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Search results for: FASTER REGION BASED CONVOLUTIONAL NEURAL NETWORK
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Taking decisions in the diagnostic intelligent systems on the basis information from an artificial neural network
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Dataset Related Experimental Investigation of Chess Position Evaluation Using a Deep Neural Network
PublicationThe idea of training Articial Neural Networks to evaluate chess positions has been widely explored in the last ten years. In this paper we investigated dataset impact on chess position evaluation. We created two datasets with over 1.6 million unique chess positions each. In one of those we also included randomly generated positions resulting from consideration of potentially unpredictable chess moves. Each position was evaluated...
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Fetal Brain Imaging: A Composite Neural Network Approach for Keyframe Detection in Ultrasound Videos
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An application of neural network for Structural Health Monitoring of an adaptive wing with an array of FBG sensors
PublicationW pracy przedstwiono możliwości zastoswania sieci czujników FBG i sztucznych sieci neuronowych do detekcji uszkodzeń w poszyciu adaptacyjnego skrzydła.
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Towards Designing an Innovative Industrial Fan: Developing Regression and Neural Models Based on Remote Mass Measurements
PublicationThis article presents the process of the construction and testing a remote, fully autonomous system for measuring the operational parameters of fans. The measurement results obtained made it possible to create and verify mathematical models using linear regression and neural networks. The process was implemented as part of the first stage of an innovative project. The article presents detailed steps of constructing a system to...
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Comparison of tuning procedures based on evolutionary algorithm for multi-region fuzzy-logic PID controller for non-linear plant
PublicationThe paper presents a comparison of tuning procedures for a multi-region fuzzy-logic controller used for nonlinear process control. This controller is composed of local PID controllers and fuzzy-logic mechanism that aggregates local control signals. Three off-line tuning procedures are presented. The first one focuses on separate tuning of local PID controllers gains in the case when the parameters of membership functions of fuzzy-logic...
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Modified Inductive Multi-Coil Wireless Power Transfer Approach Based On Z-Source Network
PublicationThis article presents a non-conventional approach to a multi-coil wireless power transfer system based on a Z-source network. The novelty of the approach lies in the use of a Z-source as a voltage source for energy transmission through the wireless power transfer coils. The main advantage is in a reduced number of semiconductors. This paper provides the design approach, simulation and experimental study. Feasibility and possible...
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Wind-wave variability in a shallow tidal sea—Spectral modelling combined with neural network methods
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Performance and Energy Aware Training of a Deep Neural Network in a Multi-GPU Environment with Power Capping
PublicationIn this paper we demonstrate that it is possible to obtain considerable improvement of performance and energy aware metrics for training of deep neural networks using a modern parallel multi-GPU system, by enforcing selected, non-default power caps on the GPUs. We measure the power and energy consumption of the whole node using a professional, certified hardware power meter. For a high performance workstation with 8 GPUs, we were...
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Neural network simulator's application to reference performance determination of turbine blading in the heat-flow diagnostics.
PublicationIn the paper, the possibility of application of artificial neural networks to perform the fluid flow calculations through both damaged and undamaged turbine blading was investigated. Preliminary results are presented and show the potentiality of further development of the method for the purpose of heat-flow diagnostics.
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Selective adsorption of BTEX on calixarene-based molecular coordination network determined by 13C NMR spectroscopy
PublicationBenzene, toluene, ethylbenzene, and xylenes (BTEX), a class of volatile organic compounds, are harmful pollutants but also very important precursors in organic industrial chemistry. Among different approaches used for the BTEX treatment, the adsorption technology has been recognized as an efficient approach because it allows to recover and reuse both adsorbent and adsorbate. However, the selective adsorption of the components is...
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QUASI-DISTRIBUTED NETWORK OF LOW-COHERENCE FIBER-OPTIC FABRY-PÉROT SENSORS WITH CAVITY LENGTH-BASED ADDRESSING
PublicationDistributed measurement often relies on sensor networks. In this paper, we present the construction of low coherent fiber-optic Fabry-Pérot sensors connected into a quasi-distributed network. We discuss the mechanism of spectrum modulation in this type of sensor and the constraints of assembly of such sensors in the network. Particular attention was paid to separate the signals from individual sensors, which can be achieved by...
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Control of the induction motor in the field weakening region based on the multiscalar model.
PublicationNajwiększą korzyścią płynąca z zastosowania w układzie regulacji modelu multiskalarnego jest pełne odsprzężenie toru sterowania prędkością i toru sterowania strumieniem. Wykorzystanie zależności występujących w modelu multiskalarnym pozwala na określenie maksymalnego momentu wyjściowego w układzie napędowym dla zakresu osłabiania pola. Zaproponowany został bezczujnikowy układ regulacji w oparciu o obserwator prędkości.
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Selecting wells for an optimal design of groundwater monitoring network based on monitoring priority map: A Kish Island case study
PublicationThis paper presents a novel approach, i.e. a combination of gamma test and monitoring priority map, for optimal design of groundwater monitoring network (GMN) by considering the cumulative effects of industries, human activities, and natural factors on the groundwater quality. The proposed method was successfully applied to design an optimal network for groundwater salinity monitoring on Kish Island, Persian Gulf. The priority...
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<title>Recurrent neural network application to image filtering: 2-D Kalman filtering approach</title>
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Designing of an effective structure of system for the maintenance of a technical object with the using information from an artificial neural network
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Hybrid Inception-embedded deep neural network ResNet for short and medium-term PV-Wind forecasting
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Novel Adaptive Method for Data Streams Allocation Based on the Estimate of Radio Channel Parameters in Heterogeneous WBAN Network
PublicationThe new adaptive method for data streams allocation in heterogeneous Wireless Body Area Networks and meas-urement equipment is presented. The results obtained using the developed method compared with the selected algorithms likely to be used in those networks. The pro-posed adaptive data streams allocation method based on radio channel parameters makes it even twice as efficient to use in terms of resources usage in a WBAN heterogeneous...
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Neural networks based NARX models in nonlinear adaptive control
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The Optical Transport Network Control Based on SDN Architecture
PublicationThe aim of this publication is to present research results on the usability of the Software-Defined Networking concept to control transport networks. For this purpose, an easy-to-use connection scheduler was developed capable of controlling connections in optical transport networks. The authors would like to present this solution and details of constructed SDN architecture implemented for modern optical transport solutions based...
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Burst loss probability for the combination of extended offset time based service differentiation scheme and PPS in optical burst switching network
PublicationIn the paper analytical model for calculating burst loss probabilities for the combination of two service differentiation schemes for OBS network namely: extended offset time based scheme and PPS (Preemption Priority Schemes) is revised. Moreover authors introduce analytical model for calculating burst loss probabilities for an optical path when OBS network employs both service differentiation schemes and JET signaling. The comparison...
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Optimal Selection of Input Features and an Acompanying Neural Network Structure for the Classification Purposes - Skin Lesions Case Study
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Optimal selection of input features and an acompanying neural network structure for the classification purposes - skin lesions case study
PublicationMalignant melanomas are the most deadly type of skin cancers however detected early enough give a high chances for successful treatment. The last years saw the dynamic growth of interest of automatic computer-aided skin cancer diagnosis. Every month brings new research results on new approaches to this problem, new methods of preprocessing, new classifiers, new ideas to follow etc. In particular, the rapid development of dermatoscopy,...
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Neural Networks Based on Ultrafast Time-Delayed Effects in Exciton Polaritons
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Accidental wow evaluation based on sinusoidal modeling and neural nets prediction
PublicationReferat przedstawia opis algorytmu do określenia charakterystyki zniekształcenia kołysania dźwięku. Prezentowane podejście wykorzystuje sinusoidalną analizę dźwięku bazującą zarówno na amplitudowym jak i fazowym widmie sygnału fonicznego. Trajektorie poszczególnych składowych tonalnych, obrazujące zniekształcenie kołysania, określane są na podstawie analizy ich chwilowych amplitud, częstotliwości i faz. Dodatkowo referat przedstawia...
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Hierarchical 2-step neural-based LEGO bricks detection and labeling
PublicationLEGO bricks are extremely popular and allow the creation of almost any type of construction due to multiple shapes available. LEGO building requires however proper brick arrangement, usually done by shape. With over 3700 different LEGO parts this can be troublesome. In this paper, we propose a solution for object detection and annotation on images. The solution is designed as a part of an automated LEGO bricks arrangement. The...
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A novel method based on adaptive cuckoo search for optimal network reconfiguration and distributed generation allocation in distribution network
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Technology brands in the digitally-based and network economy. Setting the background
PublicationThis chapter defines and draws a general picture on Digital Technologies and Technology Brands’ meaning in the current economy. It contextualises the role and channels of digital technology’s impact on their shaping technology brands in network economy. It briefly explains why digital, innovative technologies constitute a perfect background and environment for technology brands of global scope. It discusses the place of technology...
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Agent-Based Population Learning Algorithm for RBF Network Tuning
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Photovoltaic bulk heterojunctions with interpenetrating network based on semiconducting polymers
PublicationPhotovoltaic cells are supposed to be the most common generators of useful electricity in the nearest future as they utilize inexhaustible carriers of renewable energy called photons. Despite the fact that 95% of worldwide applied photovoltaic devices are based on inorganic semiconductors the area of organic photovoltaics grows successively due to possibility of considerable reduction of manufacturing costs. Since the Heeger's...
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Agent-Based Approach to RBF Network Training with Floating Centroids
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An Experimental Study of Scenarios for the Agent-Based RBF Network Design
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Hardware-Software Implementation of a Sensor Network for CityTraffic Monitoring Using the FPGA- and ASIC-Based Sensor Nodes
PublicationArtykuł opisuje prototypową sieć sensorową do monitorowania ruchu pojazdów w mieście. Węzły sieci sensorowej, wyposażone w kamerę o niskiej rozdzielczości, obserwują ulice i wykrywają poruszające się obiekty. Detekcja obiektów jest realizowana w oparciu o własny algorytm segmentacji obrazów, wykorzystujący podwójne odejmowanie tła, wykrywanie krawędzi i cieni, działający na dedykowanym systemie mikroelektronicznym typu ''System...
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Modeling of TEC Variations Based on Signals from Near Zenith GNSS Satellite Observed by Dense Regional Network
PublicationCurrently the substantial successes in high-resolution ionospheric mapping is declared in many publications. Nevertheless, up to now there are no examples of dynamic visualization of TEC disturbances on regional scale with as high resolution as tropospheric models. Over the years, ionosphere has been modeling basing on the simple assumption, that it is a thin layer, which surrounds the Earth at some arbitrary height. However, the...
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Expedited Design Closure of Antennas By Means Of Trust-Region-Based Adaptive Response Scaling
PublicationIn the letter, a reliable procedure for expedited design optimization of antenna structures by means of trust-region adaptive response scaling (TR-ARS) is proposed. The presented approach exploits two-level electromagnetic (EM) simulation models. A predicted high-fidelity model response is obtained by applying nonlinear frequency and amplitude correction to the low-fidelity model. The surrogate created this way is iteratively rebuilt...
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Artificial Neural Networks in Classification of Steel Grades Based on Non-Destructive Tests
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Optimization of river network representation data models for web-based systems
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Composite Bioelectrodes Based on Lipidic Cubic Phase with Carbon Nanotube Network
PublicationElektrody z węgla szklistego modyfikowane fazą kubiczną z siecią nanorurek zastosowano do enzymatycznej redukcji tlenu katalizowanej przez lakazę. Zastosowanie nanorurek obniżyło nadpotencjał redukcji tlenu o 0,5 V. W celu zwiększenia gęstości prądu redukcji tlenu zastosowano znany mediator przeniesienia elektronów - ABTS. Mediator adsorbowano na nanorurkach lub wiązano kowalencyjnie z końcami nanorurek. Kowalencyjne związanie...
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Network Protection Against Node Attacks Based on Probabilistic Availability Measures
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Agent-Based RBF Network Classifier with Feature Selection in a Kernel Space
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Prediction of skin color, tanning and freckling from DNA in Polish population: linear regression, random forest and neural network approaches
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Artificial neural network model of hardness, porosity and cavitation erosion wear of APS deposited Al2O3 -13 wt% TiO2 coatings
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Application of Generalized Regression Neural Network and Gaussian Process Regression for Modelling Hybrid Micro-Electric Discharge Machining: A Comparative Study
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Hanna Obracht-Prondzyńska dr inż. arch.
PeopleHanna Obracht-Prondzyńska, PhD MArch, Eng. Assistant Professor at the University of Gdańsk, Department of Spatial Management, academic teacher of urban design and spatial data analyses. Architect and urban planner experienced in data driven urban design and planning. She defended her PhD with distinction in engineering and technical sciences in the discipline of architecture and urban planning in 2020 at the Faculty of Architecture...
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Prediction of Early Childhood Caries Based on Single Nucleotide Polymorphisms Using Neural Networks
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Application of PSO-artificial neural network and response surface methodology for removal of methylene blue using silver nanoparticles from water samples
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Multimodal Network Based Graphs of Primitives Storage Concept for Web Mining CBIR
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INTEGRATION OF THE MOBILE PLATFORMS BASED ON SOCIAL NETWORK SERVICE DIRECTED AT USERS LOCALIZATION
PublicationThis paper presents an architecture overview and some aspects of implementation of the social network service directed at users localization. It shows how web services can be used as a tool for integrating different mobile platforms with a web application. The main focus is set on communication between system elements and related problems.
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Kernel-Based Fuzzy C-Means Clustering Algorithm for RBF Network Initialization
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Challenges for universities in the face of the knowledge-based economy - Directions for higher education institutions in the Baltic Sea Region
PublicationThe aim of this paper is to present new challenges that are faced by universities in the knowledge-based economy. There are several phenomena that can presently be observed like the need for life-long learning or interdisciplinary approach, and universities should prepare their graduates for those challenges. One of the crucial questions that universities need to ask is how to teach and what to teach. Knowledge becomes obsolete...