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Wyniki wyszukiwania dla: FASTER REGION BASED CONVOLUTIONAL NEURAL NETWORK
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Modelling of a medium-term dynamics in a shallow tidal sea, based on combined physical and neural network methods
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Safety assessment of ships in critical conditions using a knowledge-based system for design and neural network system
PublikacjaW pracy opisano wybrane elementy metody oceny bezpieczeństwa statków w stanie uszkodzonym, ukierunkowanej na ocenę osiągów statku i ocenę ryzyka. Metoda analizy osiągów i zachowania się statku w stanie uszkodzonym została wykorzystana do oceny charakterystyk hydromechanicznych statku uszkodzonego. Do oceny ryzyka wykorzystano elementy metodyki Formalnej Oceny Bezpieczeństwa. System ekspertowy został wykorzystany do analziy podziału...
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Food Classification from Images Using a Neural Network Based Approach with NVIDIA Volta and Pascal GPUs
PublikacjaIn the paper we investigate the problem of food classification from images, for the Food-101 dataset extended with 31 additional food classes from Polish cuisine. We adopted transfer learning and firstly measured training times for models such as MobileNet, MobileNetV2, ResNet50, ResNet50V2, ResNet101, ResNet101V2, InceptionV3, InceptionResNetV2, Xception, NasNetMobile and DenseNet, for systems with NVIDIA Tesla V100 (Volta) and...
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A survey on network resiliency methodologies against weather-based disruptions
PublikacjaDue to the increasing dependence on network services of our society, research has recently been concentrating on enhancing traditional protection strategies to withstand large-scale failures, as in case of disaster events. The recently-formed EU-funded RECODIS project aims at coordinating and fostering research collaboration in Europe on disaster resiliency in communication networks. In particular, the Working Group (WG) 2 of the...
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Cellular neural network application to moire pattern filtering
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Comparative study of methods for artificial neural network training.
PublikacjaPrzedstawiono 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
PublikacjaPrzedstawiono 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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The Neural Knowledge DNA Based Smart Internet of Things
PublikacjaABSTRACT The Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. Smartness, however, remains a substantial challenge for IoT applications. Recent advances in networked sensor technologies, computing, and machine learning have made it possible for building new smart IoT applications. In this paper, we propose a novel approach: the Neural Knowledge DNA based Smart Internet...
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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublikacjaThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
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Agent-based social network as a simulation of a market behaviour
PublikacjaRecent years and the outbreak of world's economic crisis in 2008 proved the crucial importance of reliable analysis of market dynamics. However, werarely apply models of proper detail level (the global prosperity forecast of 2007 can be seen as a grim proof). The behaviour of individuals and companies is far from being ideal and rational. Many claims that the economic paradigm of rational expectations (coming from J. Muth and R....
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Creating neural models using an adaptive algorithm for optimal size of neural network and training set.
PublikacjaZaprezentowano adaptacyjny algorytm generujący modele neuronowe liniowych układów mikrofalowych, zdolny do oszacowania optymalnego rozmiaru zbiory uczącego i sieci neuronowej. Stworzono kilka modeli nieciągłości falowodowych i mokropaskowych, a następnie zweryfikowano ich poprawność porównując wyniki analiz metodą dopasowania rodzajów i metodą momentów filtrów pasmowo-przepustowych.
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Blood Pressure Estimation Based on Blood Flow, ECG and Respiratory Signals Using Recurrent Neural Networks
PublikacjaThe estimation of systolic and diastolic blood pressure using artificial neural network is considered in the paper. The blood pressure values are estimated using pulse arrival time, and additionally RR intervals of ECG signal together with respiration signal. A single layer recurrent neural network with hyperbolic tangent activation function was used. The average blood pressure estimation error for the data obtained from 21 subjects...
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A compact smart sensor based on a neural classifier for objects modeled by Beaunier's model
PublikacjaA new solution of a smart microcontroller sensor based on a simple direct sensor-microcontroller interface for technical objects modeled by two-terminal networks and by the Beaunier’s model of anticorrosion coating is proposed. The tested object is stimulated by a square pulse and its time voltage response is sampled four times by the internal ADC of microcontroller. A neural classifier based on measurement data classifies the...
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PROGRAMMABLE YANG - BASED INTERFACE IN CONTROL OF OPTICAL TRANSPORT NETWORK
PublikacjaSince over a decade we observe intensive effort of research institutions and industrial consortia on extending flexibility and automation of the transport network control also known under the term network programmability. Key aspect of each programming interface is ability to evolve but also sensitivity to future modifications. As indicated in the past work in the specific context of optical transport networks an important criterion...
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Energy-Efficient Neural Network Inference with Microcavity Exciton Polaritons
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Neural network approach to 2D Kalman filtering in image processing
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Neural network modelling of the influence of channelopathies on reflex visual attention
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The fuzzy neural network: application for trends in river pollution prediction
PublikacjaPraca przedstawia zastosowanie rozmytych sieci neuronowych do przygotowywania prognoz zmian w stężeniu zanieczyszczeń w rzekach. Opisane są pokrótce inne narzędzia stosowane w tym celu.
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Application of a fuzzy neural network for river water quality prediction
PublikacjaMonitoring i modelowanie zmian w jakości wód powierzchniowych stanowią jeden z kluczowych elementów monitoringu i zarządzania ochroną środowiska na skalę globalną. Kontrolowanie tak złożonych i nieliniowych w swojej charakterystyce obiektów, jakimi są rzeki, jest trudnym zadaniem. Zazwyczaj do tego celu wykorzystuje się modele matematyczne, jednak czasem wymagają one bardzo dużej ilości danych, lub czas oczekiwania na odpowiedź...
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Expedited Trust-Region-Based Design Closure of Antennas by Variable-Resolution EM Simulations
PublikacjaThe observed growth in the complexity of modern antenna topologies fostered a widespread employment of numerical optimization methods as the primary tools for final adjustment of the system parameters. This is mainly caused by insufficiency of traditional design closure approaches, largely based on parameter sweeping. Reliable evaluation of complex antenna structures requires full-wave electromagnetic (EM) analysis. Yet, EM-driven...
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A new analyzer based on pellistor sensor with neural network data postprocessing for measurement of hydrocarbons in lower explosive limit range
PublikacjaW pracy przedstawiono rezultaty pierwszego etapu badań nad nowym typem analizatora do oznaczania stężenia wodoru i lotnych węglowodorów w zakresie dolnej granicy wybuchowości. Analizator ten zbudowano w oparciu o pojedynczy czujnik pelistorowy z układem przetwarzania danych wykorzystującym sztuczną sieć neuronową.
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Generalized regression neural network and fitness dependent optimization: Application to energy harvesting of centralized TEG systems
PublikacjaThe thermoelectric generator (TEG) system has attracted extensive attention because of its applications in centralized solar heat utilization and recoverable heat energy. The operating efficiency of the TEG system is highly affected by operating conditions. In a series-parallel structure, due to diverse temperature differences, the TEG modules show non-linear performance. Due to the non-uniform temperature distribution (NUTD) condition,...
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A method of the UMTS-FDD network design based on universal load characteristics
PublikacjaIn the paper an original method of the UMTS radio network design was presented. The method is based on simple way of capacity-coverage trade-off estimation for WCDMA/FDD radio interface. This trade-off is estimated by using universal load characteristics and normalized coverage characteristics. The characteristics are useful for any propagation environment as well as for any service performance requirements. The practical applications...
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Analysis of the impact of socio-economic development on road safety based on the example of Baltic Sea Region countries
PublikacjaBaltic Sea Region (BSR) is a specific region of Europe, bringing together countries with different levels of socio-economic development. The main common point is territorial access to the Baltic Sea and the importance of maritime transport in the transportation of goods. The region consists of 9 countries, including Germany, Poland, Lithuania, Latvia, Estonia, Finland, Sweden, Denmark and Russia (more specifically, Kaliningrad...
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Energy Management for PV Powered Hybrid Storage System in Electric Vehicles Using Artificial Neural Network and Aquila Optimizer Algorithm
PublikacjaIn an electric vehicle (EV), using more than one energy source often provides a safe ride without concerns about range. EVs are powered by photovoltaic (PV), battery, and ultracapacitor (UC) systems. The overall results of this arrangement are an increase in travel distance; a reduction in battery size; improved reaction, especially under overload; and an extension of battery life. Improved results allow the energy to be used efficiently,...
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Ultracapacitor modeling and control with discrete fractional order artificial neural network
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An application of the TCRBF neural network in multi-node fault diagnosis method
PublikacjaPrzedstawiono nową metodę samo-testowania części analogowej w systemach elektronicznych sterowanych mikrokontrolerami. Układ badany pobudzany jest przebiegiem sinusoidalnym przez generator zamontowany w systemie, a jego odpowiedź jest próbkowana w wybranych węzłach przez wewnętrzny przetwornik A/C mikrokontrolera. Detekcja i lokalizacja uszkodzenia jest dokontwana przez sieć neuronową typu TCRBF. Procedurę diagnostyczną zaimplementowano...
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Diagnostic potential for a serum miRNA neural network for detection of ovarian cancer
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Artificial neural network controller for underwater ship hull operation robot.
PublikacjaZaproponowano model matematyczny pojazdu podwodnego, który w uproszczonej wersji spełnia warunki dynamiki odpowiadające głowicy roboczej podwodnego robota. Uwzględniono niektóre czynniki oddziałujące na ruch podwodnej głowicy roboczej, jak np. gęstość wody oraz siły odśrodkowe i wypornościowe. Przedstawiono układ sterowania, w którym zastosowano regulator oparty na bazie sieci neuronowych, za pomocą którego można sterować...
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Neural Network Application for Recognition of Geometry Degradation of Power Cycle Components
PublikacjaPrzedyskutowano problem rozpoznawania degradacji geometrycznej. Skuteczne zastosowanie wybranego typu sieci neuronowej (SSN) jest prezentowane w referacie. SSN wykrywająca typy degradacji geometrycznej wykazała wysoką jakość. Pokazano pewną możliwość ekstrapolacji takich SSN. Pokazano możliwość wykrywania typów degradacji geometrycznej nawet w przypadku pozyskiwania niepełnych danych pomiarowych.
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A Novel Trust-Region-Based Algorithm with Flexible Jacobian Updates for Expedited Optimization of High-Frequency Structures
PublikacjaSimulation-driven design closure is mandatory in the design of contemporary high-frequency components. It aims at improving the selected performance figures through adjustment of the structure’s geometry (and/or material) parameters. The computational cost of this process when employing numerical optimization is often prohibitively high, which is a strong motivation for the development of more efficient methods. This is especially...
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Surface effects of network materials based on strain gradient homogenized media
PublikacjaThe asymptotic homogenization of periodic network materials modeled as beam networks is pursued in this contribution, accounting for surface effects arising from the presence of a thin coating on the surface of the structural beam elements of the network. Cauchy and second gradient effective continua are considered and enhanced by the consideration of surface effects. The asymptotic homogenization technique is here extended to...
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Using Deep Neural Network Methods for Forecasting Energy Productivity Based on Comparison of Simulation and DNN Results for Central Poland—Swietokrzyskie Voivodeship
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Using Deep Neural Network Methods for Forecasting Energy Productivity Based on Comparison of Simulation and DNN Results for Central Poland – Swietokrzyskie Voivodeship
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Leveraging Training Strategies of Artificial Neural Network for Classification of Multiday Electromyography Signals
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Application of fuzzy neural network for supporting measurements and control in a wastewater treatment plant
PublikacjaOczyszczanie ścieków jest jednym z ważniejszych aspektów ochrony środowiska. Nowoczesne systemy kontroli w oczyszczalniach ścieków pozwalają na poprawę jakości procesu oczyszczania redukując jednocześnie koszty. Systemy kontroli i optymalizacji jakie odkilku lat opracowuje się dla oczyszczalni ścieków, bazują zazwyczaj na skomplikowanych modelach matematycznych. Kluczowym problemem w zastosowaniu tych systemów jest duża liczba...
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Mathematical modeling and prediction of pit to crack transition under cyclic thermal load using artificial neural network
PublikacjaThe formation of pitting is a major problem in most metals, which is caused by extremely localized corrosion that creates small holes in metal and subsequently, it changes into cracks under mechanical load, thermo-mechanical stress, and corrosion process factors. This research aims to study pit to crack transition phenomenon of steel boiler heat tubes under cyclic thermal load, and mathematical modeling...
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Intracranial hemorrhage detection in 3D computed tomography images using a bi-directional long short-term memory network-based modified genetic algorithm
PublikacjaIntroduction: Intracranial hemorrhage detection in 3D Computed Tomography (CT) brain images has gained more attention in the research community. The major issue to deal with the 3D CT brain images is scarce and hard to obtain the labelled data with better recognition results. Methods: To overcome the aforementioned problem, a new model has been implemented in this research manuscript. After acquiring the images from the Radiological...
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Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks
PublikacjaOne of the ways to improve the fuel economy of heavy duty trucks is to operate the combustion engine in its most efficient operating points. To do that, a mathematical model of the engine is required, which shows the relations between engine speed, torque and fuel consumption in transient states. In this paper, easy accessible exploitation data collected via CAN bus of the heavy duty truck were used to obtain a model of a diesel...
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Classification of objects in the LIDAR point clouds using Deep Neural Networks based on the PointNet model
PublikacjaThis work attempts to meet the challenges associated with the classification of LIDAR point clouds by means of deep learning. In addition to achieving high accuracy, the designed system should allow the classification of point clouds covering an area of several dozen square kilometers within a reasonable time interval. Therefore, it must be characterized by fast processing and efficient use of memory. Thus, the most popular approaches...
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Towards Designing an Innovative Industrial Fan: Developing Regression and Neural Models Based on Remote Mass Measurements
PublikacjaThis 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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Taking decisions in the diagnostic intelligent systems on the basis information from an artificial neural network
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An application of neural network for Structural Health Monitoring of an adaptive wing with an array of FBG sensors
PublikacjaW pracy przedstwiono możliwości zastoswania sieci czujników FBG i sztucznych sieci neuronowych do detekcji uszkodzeń w poszyciu adaptacyjnego skrzydła.
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Dataset Related Experimental Investigation of Chess Position Evaluation Using a Deep Neural Network
PublikacjaThe 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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Comparison of tuning procedures based on evolutionary algorithm for multi-region fuzzy-logic PID controller for non-linear plant
PublikacjaThe 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
PublikacjaThis 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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Neural network simulator's application to reference performance determination of turbine blading in the heat-flow diagnostics.
PublikacjaIn 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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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
PublikacjaIn 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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Selective adsorption of BTEX on calixarene-based molecular coordination network determined by 13C NMR spectroscopy
PublikacjaBenzene, 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...