transformation wi... View full abstract»

IN OUR talk we will focus on networks with no predefined infrastructure (ad-hoc networks, sensor networks, vehicular networks). There are many optimization problems derived from the context of such networks including power assignment mechanisms, scheduling, data gathering, etc. We will discuss various techniques tacking these problems emphasizing the importance of mobile nodes locations and its in... View full abstract»

We consider concept of approximate query in RDBMS i.e. query that returns results which may differ from common (exact) query results in a way but its evaluation requires less resources. In the work we focus mostly on time and storage space aspects. We follow one of the state-of-the-art trends using synopses of data as the input of approximate query evaluation. We propose some measures of approxima... View full abstract»

This article is a continuation of previous work, in which a new method of decision tree construction was presented. That method is based on the use of so-called verifying cuts, which can provide knowledge obtained from the attributes frequently eliminated when greedy methods of the choice of singleton best cuts are applied. Till now only one strategy of choosing verifying cuts was examined. It exp... View full abstract»

The paper presents a new method of building a hierarchical model of the state space. The model is extracted fully automatically from game replays that store executed plan traces. It is used by a novel approach for estimating the distance between states in a state-space graph. The estimate is applied in the A* algorithm as a heuristic function to reduce the search space. The method was validated us... View full abstract»

Game theory is a tool that may be used to model a player as an intelligent being - one who seeks to optimize his own performance while taking into account the performance of his opponent. However, it is often challenging to apply the theory in practice. In the naval environment, this approach may be used, for instance, to find the best strategy for an Autonomous Underwater Vehicle (AUV) while cons... View full abstract»

The exploration of a data set consists in grouping similar data. The classical statistical methods often fail when there is is no minimal assumption on the clusters. Our approach is based on the links between data, but the pairwise comparison between data and the importance of the links depend heavily on context where data lies. We propose to analyze a dataset through methods of the social choice ... View full abstract»

Fishing activity detection is important for fishery management to maintain abundant oceans. This paper presents a novel approach to identifying fishing activities from Automatic Identification System (AIS) data using Conditional Random Fields (CRFs). CRFs are popular for solving structured prediction problems such as sequence labeling in natural language processing. To model the conditional probab... View full abstract»

The paper concerns automatic recognition of emotion induced by music (MER, Music Emotion Recognition). Comparison of different sparse coding schemes in a task of MER is the main contribution of the paper. We consider a domain-specific categorization of emotions, called Geneva Emotional Music Scale (GEMS), which focuses on induced emotions rather than expressed emotions. We were able to find only o... View full abstract»

This paper is aimed at presenting some general construction method of the hybrid plan controller for some task of temporal planning with preferences. This construction is multi-stage and it begins with a description of a chosen robot environment and its plan in some extended version of Linear Temporal Logic. This description is later transformed to the appropriate preferential Büchi automaton. In ... View full abstract»

Mood of music is considered as one of the most intuitive criteria for listeners, thus this work is focused on the emotional content of music and its automatic recognition. The research study presented in this work contains an attempt to music emotion recognition including audio parameterization and rough sets. A music set consisting of 154 excerpts from 10 music genres was evaluated in the listeni... View full abstract»

This paper describes a new approach to metaheuristic-based data clustering by means of Krill Herd Algorithm (KHA). In this work, KHA is used to find centres of the cluster groups. Moreover, the number of clusters is set up at the beginning of the procedure, and during the subsequent iterations of the optimization algorithm, particular solutions are evaluated by selected validity criteria. The prop... View full abstract»

Ensemble learning is being considered as one of the most well-established and efficient techniques in the contemporary machine learning. The key to the satisfactory performance of such combined models lies in the supplied base learners and selected combination strategy. In this paper we will focus on the former issue. Having classifiers that are of high individual quality and complementary to each... View full abstract»

In this article, the modified probabilistic neural network (MPNN) is proposed. The network is an extension of conventional PNN with the weight coefficients introduced between pattern and summation layer of the model. These weights are calculated by using the sensitivity analysis (SA) procedure. MPNN is employed to the classification tasks and its performance is assessed on the basis of prediction ... View full abstract»

This paper describes a method for spatial tracking of a strapdown device that can be used for design of human-computer interfaces. Inertial Measurement Unit (IMU) is used to obtain 6-dof position exploiting the so-called ZUPT technique by the means of the Kalman Filter. Additional corrections of position are done using magnetometer readings in the presence of static magnetic field induced by perma... View full abstract»

This paper presents a comparison of different machine learning algorithms applied to automatic sleep detection which uses electroencephalogram signals as a differentiating basis. The Single-Layer Perceptron, Multi-Layer Perceptron, Support Vector Machine, Boosted Tree and the Multi-Agent (comprising of the earlier models) models are developed and analyzed with training and testing datasets. The re... View full abstract»

This paper presents the analysis of potential of the Kosinski's Fuzzy Number (KFN) idea in the modeling trends of the processes which are described imprecisely. KFNs conception is an alternative for the classical fuzzy numbers ideas as model to represent of the imprecise quantitative data. They introduces new feature into vagueness of the information - a direction. It is base for good arithmetical... View full abstract»

In the paper issues related to the use of dispersed knowledge in medicine are discussed. The main aim of the article is to investigate the efficiency of inference of seven selected fusion methods in a dispersed decision-making system. The dispersed system was proposed by the author in previous papers. The examined fusion methods - the maximum rule, the minimum rule, the median rule, the sum rule, ... View full abstract»

Clustering is a task of grouping a set of objects in such a way that objects in the same group (called a cluster) are similar to each other and dissimilar to objects belonging to other groups (clusters). The article presents the idea of the hybrid Fuzzy Logic-Genetic Algorithm (FLGA) system that supports solving clustering problems. The Genetic Algorithm (GA) realizes the process of multi-objectiv... View full abstract»

In the paper, the deep evolving neural network and its learning algorithms (in batch and on-line mode) are proposed. The deep evolving neural network's architecture is developed based on GMDH approach (in J. Schmidhuber's opinion it is historically first system, which realizes deep learning ) and least squares support vector machines with fixed number of the synaptic weights, which provide high qu... View full abstract»

In this paper a convolutional neural network is applied to the problem of note onset detection in audio recordings. Two time-frequency representations are analysed, showing the superiority of standard spectrogram over enhanced autocorrelation (EAC) used as the input to the convolutional network. Experimental evaluation is based on a dataset containing 10,939 annotated onsets, with total duration o... View full abstract»

We present IQBEES, a novel prototype system for similar entity search by example on semantic knowledge graphs that is based on the concept of maximal aspects. The system makes it possible for the user to provide positive and negative relevance feedback to iteratively refine the information need. The maximal aspects model supports diversity-aware results. View full abstract»

In this paper are presented classification methods with use of two-dimensional three-state cellular automata. This methods are probabilistic forms of cellular automata rule modified from wide known almost deterministic rule designed by Fawcett. Fawcetts rule is modified into two proposed forms partially and fully probabilistic. The effectiveness of classifications of these three methods is analyse... View full abstract»