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The paper presents a new robust predictive speed controller with soft-switched controls. The proposed control structure is based on the predictive controller off-line calculated for different values of the unknown parameter. Then, depending on the parameter estimates soft switching approach follows between the MPC control laws. A preliminary point discusses the problems of motion control of the drive...
In this paper, we propose a novel method for control the formation of the autonomous robots following to the desired formations during tracking a moving target under the influence of the dynamic environment. The V-shape formation is used to track a moving target when the distance from this formation to the target is longer than the target approaching radius. Furthermore, when the leader moves in the...
One of the fast method for extracting head position from the camera image is the selection of face pixels with a skin color classifier. Regardless of the chosen model of such a classifier, the problem is to automatically calculate its optimal parameters and to obtain a short computation time. In this article a new grid-based method for clustering RGB space is proposed. It allows a significant reduction...
Multi-population-based bio-inspired computation may use migration among groups to increase the search diversity. Through good solutions exchanged among sub-populations, better solutions may be found with a high probability. In this paper, we propose two algorithms to dynamically adjust the two primary parameters, migration interval and migration rate, for flexibly reflect solution situation for effective...
The paper presents optimization of parameters of nonlinear dynamic ship steering model with one degree of freedom, in which the input is the commanded rudder angle and the output is the ship course. Optimization of parameters concerned the Bech and Wagner-Smith model for which the nonlinearity was determined from a standard Bech's reverse spiral test, whilst the parameters describing dynamic properties...
In the paper we present a method of reasoning with Horn rules within a contextual framework. We show that by proper use of a structure of contexts we can obtain partial OWA compliance with no necessity of extending the syntax of underlying Description Logics.
The idea presented in this paper is to gradually decrease the influence of selected training vectors on the model: if there is a higher probability that a given vector is an outlier, its influence on training the model should be limited. This approach can be used in two ways: in the input space (e.g. with such methods as k-NN for prediction and for instance selection) and in the output space (e.g...
Use of the information technology increases chances of adapting to changing environments. This applies to wild jungle as it applies to the urban information jungle. Modern wearable devices will allow to improve physical and augmented mental capabilities of humans. An interdisciplinary approach aimed at improving human mental processes is cognitive enhancement. There are many diverse methods in this...
In contemporary companies unstructured knowledge is essential, mainly due to the possibility to obtain better flexibility and competitiveness of the organization. For example, on the basis of automatic analysis of the experts' opinions, the decision-makers are capable of taking decisions (for example decisions concerning investments). This paper presents issues related to developing and evaluating...
Contemporary machine learning systems must be able to deal with ever-growing volumes of data. However, most of the canonical classifiers are not well-suited for big data analytics. This is especially vivid in case of distance-based classifiers, where their classification time is prohibitive. Recently, many methods for adapting nearest neighbour classifier for big data were proposed. We investigate...
Tool condition monitoring is in major focus nowadays in order to reduce production downtime due to breakdown maintenance, as timely detection of tool wear reduces the production cost. The paper provides an approach to monitor tool health for a CNC turning process using airborne acoustic emission and a PSO (Particle Swarm Optimization) optimized back-propagation neural network. Acoustic signals for...
The paper proposes a global optimization approach to the network resource allocation problem, where the objective is to maximize the overall data flow through a shared network. In the proposed approach, the utility functions of agents may have different forms, which allows a more realistic modeling of phenomena occurring in computer networks. To solve the optimization problem, a modified gradient...
There are few Chinese dish recommendation algorithms due to the variety of Chinese dishes. It could be impossible to find one's most liked dishes in a restaurant through the name or the ingredients of a dish. The algorithm in this paper uses the user's ordering history to quantify one's taste by k-means clustering method and determines the number of user's favorite tastes by the BWP index. With the...
Managing Security is a complex process and existing research in the field of cybersecurity metrics provide limited insight into understanding the impact attacks have on the overall security goals of an enterprise. We need a new generation of metrics that can enable enterprises to react even faster in order to properly protect mission-critical systems in the midst of both undiscovered and disclosed...
We present PharmaGuard, a novel system for the automatic discovery of illegal online pharmacies, aimed at assisting law-enforcement toward their early identification, blacklisting and shutdown. Given a previously labelled set of examples, the system is able to learn a profile of (illegal) pharmacies, and then exploit it to discover never-before-seen instances indexed by popular web search engines...
Recently, researchers have discovered that there are non-invasive ways to detect Diabetes Mellitus based on the analysis of human facial blocks. Even though a few algorithms have been developed to detect Diabetes Mellitus based on facial feature analysis, Diabetes Mellitus detection remains a challenging problem. In this paper, we propose two algorithms to detect Diabetes Mellitus through the analysis...
Contextual processing is a great challenge for information retrieval study - the most approved techniques include scanning content of HTML web pages, user supported metadata analysis, automatic inference grounded on knowledge base, or content-oriented digital documents analysis. We propose a meta-heuristic by making use of Genetic Algorithms for Contextual Search (GACS) built on genetic programming...
Time series forecasting is a widely and important research area in signal processing and machine learning. With the development of the artificial intelligence (AI), more and more AI technologies are used in time series forecasting. Multi-layer network structure has been widely used for forecasting problems. In this paper, based on a data-driven and adaptive method, extrema mean empirical mode decomposition,...
Transient departure process of outgoing packets in a finite-buffer queueing model with the BMAP-type input stream and generally distributed processing times is investigated. Applying the paradigm of embedded Markov chain and the total probability law, a system of integral equations for the distribution function of the number of packets successfully processed up to fixed time t; conditioned by the...
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