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Search results for: natural radioactivity
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On Nature-Inspired Design Optimization of Antenna Structures Using Variable-Resolution EM Models
PublicationNumerical optimization has been ubiquitous in antenna design for over a decade or so. It is indispensable in handling of multiple geometry/material parameters, performance goals, and constraints. It is also challenging as it incurs significant CPU expenses, especially when the underlying computational model involves full-wave electromagnetic (EM) analysis. In most practical cases, the latter is imperative to ensure evaluation reliability....
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The Effectiveness of Using a Pretrained Deep Learning Neural Networks for Object Classification in Underwater Video
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Hybrid of Neural Networks and Hidden Markov Models as a modern approach to speech recognition systems
PublicationThe aim of this paper is to present a hybrid algorithm that combines the advantages ofartificial neural networks and hidden Markov models in speech recognition for control purpos-es. The scope of the paper includes review of currently used solutions, description and analysis of implementation of selected artificial neural network (NN) structures and hidden Markov mod-els (HMM). The main part of the paper consists of a description...
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Neural Networks, Support Vector Machine and Genetic Algorithms for Autonomous Underwater Robot Support
PublicationIn this paper, artificial neural networks, a classification technique called support vector machine and meta-heuristics genetic algorithm have been considered for development in autonomous underwater robots. Artificial neural networks have been used for seabed modelling as well as support vector machine has been applied for the obstacles classification to avoid some collision problems. Moreover, genetic algorithm has been applied...
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Usage of Two-Center Basis Function Neural Classifiers in Compact Smart Resistive Sensors
PublicationA new solution of the smart resistance sensorwith the Two-Center Basis Function (TCBF) neuralclassifier, for which the resistance sensor is a component ofan anti-aliasing filter of an ADC is proposed. Thetemperature measurement procedure is based on excitationof the filter by square impulses, sampling time response ofthe filter and processing measured voltage values by theTCBF classifier. All steps of the measurement procedure...
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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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Optical Sensor Based Gestures Inference Using Recurrent Neural Network in Mobile Conditions
PublicationIn this paper the implementation of recurrent neural network models for hand gesture recognition on edge devices was performed. The models were trained with 27 hand gestures recorded with the use of a linear optical sensor consisting of 8 photodiodes and 4 LEDs. Different models, trained off-line, were tested in terms of different network topologies (different number of neurons and layers) and different effective sampling frequency...
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APPLICATION OF STATISTICAL FEATURES AND MULTILAYER NEURAL NETWORK TO AUTOMATIC DIAGNOSIS OF ARRHYTHMIA BY ECG SIGNALS
PublicationAbnormal electrical activity of heart can produce a cardiac arrhythmia. The electrocardiogram (ECG) is a non-invasive technique which is used as a diagnostic tool for cardiac diseases. Non-stationarity and irregu- larity of heartbeat signal imposes many difficulties to clinicians (e.g., in the case of myocardial infarction arrhythmia). Fortunately, signal processing algorithms can expose hidden information within ECG signal contaminated...
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The influence of image masks definition onsegmentation results of histopathological imagesusing convolutional neural network
PublicationAbstract—In the era of collecting large amounts of tissue materials, assisting the work of histopathologists with various electronic and information IT tools is an undeniable fact. The traditional interaction between a human pathologist and the glass slide is changing to interaction between an AI pathologist with a whole slide images. One of the important tasks is the segmentation of objects (e.g. cells) in such images. In this...
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TOXIC GASES IDENTIFICATION USING SINGLE ELECTROCATALYTIC SENSOR RESPONSES AND ARTIFICIAL NEURAL NETWORK
PublicationThe need for precise detection of toxic gases drives development of new gas sensors structures and methods of processing the output signals from the sensors. In literature, artificial neural networks are considered as one of the most effective tool for the analysis of gas sensors or sensors arrays responses. In this paper a method of toxic gas components identification using a electrocatalytic gas sensor as a detector and an artificial...
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Approximation of Fractional Order Dynamic Systems Using Elman, GRU and LSTM Neural Networks
PublicationIn the paper, authors explore the possibility of using the recurrent neural networks (RNN) - Elman, GRU and LSTM - for an approximation of the solution of the fractional-orders differential equations. The RNN network parameters are estimated via optimisation with the second order L-BFGS algorithm. It is done based on data from four systems: simple first and second fractional order LTI systems, a system of fractional-order point...
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Artificial Neural Network in Forecasting the Churn Phenomena Among Costumers of IT and Power Supply Services
PublicationThis paper presents an attempt to use an artificial neural network to investigate the churn phenomenon among the customers of a telecommunications operator. An attempt was made to create a data model based on the customer lifetime value (CLV) rather than on activity alone. A multilayered artificial neural network was used for the experiments. The results yielded a 99% successful identification rate for customers in no danger of...
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An automatic selection of optimal recurrent neural network architecture for processes dynamics modelling purposes
PublicationA problem related to the development of algorithms designed to find the structure of artificial neural network used for behavioural (black-box) modelling of selected dynamic processes has been addressed in this paper. The research has included four original proposals of algorithms dedicated to neural network architecture search. Algorithms have been based on well-known optimisation techniques such as evolutionary algorithms and...
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublicationForecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...
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Neural network based algorithm for hand gesture detection in a low-cost microprocessor applications
PublicationIn this paper the simple architecture of neural network for hand gesture classification was presented. The network classifies the previously calculated parameters of EMG signals. The main goal of this project was to develop simple solution that is not computationally complex and can be implemented on microprocessors in low-cost 3D printed prosthetic arms. As the part of conducted research the data set EMG signals corresponding...
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Dynamically positioned ship steering making use of backstepping method and artificial neural networks
PublicationThe article discusses the issue of designing a dynamic ship positioning system making use of the adaptive vectorial backstepping method and RBF type arti cial neural networks. In the article, the backstepping controller is used to determine control laws and neural network weight adaptation laws. e arti cial neural network is applied at each time instant to approximate nonlinear functions containing parametric uncertainties....
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Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
PublicationThe 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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Selection of an artificial pre-training neural network for the classification of inland vessels based on their images
PublicationArtificial neural networks (ANN) are the most commonly used algorithms for image classification problems. An image classifier takes an image or video as input and classifies it into one of the possible categories that it was trained to identify. They are applied in various areas such as security, defense, healthcare, biology, forensics, communication, etc. There is no need to create one’s own ANN because there are several pre-trained...
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Using Convolutional Neural Networks for Corneal Arcus Detection Towards Familial Hypercholesterolemia Screening
PublicationFamilial hypercholesterolemia (FH) is a highly undiagnosed disease. Among FH patients, the onset of premature coronary artery disease is 13 times higher than in the general population. Early diagnosis and treatment is essential to prevent cardiovascular diseases and their complications, and to prolong life. One of the clinical criteria of FH is the occurrence of a corneal arcus (CA) among patients, especially those under 45 years...
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Design and Analysis of Artificial Neural Network (ANN) Models for Achieving Self-Sustainability in Sanitation
PublicationThe present study investigates the potential of using fecal ash as an adsorbent and demonstrates a self-sustaining, optimized approach for urea recovery from wastewater streams. Fecal ash was prepared by heating synthetic feces to 500 °C and then processing it as an adsorbent for urea adsorption from synthetic urine. Since this adsorption approach based on fecal ash is a promising alternative for wastewater treatment, it increases...
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Accidental wow defect evaluation using sinusoidal analysis enhanced by artificial neural networks
PublicationArtykuł 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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International Conference on Natural Computation
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Intrinsic effects of AM4113, a putative neutral CB1 receptor selective antagonist, on open-field behaviors in rats
PublicationW pracy przedstawiono wyniki testów otartego pola na zachowanie szczurów po iniekcji zwierzętom WIN55,21-2 (WIN; 3 mg/kg) agonisty receptora kanabinoidowego CB1R, bądź AM4113 (0.3−5.6 mg/kg) przypuszczalnie neutralnego antagonisty receptora kanabinoidowego CB1R oraz mieszaniny obu związków. W badaniach pod uwagę brano następujące zachowania zwierząt; ilość kwadratów, którą szczury przechodziły na czterech nogach, częstotliwość...
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Parameter of nonlinearity B/A of three-component systems with separate volumes of liquid, its vapor and a neutral gas
PublicationOtrzymane zostało wyrażenie dla zaburzenia entropii substancji o trzech komponentach jako funkcja zaburzeń jej ciśnienia i gęstości. Na podstawie wzoru prędkość i parametru nieliniowosci fali akustycznej zostały wyliczone jako funkcje i ciśnienia i koncentracji pary i powietrza. Rezultaty są przedstawione w postaci wykresów.
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Conventional and solid-contact lithium-selective electrodes based on tris(N,N-dicyclohexylamide) neutral ionophore
PublicationKonstruowano jonoselektywne elektrody litowe (Li-ISEs) z membraną polimerową i obojętnym jonoforem tris(N,N-dicycloheksyloamidem) jako: elektrodę konwencjonalną (z wodnym roztworem elektrolitu wewnętrznego) oraz ze stałym kontaktem (polianilina jako przekaźnik jonowo-elektronowy). Charakterystyki obu elektrod (nachylenie i zakres liniowy) są porównywalne. Badana elektroda ze stałym kontaktem wykazuje dobrą stabilność w czasie....
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Lateral diffusion coefficients in membranes measured by resonance energy transfer and a new algorithm for diffusion in two dimentions
PublicationOpisano wyniki pomiarów współczynników dyfuzji w membranach przy wykorzystaniu rezonansowego przekazywania energii wzbudzania. Donorem był kompleks metaloorganiczny renu o czasie życia ok. 3ćs, co pozwalało na pomiary współczynników dyfuzji mniejszych od 10 cm2/s. Zmierzono współczynniki dyfuzji w membranach typu DMPG i DOPC w różnych temperaturach.
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space-vector pulse width modulation for three-level npc converter with the neutral point voltage control
PublicationPrzedstawiono strategię modulacji PWM dla trójpoziomowych falowników NPC z predykcją i kompensacją asymetrii rozkładu napięcia na kondensatorach obwodu pośredniczącego
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The influence of a change in the meniscus cross-sectional shape on the medio-lateral translation of the knee joint and meniscal extrusion
PublicationObjective The purpose of this study was to evaluate the influence of a change in the meniscus cross sectional shape on its position and on the biomechanics of a knee joint. Methods One main finite element model of a left knee joint was created on the basis of MRI images. The model consisted of bones, articular cartilages, menisci and ligaments. Eight variants of this model with an increased or decreased meniscus height were then...
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Assessment of the Relationship between the Shape of the Lateral Meniscus and the Risk of Extrusion Based on MRI Examination of the Knee Joint
PublicationBackground Meniscus extrusion is a serious and relatively frequent clinical problem. For this reason the role of different risk factors for this pathology is still the subject of debate. The goal of this study was to verify the results of previous theoretical work, based on the mathematical models, regarding a relationship between the cross-section shape of the meniscus and the risk of its extrusion. Materials and Methods Knee...
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Proceedings of the Latvian Academy of Sciences, Section B: Natural, Exact, and Applied Sciences
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POLISH JOURNAL OF NATURAL SCIENCES
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Mathematical Modelling of Natural Phenomena
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Environmental Communication-A Journal of Nature and Culture
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Journal for the Study of Religion Nature and Culture
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Micrologus-Nature Science and Medieval Societies
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International Journal of Design and Nature and Ecodynamics
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HUMAN NATURE-AN INTERDISCIPLINARY BIOSOCIAL PERSPECTIVE
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Nature Clinical Practice Cardiovascular Medicine
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NATURE REVIEWS MOLECULAR CELL BIOLOGY
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Nature Clinical Practice Endocrinology & Metabolism
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Environment and Planning E-Nature and Space
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Nature Clinical Practice Gastroenterology & Hepatology
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Estudos de Psicologia (Natal)
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Relacoes Internacionais no Mundo Atual
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Wind-wave variability in a shallow tidal sea—Spectral modelling combined with neural network methods
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A contribution to the moss and liverwort flora of the Reberce Nature Reserve at the Przemyśl Foothills (Western Carpathians, Poland)
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The nature of emitting states in electroluminescence of polymeric films do-ped with anthracene andanthracene-based supramolecules
PublicationZaobserwowano nową odmianę bi-molekularnych stanów wzbudzenia elektronowego w polimerowych jednowarstwowych diodach EL z molekułami antracenu wbudowanymi bezpośrednio w matrycę poliwęglanową, jak i pośrednio przez ich włączenie jako grup chromoforowych w dużych makromolekułach rotaxanowych. Stwierdzono, że obok typowej emisji ekscymerowej pojawia się długofalowe pasmo elektromerowe. Pasmo to związane jest z emisją kolumbowsko związanych...
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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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Inspired by Nature: The Use of Plant-derived Substrate/Enzyme Combinations to Generate Antimicrobial Activity in situ
PublicationThe last decade has witnessed a renewed interest in antimicrobial agents. Plants have received particular attention and frequently rely on the spontaneous enzymatic conversion of an inactive precursor to an active agent. Such two-component substrate/enzyme defence systems can be reconstituted ex vivo. Here, the alliin/alliinase system from garlic seems to be rather effective against Saccharomyces cerevisiae, whilst the glucosinolate/myrosinase...