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The usage of Unmanned Aerial Vehicles (UAVs) is increasing day by day. In recent years, UAVs are being used in increasing number of civil applications, such as policing, fire-fighting, etc in addition to military applications. Instead of using one large UAV, multiple UAVs are nowadays used for higher coverage area and accuracy. Therefore, networking models are required to allow two or more UAV nodes...
In the twenty years from first grade to a PhD, students never learn any subject by the methods for which machine-learning algorithms have been designed. Those algorithms are useful for analyzing large volumes of data. But they don't enable a computer system to learn a language as quickly and accurately as a three-year-old child. They're not even as effective as a mother raccoon teaching her babies...
Recurrent drift, as a specific type of concept drift, is characterised by the appearance of previously seen concepts. Therefore, in those cases the learning process could be saved or at least minimized by applying an already trained classification model. In this paper we propose Fuzzy-Rec, a framework that is able to deal with recurrent concept drifts by means of a repository of classification models...
Decision tree is a widely used technique to discover patterns from consistent data set. But if the data set is inconsistent, where there are groups of examples (objects) with equal values of conditional attributes but different decisions (values of the decision attribute), then to discover the essential patterns or knowledge from the data set is challenging. We consider three approaches (generalized,...
Two algorithms for building classification trees, based on Tsallis and Rényi entropy, are proposed and applied to customer churn problem. The dataset for modeling represents highly unbalanced proportion of two classes, which is often found in real world applications, and may cause negative effects on classification performance of the algorithms. The quality measures for obtained trees are compared...
Equality is fundamental notion of logic and mathematics as a whole. If computer-supported formalization of knowledge is taken into account, sooner or later one should precisely declare the intended meaning/interpretation of the primitive predicate symbol of equality. In the paper we draw some issues how computerized proof-assistants can deal with this notion, and at the same time, we propose solutions,...
Cognitive radio (CR) technology has emerged as a promising solution to many wireless communication problems including spectrum scarcity and underutilization. To enhance the selection of channel with less noise among the white spaces (idle channels), the a priory knowledge of Radio Frequency (RF) power is very important. Computational Intelligence (CI) techniques cans be applied to these scenarios...
This paper presents the DISESOR integrated decision support system. The system integrates data from different monitoring and dispatching systems and contains such modules as data preparation and cleaning, analytical, prediction and expert system. Architecture of the system is presented in the paper and a special focus is put on the presentation of two issues: data integration and cleaning, and creation...
This paper concerns the design and physical construction of an emotion monitor stand for tracking human emotions in Human-Computer Interaction using multi-modal approach. The concept of the stand using cameras, behavioral analysis tools and a set of physiological sensors such as galvanic skin response, blood-volume pulse, temperature, breath and electromyography is presented and followed by details...
The idea of the Pawlak's flow graphs is applicable to many problems in various fields related to decision algorithms or data mining. The flow graphs can be used also in the video surveillance systems. Especially in distributed multi-camera systems which are problematic to be handled by human operators because of their limited perception. In such systems automated video analysis needs to be implemented...
We use higher-order, type-theoretic Situation Theory to model semantic concepts as situation-theoretic objects consisting of parametric information. Situation Theory contributes by representing concepts as classes of parametric objects, in a computational way. We use concepts that are often expressed by human language in taxonomy classifications, as a demonstration of the situation theoretic-approach...
This paper summarizes our approach and experimental evaluation of infrastructure-based Indoor Positioning System (IPS) designed to be used by First Responders. We are using 868 MHz single channel, power-efficient radio markers and RSSI (Receiver Signal Strength Indicator) fingerprinting. Artificial Neural Network translates vectors of RSSI constructed using mobile units into position. Special preprocessing...
The paper presents the results of research related to the efficiency of the so called rule quality measures which are used to evaluate the quality of rules at each stage of the rule induction. The stages of rule growing and pruning were considered along with the issue of conflicts resolution which may occur during the classification. The work is the continuation of research on the efficiency of quality...
In this paper, we define a new practical technology-driven Resource Constrained Scheduling Problem (t-RCPSP). We propose three approaches, applying constructive heuristics to tackle effectively the practical application of RCPSP. In the RCPSP formulation, the constraints are defined to design the tasks in the spaces constructed by non- and renewable resources, without violating the precedence relationships...
In this paper novel project scheduling difficulty estimations are proposed for Multi-Skill Resource-Constrained Project Scheduling Problem (MS-RCPSP). The main goal of introducing the complexity estimations is an attempt of estimation the project complexity before launching the optimization process. What is more, the dataset instance generator is also presented as a tool to create new instances for...
The goal of this paper is to describe the approach for automatic identifying human organs from a medical CT images and discuss results of its comparison to different classification methods. The main premise of this approach is the use of data sets together with the relevant domain knowledge. We test our approach on multiple CT images of chest organs (trachea, lungs, bronchus) and demonstrate usefulness...
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