Wyniki wyszukiwania dla: communiation networks

• Using Long-Short term Memory networks with Genetic Algorithm to predict engine condition

  Publikacja

  • S. Erpolat Tasabat
  • O. Aydin

  - Gazi University Journal of Science - Rok 2022

  Predictive maintenance (PdM) is a type of approach for maintenance processes, allowing maintenance actions to be managed depending on the machine's current condition. Maintenance is therefore carried out before failures occur. The approach doesn’t only help avoid abrupt failures but also helps lower maintenance cost and provides possibilities to manufacturers to manage maintenance budgets in a more efficient way. A new deep neural...

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• Effects of UV light irradiation on fluctuation enhanced gas sensing by carbon nanotube networks

  Publikacja

  • K. Drozdowska
  • A. Rehman
  • A. Krajewska
  • D. V. Lioubtchenko
  • K. Pavłov
  • S. Rumyantsev
  • J. Smulko
  • G. Cywiński

  - SENSORS AND ACTUATORS B-CHEMICAL - Rok 2022

  The exceptionally large active surface-to-volume ratio of carbon nanotubes makes it an appealing candidate for gas sensing applications. Here, we studied the DC and low-frequency noise characteristics of a randomly oriented network of carbon nanotubes under NO2 gas atmosphere at two different wavelengths of the UV light-emitting diodes. The UV irradiation allowed to sense lower concentrations of NO2 (at least 1 ppm) compared to...

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• New Alternative Passive Networks to Improve the Range Output Voltage Regulation of the PWM Inverters

  Publikacja

  • R. Strzelecki
  • W. Bury
  • M. Adamowicz
  • N. Strzelecka

  - Rok 2009

  This paper presents different topologies of buck-boost converters with passive input networks that have alternative topologies; this is known in the literature as a Z-source inverter. Alternative passive networks were named by the authors as T-inverters; these improve output voltage regulation of the PWM inverters. T-inverter has fewer reactive components in comparison to conventional Z-source inverter. The most significant advantage...

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• Performance Evaluation of GAM in Off-Body Path Loss Modelling for Body Area Networks

  Publikacja

  • M. Laskowski
  • S. J. Ambroziak
  • L. M. Correia
  • K. Świder

  - Rok 2021

  This paper addresses the performance evaluation of an off-body path loss model, based on measurements at 2.45 GHz, which has been developed with the use of the Generalised Additive Model, allowing to model a non-linear dependence on different predictor variables. The model formulates path loss as a function of distance, antennas’ heights, antenna orientation angle and polarisation, results showing that performance is very sensitive...

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• Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks

  Publikacja

  • S. Kozieł
  • N. Calik
  • P. Mahouti
  • M. Belen

  - IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION - Rok 2022

  The importance of surrogate modeling techniques has been gradually increasing in the design of antenna structures over the recent years. Perhaps the most important reason is a high cost of full-wave electromagnetic (EM) analysis of antenna systems. Although imperative in ensuring evaluation reliability, it entails considerable computational expenses. These are especially pronounced when carrying out EM-driven design tasks such...

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• The influence of azide and imidazole on the properties of Mn- and Cd-based networks: conductivity and nonlinear phenomena

  Publikacja

  • M. Trzebiatowska
  • D. A. Kowalska
  • A. Ciżman
  • N. A. Wójcik
  • R. J. Barczyński
  • A. Pikul
  • J. K. Zaręba
  • M. Palewicz
  • T. Piasecki
  • K. Roleder... i 2 innych

  - Journal of Materials Chemistry C - Rok 2024

  We report a study on a family of four new Mn- and Cd-azide-imidazolate-based compounds with various crystal architectures. Notably, three of these compounds display noncentrosymmetric crystal arrangements at room temperature, a rare phenomenon in hybrid organic–inorganic materials. Both nonlinear optical (NLO) and electrical phenomena in these compounds are observed. The NLO processes include second and third harmonic generation,...

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• Detecting Objects of Various Categories in Optical Remote Sensing Imagery Using Neural Networks

  Publikacja

  • A. Madajczak
  • M. Ciecholewski

  - Rok 2024

  The effective detection of objects in remote sensing images is of great research importance, so recent years have seen a significant progress in deep learning techniques in this field. However, despite much valuable research being conducted, many challenges still remain. A lot of research projects focus on detecting objects of a single category (class), while correctly detecting objects of different categories is much harder. The...

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• Session-Based Recommendation with Graph Neural Networks with an Examination of the Impact of Local and Global Vectors

  Publikacja

  • J. Głogowska
  • D. Kobiela
  • S. Mielewczyk

  - Rok 2024

  This study investigates the application of graph neural networks (GNN) in session-based recommendation systems (SR), focusing on a key modification involving the use of a global vector. Session-based recommendation systems often face challenges in accurately capturing user behavior due to the limited data available within individual sessions. The SR-GNN model, originally designed for automatic feature extraction from session graphs...

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• Classification of Glacial and Fluvioglacial Landforms by Convolutional Neural Networks Using a Digital Elevation Model

  Publikacja

  • P. Nadachowski
  • Z. Łubniewski
  • A. Malecha-Łysakowska
  • K. Trzcińska
  • R. Wróblewski
  • J. Tęgowski

  - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing - Rok 2024

  The rise of artificial neural networks (ANNs) has revolutionized various fields of research, demonstrating their effectiveness in solving complex problems. However, there are still unexplored areas where the application of neural networks, particularly convolutional neural network (CNN) models, has yet to be explored. One area is where the application of ANNs is even expected is geomorphology. One of the tasks of geomorphology...

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• Comparison of 3D Point Cloud Completion Networks for High Altitude Lidar Scans of Buildings

  Publikacja

  • M. Kulawiak

  - PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING - Rok 2024

  High 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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• A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks

  Publikacja

  • J. Sadowski
  • J. Stefański

  - SENSORS - Rok 2024

  This article proposes the use of a feedforward neural network (FNN) to select the starting point for the first iteration in well-known iterative location estimation algorithms, with the research objective of finding the minimum size of a neural network that allows iterative position estimation algorithms to converge in an example positioning network. The selected algorithms for iterative position estimation, the structure of the...

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• On reducing the value of aggregate restoration time when assuring survivability in scale-free networks.

  Publikacja

  • T. Gierszewski
  • J. Rak

  - Rok 2004

  Referat dotyczy zapewniania przeżywalności połączeń w rozległych sieciach bezskalowych. Zaproponowano metrykę pozwalającą omijać centra sieci, a tym samym zmniejszać ilość połączeń wymagających odtwarzania na skutek awarii węzła. Wyniki dla sieci bezskalowych porównywane są z wynikami dla sieci losowych. Uzyskane wyniki potwierdzają efektywność metryki w sieciach bezskalowych.

• Application of artificial neural networks (ANN) as multiple degradation classifiers in thermal and flow diagnostics

  Publikacja

  • J. Głuch

  - Rok 2005

  Przedyskutowano problem zwiększenia dokładności rozpoznawania wielokrotnych degradacji eksploatacyjnych urządzeń składowych dużych obiektów energetycznych. Zastosowani sieć neuronową (SSN) o skokowych funkcjach przejścia. Sprawdzono możliwości przyspieszenia treningu sieci neuronowych. Zastosowano modułową metodę budowy SSN, polegającą na dedykowaniu pojedynczej sieci do rozpoznawania tylko jednego typu degradacji.

• Accidental wow defect evaluation using sinusoidal analysis enhanced by artificial neural networks

  Publikacja

  • A. Czyżewski
  • B. Kostek
  • P. Maziewski
  • Ł. Litwic

  - Rok 2006

  Artykuł przedstawia metodę do wyznaczania charakterystyki pasożytniczych modulacji częstotliwości (kołysanie) obecnych w archiwalnych nagraniach dźwiękowych. Prezentowane podejście wykorzystuje śledzenie zmian sinusoidalnych komponentów dźwięku które odzwierciedlają przebieg kołysania. Analiza sinusoidalna wykorzystana jest do ekstrakcji składowych tonalnych ze zniekształconych nagrań dźwiękowych. Dodatkowo, w celu zwiększenia...

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• A Highly Scalable, Modular Architecture for Computer Aided Assessment e-Learning Systems

  Publikacja

  • K. Gierłowski
  • K. Nowicki

  - Rok 2011

  In this chapter, the authors propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. The authors' research proved that such architecture, while well suited for didactic content distribution systems is ill-suited for knowledge...

• A taxonomy of challenges to resilient message dissemination in VANETs

  Publikacja

  • J. Rak
  • M. Jonsson
  • A. Vinel

  - Rok 2016

  Inter-vehicular communications is seen as a promising solution to a number of issues related with public road safety, road congestion management, and infotainment. However, Vehicular Ad-hoc NETworks (VANETs) characterized by high mobility of vehicles and facing a number of other issues related with high frequency wireless communications and network disconnections, encounter major challenges related with reliability of message delivery....

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• Disciplines and measures of information resilience

  Publikacja

  • J. Rak
  • M. Jonsson
  • D. Hutchison
  • J. Sterbenz

  - Rok 2017

  Communication networks have become a fundamental part of many critical infrastructures, playing an important role in information delivery in various failure scenarios triggered e.g., by forces of nature (including earthquakes, tornados, fires, etc.), technology-related disasters (for instance due to power blackout), or malicious human activities. A number of recovery schemes have been defined in the context of network resilience...

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• COMMUNICATIONS IN CONTEMPORARY MATHEMATICS

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  ISSN: 0219-1997 , eISSN: 1793-6683

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• Image Processing & Communications

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• COMPUTER PHYSICS COMMUNICATIONS

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• Communications in Computational Physics

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• COMMUNICATIONS IN MATHEMATICAL PHYSICS

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• WIRELESS PERSONAL COMMUNICATIONS

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• COMMUNICATIONS IN THEORETICAL PHYSICS

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• ELECTRONIC COMMUNICATIONS IN PROBABILITY

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• Communications in Information Literacy

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• Journal of Marketing Communications

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• Communications in Mathematics and Statistics

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• WSEAS Transactions on Communications

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• Acta Neuropathologica Communications

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• Communications in Applied Analysis

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• Howard Journal of Communications

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