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Wyniki wyszukiwania dla: ELECTRONICALLY STEERABLE PARASITIC ARRAY RADIATOR (ESPAR) ANTENNA, RECEIVED SIGNAL STRENGTH (RSS), SUPPORT VECTOR MACHINE (SVM), SWITCHED-BEAM ANTENNA
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Implementation of Haar wavelet, higher order Haar wavelet, and differential quadrature methods on buckling response of strain gradient nonlocal beam embedded in an elastic medium
PublikacjaThe present investigation is focused on the buckling behavior of strain gradient nonlocal beam embedded in Winkler elastic foundation. The first-order strain gradient model has been combined with the Euler–Bernoulli beam theory to formulate the proposed model using Hamilton’s principle. Three numerically efficient methods, namely Haar wavelet method (HWM), higher order Haar wavelet method (HOHWM), and differential quadrature method...
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublikacjaThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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Supply current signal and artificial neural networks in the induction motor bearings diagnostics
PublikacjaThis paper contains research results of the diagnostics of induction motor bearings based on measurement of the supply current with usage of artificial neural networks. Bearing failure amount is greater than 40% of all engine failures, which makes their damage-free operation crucial. Tests were performed on motors with intentionally made bearings defects. Chapter 2 introduces the concept of artificial neural networks. It presents...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublikacjaThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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A demand for innovation support in samll and medium-sized enterprises in the baltic sea region
Publikacjathe aim of the expertise is to analyze the actual demand of smes from the baltic sea region for innovation support. the results of the conducted study can help formulate recommendations designed to increase innovation and competitiveness of smes in the baltic sea region in the future. research activities of this study include: the evaluation of innovation level of the baltic sea region enterprises (type and intensity of implemented...
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Plastic Debris in the Stomach of the Invasive Signal Crayfish Pacifastacus leniusculus from a Baltic Coastal River
PublikacjaPollution by plastic debris, widely recognized as a growing global problem [1-3] is caused by the production of synthetic polymers. Over recent years, the production of plastics has increased, while in Europe, fossil-based plastics production has decreased, and recycled plastics production has increased [4]. There are different types of plastics. Some types of plastic ingredients, applied in a wide variety of cosmetics and personal...
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Navigational decision support system during approach manoeuvre in emergency STS transfer operation
PublikacjaThe paper is concerned with the problem of safe trajectory planning for approaching during emergency STS (Ship to Ship) transfer operation with oil spill. The safe trajectory means that the way points does not cross in the area of the environment with the static and dynamic obstacles and at the same time satisfies ship's stopping and speed deceleration performance. The evolutionary path planning algorithm is used to determine trajectory...
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublikacjaSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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Comparative analysis of spectral and cepstral feature extraction techniques for phoneme modelling
PublikacjaPhoneme parameter extraction framework based on spectral and cepstral parameters is proposed. Using this framework, the phoneme signal is divided into frames and Hamming window is used. The performances are evaluated for recognition of Lithuanian vowel and semivowel phonemes. Different feature sets without noise as well as at different level of noise are considered. Two classical machine learning methods (Naive Bayes and Support...
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THE EFFECT OF ALTERNATIVE CUTTER PATHS ON FLATNESS DEVIATIONS IN THE FACE MILLING OF ALUMINUM PLATE PARTS
PublikacjaIn this paper the relationships between the alternative machining paths and flatness deviations of the aluminum plate part, were presented. The flatness tolerance of the main surface of the plate part has crucial meaning due to the assembly requirement of piezoelectric elements on the radiator. The aluminum bodies under investigation are the base part of the radiators with crimped feathers for the train industry. The surface of...