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Search results for: BAG-OF-WORDS, DOCUMENT CATEGORIZATION, NEURAL NETWORKS, TEXT CLASSIFICATION, TEXT REPRESENTATION, WIKIPEDIA, WORD EMBEDDINGS
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INFLUENCE OF A VERTEX REMOVING ON THE CONNECTED DOMINATION NUMBER – APPLICATION TO AD-HOC WIRELESS NETWORKS
PublicationA minimum connected dominating set (MCDS) can be used as virtual backbone in ad-hoc wireless networks for efficient routing and broadcasting tasks. To find the MCDS is an NP- complete problem even in unit disk graphs. Many suboptimal algorithms are reported in the literature to find the MCDS using local information instead to use global network knowledge, achieving an important reduction in complexity. Since a wireless network...
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Otopy Classification of Gradient Compact Perturbations of Identity in Hilbert Space
PublicationWe prove that the inclusion of the space of gradient local maps into the space of all local maps from Hilbert space to itself induces a bijection between the sets of the respective otopy classes of these maps, where by a local map we mean a compact perturbation of identity with a compact preimage of zero.
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Business angels in the Czech Republic: characteristics and a classification with policy implications
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Supervised Classification Problems–Taxonomy of Dimensions and Notation for Problems Identification
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Expert system for automatic classification and quality assessment of singing voices
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Assessment of sources of uncertainty in macrophyte surveys and the consequences for river classification
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Do we need a new classification of parotid gland surgery?
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Classification of different type of propeller ventilation and ventilation inception mechanism
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Classification of different type of propeller ventilation and ventilation inception mechanism
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Human adenylate kinases – classification, structure, physiological and pathological importance
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An approach to machine classification based on stacked generalization and instance selection
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Role of various parametres in automatic classification of musical instrument sound.
PublicationArtkuł dotyczy problemu automatycznej klasyfikacji dźwięków instrumentów muzycznych, w tym głównie wpływu indywidualnych parametrów na proces automatycznego rozpoznawania instrumentów. Parametryzacja wykorzystuje wdirmo Fourierowskie i analizę czasową dźwięków do formowania 14 i 62-parametrowych wektorów cech dystynktywnych. Autorzy porównują jakość rozpoznawania i rozróźnialność instrumentów. Przy ocenach tego typu stosowano drzewa...
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Expert system for automatic classification and quality assessment of singing voices
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Rough set based automatic classification of musical instrument sound
PublicationReferat dotyczy problemu automatycznego rozpoznawania instrumentów muzycznych rozwiązywanego z zastosowaniem, inteligentnych algorytmów decyzyjnych. Wnioski zawarte w referacie dotyczą reprezentacji sygnałów muzycznych, która jest przydatna w procesie automatycznej klasyfikacji instrumentów.
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Electronic noses in classification and quality control of edible oils: A review
PublicationThe growing demand for wholesome and nutritious food leads to intensification of production, which in turn can have a detrimental effect on quality and well-being of consumers. For that reason, it is important to develop novel methods of food control which would be characterized by a short time of analysis, adequate sensitivity and relatively low cost. One such technique involves the use of multi-sensory devices called electronic...
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Meat freshness classification using ultra-fast gas chromatography
PublicationMeat constitutes an important component of human diet. In order to ensure that it is safe to consume, it is important to be able to determine whether a particular sample is fresh. To this end, an analysis of the headspace of pork, beef, and poultrywas performed over a period of seven days using ultra-fast gas chromatography. Compounds that may possibly be used as indicators of spoilage were identified. Based on the obtained results...
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Basic evaluation of limb exercises based on electromyography and classification methods
PublicationSymptoms caused by cerebral palsy or stroke deprive a person partially or even completely of his ability to move. Nowadays we can observe more technologically advanced rehabilitation devices which incorporate biofeedback into the process of rehabilitation of such people. However, there is still a lack of devices that would analyse, assess, and control (independently or with limited support) specialised movement exercises. Here...
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Neural-Network-Based Parameter Estimations of Induction Motors
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Neural Manoeuvre Detection of the Tracked Target in ARPA Systems
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Cellular neural network application to moire pattern filtering
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Adaptive neural voltage controller with tunable activation gain
PublicationW artykule przedstawiono model adaptacyjnego neuronowego regulatora napięcia dla turbogeneratora z nastrojonym współczynnikiem wzmocnienia funkcji przynależności. Ten model jest kombinacją klasycznego neuronowego modelu i neuronowego modelu z współczynnikiem wzmocnienia funkcji przynależności zależnym od warunków pracy obiektu.Przedstawiono, także wyniki symulacji mające na celu badania efektywności proponowanego regulatora dla...
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Neural Network - Based Parameters Estimations Of Induction Motors
PublicationW artykule przedstwaiono algorytmy estymacji rezystancji wirnika i indukcyjności wzajemnej w zamkniętym układzie sterowania prędkości silnika indukcyjnego klatkowego. Do wyznaczenia rezystancji wykorzystano algorytm oparty na porównaniu modelu napięciowego i prądowego silnika. Do wyznaczania indukcyjności wykorzystano, znaną z literatury, zależność modelu multiskalarnego. Wyznaczane w stanie ustalonym parametry zapisywane są w...
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Automatic Image and Speech Recognition Based on Neural Network
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Comparative study of methods for artificial neural network training.
PublicationPrzedstawiono wyniki badań porównawczych następujących metod uczenia sieci neuronowych: propagacji wstecznej błędów, rekursywnej metody najmniejszych kwadratów, metody Zangwill'a i algorytmów ewolucyjnych. Badania dotyczyły projektowania adaptacyjnego regulatora neuronowego napięcia generatora synchronicznego.
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Neural network breast cancer relapse time prognosis
PublicationPrzedstawiono architekturę i wyniki testowania sztucznej sieci neuronowej w prognozowaniu czasu nawrotu choroby u kobiet chorych na raka piersi. Sieć neuronowa uczona była na danych zgromadzonych przez 20 lat. Dane opisują grupę 439 pacjentów za pomocą 40 parametrów. Spośród tych parametrów wybrano 6 najistotniejszych: liczbę przerzutowych węzłów chłonnych, wielkość guza, wiek, skalę według Blooma oraz stan receptorów estrogenowych...
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On the Usefulness of the Generalised Additive Model for Mean Path Loss Estimation in Body Area Networks
PublicationIn this article, the usefulness of the Generalised Additive Model for mean path loss estimation in Body Area Networks is investigated. The research concerns a narrow-band indoor off-body network operating at 2.45 GHz, being based on measurements performed with four different users. The mean path loss is modelled as a sum of four components that depend on path length, antenna orientation angle, absolute difference between transmitting...
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Long-distance quantum communication over noisy networks without long-time quantum memory
PublicationThe problem of sharing entanglement over large distances is crucial for implementations of quantum cryptography. A possible scheme for long-distance entanglement sharing and quantum communication exploits networks whose nodes share Einstein-Podolsky-Rosen (EPR) pairs. In Perseguers et al. [Phys. Rev. A 78, 062324 (2008)] the authors put forward an important isomorphism between storing quantum information in a dimension D and transmission...
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The Idea of Using Bayesian Networks in Forecasting Impact of Traffic-Induced Vibrations Transmitted through the Ground on Residential Buildings
PublicationTraffic–induced vibrations may constitute a considerable load to buildings. In this paper, vibrations transmitted through the ground caused by wheeled vehicles are considered. This phenomenon may cause cracking of plaster, cracks in load-bearing elements or even, in extreme cases, collapse of the whole structure. Measurements of vibrations of real structures are costly and laborious. Therefore, the aim of the present paper is to...
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An Off-Body Narrowband and Ultra-Wide Band Channel Model for Body Area Networks in a Ferryboat Environment
PublicationIn the article an off-body narrowband and ultra-wide band channel model for body area networks in a ferryboat environment is described. Considering the limited number of publications there is a need to develop an off-body channel model, which will facilitate the design of radio links, both from the multimedia services provider and the security point of view, for body area networks in this atypical environment. A mobile heterogeneous...
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Evidence-Based Risk Management for Civil Engineering Projects Using Bayesian Belief Networks (BBN)
PublicationThe authors are seeking new methods for improving the efficiency of the investments associated with the maintenance and operation of existing civil engineering structures. It is demonstrated how the knowledge about the elements of construction and operation phases and their relationships, combined with monitoring data can be used for more effective management of the risks associated with civil engineering projects. The methodology...
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Michał Hoeft dr inż.
PeopleMichał Hoeft graduated with distinction form Gdansk University of Technology (GUT), Gdansk, Poland in 2011. His main areas of research interest contain: effective mobility management and handover optimisation in 802.11 networks. Michał Hoeft has been involved in major communication-oriented projects including the EU-funded Polish Future Internet Engineering initiative, PL-LAB2020 and netBaltic projects. He has served as a reviewer...
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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublicationFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
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Persistences: analysis of the image of Gdańsk and its cultural identity through survey processes and digital architectural representation
PublicationThe aim of the research was to analyse the historical legacy/heritage of the city of Gdańsk in order to characterise the narrative tools which can be used to promote the cultural identity of the urban landscape. The main focus was on the city's defence system - a cultural route that is spatially limited to a relatively small area, but temporally spanning almost a millennium. The fortifications demarcate a spatial boundary, limiting...
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Average Size of a Suffix Tree for Markov Sources
PublicationWe study a suffix tree built from a sequence generated by a Markovian source. Such sources are more realistic probabilistic models for text generation, data compression, molecular applications, and so forth. We prove that the average size of such a suffix tree is asymptotically equivalent to the average size of a trie built over n independentsequences from the same Markovian source. This equivalenceis only known for memoryless...
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Mutual Coupling Reduction in Antenna Arrays Using Artificial Intelligence Approach and Inverse Neural Network Surrogates
PublicationThis paper presents a novel approach to reduce undesirable coupling in antenna arrays using custom-designed resonators and inverse surrogate modeling. To illustrate the concept, two stand-ard patch antenna cells with 0.07λ edge-to-edge distance are designed and fabricated to operate at 2.45 GHz. A stepped-impedance resonator is applied between the antennas to suppress their mutual coupling. For the first time, the optimum values...
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Towards classification of patients based on surface EMG data of temporomandibular joint muscles using self-organising maps
PublicationThe study considers the need for an effective method of classification of patients with a temporomandibular joint disorder (TMD). The self-organising map method (SOM) was applied to group patients and used together with the cross-correlation approach to interpret the processed (rectified and smoothed by using root mean square (RMS) algorithm) surface electromyography signal (sEMG) obtained from testing the muscles (two temporal...
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Using LSTM networks to predict engine condition on large scale data processing framework
PublicationAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
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Time Synchronization between the eNBs in E-UTRAN under the Asymmetric IP Network
PublicationIn this paper, we present a method for a time synchronization between the two eNodeBs (eNBs) in E-UTRAN (Evolved Universal Terrestrial Radio Access) network. The...
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Previous Opinions is All You Need - Legal Information Retrieval System
PublicationWe present a system for retrieving the most relevant legal opinions to a given legal case or question. To this end, we checked several state-of-the-art neural language models. As a training and testing data, we use tens of thousands of legal cases as question-opinion pairs. Text data has been subjected to advanced pre-processing adapted to the specifics of the legal domain. We empirically chose the BERT-based HerBERT model to perform...
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Design, Realization and Measurements of Enhanced Performance 2.4 GHz ESPAR Antenna for Localization in Wireless Sensor Networks
PublicationThis paper presents the design, realization and measurements of an Electronically Steerable Parasitic Array Radiator (ESPAR) antenna with enhanced performance of estimating the incoming signal direction. Designed antenna is dedicated for 2.4 GHz ISM applications with emphasis on Wireless Sensor Networks (WSN). Proposed antenna provides different radiation patterns by proper configuration of the parasitic elements. Thus, several...
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Social networks as a context for small business? A new look at an enterprise in the context of a smallness and newness liability syndrome
PublicationIn this paper we aim to propose and outline key ingredients to a small enterprise success, emerging from the social capital of small business owner-managers and their business networks. We employ resource based view of an organization as well as an embeddedness perspective along with new approach transaction costs to outline the pillars of an advantage of a small business entity. The analysis of survey data leads us to conclusion,...
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Comparison of 3D Point Cloud Completion Networks for High Altitude Lidar Scans of Buildings
PublicationHigh altitude lidar scans allow for rapid acquisition of big spatial data representing entire city blocks. Unfortunately, the raw point clouds acquired by this method are largely incomplete due to object occlusions and restrictions in scanning angles and sensor resolution, which can negatively affect the obtained results. In recent years, many new solutions for 3D point cloud completion have been created and tested on various objects;...
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Evolving gene regulatory networks controlling foraging strategies of prey and predators in an artificial ecosystem
PublicationCo-evolution of predators and prey is an example of an evolutionary arms race, leading in nature to selective pressures in positive feedback. We introduce here an artificial life ecosystem in which such positive feedback can emerge. This ecosystem consists of a 2-dimensional liquid environment and animats controlled by evolving artificial gene regulatory networks encoded in linear genomes. The genes in the genome encode chemical...
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Improved RSS-Based DoA Estimation Accuracy in Low-Profile ESPAR Antenna Using SVM Approach
PublicationIn this paper, we have shown how the overall performance of direction-of-arrival (DoA) estimation using lowprofile electronically steerable parasitic array radiator (ESPAR) antenna, which has been proposed for Internet of Things (IoT) applications, can significantly be improved when support vector machine (SVM) approach is applied. Because the SVM-based DoA estimation method used herein relies solely...
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Australian Conference on Neural Networks
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International Symposium on Neural Networks
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World Congress on Neural Networks
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Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublicationIn the article, the fast fading influence on the proposed DL (Deep Learning) approach for LOS (Line-of-Sight) and NLOS (Non-Line-of-Sight) conditions identification in Wireless Body Area Networks is investigated. The research was conducted on the basis of the off-body communication measurements using the developed mobile measurement stand, in an indoor environment for both static and dynamic scenarios. The measurements involved...
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Investigation of Continuous Wave Jamming in an IEEE 802.15.4 Network
PublicationThis paper presents how continuous wave jamming affects IEEE 802.15.4 network. To this end, an office-based measurement setup has been proposed. Within the measurement area, 25 nodes have been set up in order to create a IEEE 802.15.4 tree-based test network structure. A dedicated jamming device that generates and transmits a continuous wave signal has been developed. Several tests have been conducted and presented to demonstrate...
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An Approach to Imbalanced Data Classification Based on Instance Selection and Over-Sampling
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