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Wyniki wyszukiwania dla: TIME SERIES CLASSIFICATIONLEARNING SYSTEMSCAPSULE NETWORKSDATA MININGMULTI-HEAD CONVOLUTIONAL NEURAL NETWORKSSIGNAL PROCESSING
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Impact of Propeller Emergence on Hull, Propeller, Engine, and Fuel Consumption Performance in Regular Head Waves
PublikacjaIn this study, the impact of propeller emergence on the performance of a ship (speed), propeller (thrust, torque, and RPM), a diesel engine (torque and RPM) and fuel consumption are analysed under severe sea conditions. The goal is to describe the variation in the system variables and fuel consumption rather than analysing the motion of the ship or the phenomenon of propeller ventilation in itself. A mathematical model of the...
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Activation maps of convolutional neural networks as a tool for brain degeneration tracking in early diagnosis of dementia in Parkinson's disease based on magnetic resonance imaging
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Towards neural knowledge DNA
PublikacjaIn this paper, we propose the Neural Knowledge DNA, a framework that tailors the ideas underlying the success of neural networks to the scope of knowledge representation. Knowledge representation is a fundamental field that dedicates to representing information about the world in a form that computer systems can utilize to solve complex tasks. The proposed Neural Knowledge DNA is designed to support discovering, storing, reusing,...
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Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing
PublikacjaDeveloping signal processing methods to extract information automatically has potential in several applications, for example searching for multimedia based on its audio content, making context-aware mobile applications (e.g., tuning apps), or pre-processing for an automatic mixing system. However, the last-mentioned application needs a significant amount of research to reliably recognize real musical instruments in recordings....
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Diamond protection for reusable ZnO coated fiber-optic measurement head in optoelectrochemical investigation of bisphenol A
PublikacjaDue to the global problem with plastic contaminating the environment, with bisphenol A (BPA) being one of the highest demand, effective monitoring and purification of the pollutants are required. The electrochemical methods constitute a good solution but, due to polymerization of electrochemical oxidation bisphenol A products and their adsorption to the surfaces, measurement head elements are clogged by the formed film. In this...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublikacjaIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Neural Architecture Search for Skin Lesion Classification
PublikacjaDeep neural networks have achieved great success in many domains. However, successful deployment of such systems is determined by proper manual selection of the neural architecture. This is a tedious and time-consuming process that requires expert knowledge. Different tasks need very different architectures to obtain satisfactory results. The group of methods called the neural architecture search (NAS) helps to find effective architecture...
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Measurements and Visualization of Sound Intensity Around the Human Head in Free Field Using Acoustic Vector Sensor
PublikacjaThis paper presents measurements and visualization of sound intensity around the human head simulator in a free field. A Cartesian robot, applied for precise positioning of the acoustic vector sensor, was used to measure sound intensity. Measurements were performed in a free field using a head and torso simulator and the setup consisting of four different loudspeaker configurations. The acoustic vector sensor was positioned around...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublikacjaIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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A FPTAS for minimizing total completion time in a single machine time-dependent scheduling problem
PublikacjaIn this paper a single machine time-dependent scheduling problem with total completion time criterion is considered. There are given n jobs J1,…,Jn and the processing time pi of the ith job is given by pi=a+bisi, where si is the starting time of the ith job (i=1,…,n),bi is its deterioration rate and a is the common base processing time. If all jobs have deterioration rates different and not smaller than a certain constant u>0,...
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Experimental and Numerical Study on Pounding of Structures in Series
PublikacjaPounding between structures in series during earthquakes may cause serious damage in the structural elements. The aim of this paper is to show the results of an experimental and numerical study that is focused on pounding between more than two structures which may be described as “structures in series”. In this study, the shaking table experiments, as well as the numerical analyses, were performed using three tower models including...
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Influence of pulse waves on the transmission of near-infrared radiation in outer-head tissue layers.
PublikacjaIn this study, we investigate the effect of pulse waves on the transmission of near-infrared radiation in the outer tissue layers of the human head. This effect is important in using optical radiation to monitor brain conditions based on measuring the transmission changes in the near-infrared radiation between the source and the detector, placed on the surface of the scalp. This is because the signal related to the changes in the...
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INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublikacjaIn recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...
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Analysing and processing of geotagged social media
PublikacjaThe use of location based data analysing tools is an important part of geomarketing strategies among entrepreneurs. One of the key elements of interest is social media data shared by the users. This data is analysed both for its content and its location information, the results help to identify trends represented in the researched regions. In order to verify the possibilities of analysing and processing of geotagged social media...
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Investigating the Ischaemic Phase of Skin NADH Fluorescence Dynamics in Recently Diagnosed Primary Hypertension: A Time Series Analysis
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Volterra series usefulness in modelling of the time-domain cross-talk phenomena in coupled microstrip lines with nonlinear termination
PublikacjaW pracy przedyskutowano możliwość wykorzystania szeregów Volterry do analizy zjawiska przesłuchu w sprzężonych liniach mikropaskowych z nieliniowym obciążeniem. Apracowano algorytm metody, zaś uzyskane wyniki numeryczne zweryfikowano poprzez porównania z wynikami badań eksperymentalnych linii obciążonych w torze transmisyjnym diodą Schottky'ego.
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Deep neural networks for human pose estimation from a very low resolution depth image
PublikacjaThe work presented in the paper is dedicated to determining and evaluating the most efficient neural network architecture applied as a multiple regression network localizing human body joints in 3D space based on a single low resolution depth image. The main challenge was to deal with a noisy and coarse representation of the human body, as observed by a depth sensor from a large distance, and to achieve high localization precision....
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Photoelectron spectroscopy of a series of acetate and propionate esters
PublikacjaThe electronic state and photoionization spectroscopy of a series of acetate esters: methyl acetate, isopropyl acetate, butyl acetate and pentyl acetate as well as two propionates: methyl propionate and ethyl propionate, have been determined using vacuum-ultraviolet photoelectron spectroscopy. These experimental investigations are complemented by ab initio calculations. The measured first adiabatic and vertical ionization energies...
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Bees Detection on Images: Study of Different Color Models for Neural Networks
PublikacjaThis paper presents an approach to bee detection in video streams using a neural network classifier. We describe the motivation for our research and the methodology of data acquisition. The main contribution to this work is a comparison of different color models used as an input format for a feedforward convolutional architecture applied to bee detection. The detection process has is based on a neural binary classifier that classifies...
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Neural Modelling of Steam Turbine Control Stage
PublikacjaThe paper describes possibility of steam turbine control stage neural model creation. It is of great importance because wider application of green energy causes severe conditions for control of energy generation systems operation Results of chosen steam turbine of 200 MW power measurements are applied as an example showing way of neural model creation. They serve as training and testing data of such neural model. Relatively simple...
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Pervaporation in food processing
PublikacjaThis chapter is about pervaporation in food processing
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Elimination of Impulsive Disturbances From Archive Audio Signals Using Bidirectional Processing
PublikacjaIn this application-oriented paper we consider the problem of elimination of impulsive disturbances, such as clicks, pops and record scratches, from archive audio recordings. The proposed approach is based on bidirectional processing—noise pulses are localized by combining the results of forward-time and backward-time signal analysis. Based on the results of specially designed empirical tests (rather than on the results of theoretical analysis),...
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TOXIC GASES IDENTIFICATION USING SINGLE ELECTROCATALYTIC SENSOR RESPONSES AND ARTIFICIAL NEURAL NETWORK
PublikacjaThe 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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Influence of genetic background and oxidative stress response on risk of mandibular osteoradionecrosis after radiotherapy of head and neck cancer
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Digital Processing of Frequency–Pulse Signal in Measurement System
PublikacjaThe work presents the issue of the use of multichannel measurement systems of sensors processing input value to impulse signal frequency. The frequency impulse signal obtained from such sensors is often required to be processed at the same time with a voltage signal which is obtained from other sensors used in the same measurement system. In such case, it is usually necessary to sample the output signals from all sensors in the...
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Dissecting gamma frequency activities during human memory processing
PublikacjaGamma frequency activity (30-150 Hz) is induced in cognitive tasks and is thought to reflect underlying neural processes. Gamma frequency activity can be recorded directly from the human brain using intracranial electrodes implanted in patients undergoing treatment for drug-resistant epilepsy. Previous studies have independently explored narrowband oscillations in the local field potential and broadband power increases. It is not...
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Single and Series of Multi-valued Decision Diagrams in Representation of Structure Function
PublikacjaStructure function, which defines dependency of performance of the system on performance of its components, is a key part of system description in reliability analysis. In this paper, we compare two approaches for representation of the structure function. The first one is based on use of a single Multi-valued Decision Diagram (MDD) and the second on use of a series of MDDs. The obtained results indicate that the series of MDDs...
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Adding Interpretability to Neural Knowledge DNA
PublikacjaThis paper proposes a novel approach that adds the interpretability to Neural Knowledge DNA (NK-DNA) via generating a decision tree. The NK-DNA is a promising knowledge representation approach for acquiring, storing, sharing, and reusing knowledge among machines and computing systems. We introduce the decision tree-based generative method for knowledge extraction and representation to make the NK-DNA more explainable. We examine...
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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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The impact of the AC922 Architecture on Performance of Deep Neural Network Training
PublikacjaPractical deep learning applications require more and more computing power. New computing architectures emerge, specifically designed for the artificial intelligence applications, including the IBM Power System AC922. In this paper we confront an AC922 (8335-GTG) server equipped with 4 NVIDIA Volta V100 GPUs with selected deep neural network training applications, including four convolutional and one recurrent model. We report...
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The influence of the size of a one-faced metallic head in Janus nanoparticles as a co-catalyst on the photocatalytic efficiency of hydrogen evolution under vis light irradiation
PublikacjaJanus nanoparticles (NPs) consisting of MoOxSy nanospheres and silver (Ag) head, successfully developed by a simple, controlled method were in the first time they were applied as a co-catalysts in photocatalytic hydrogen generation reaction under vis light irradiation (λ > 420 nm). The MoOxSy-Ag as a co-catalysts were deposited on the obtained ZnIn2S4 microspheres (ZIS) using physical absorption method. The influence of the size...
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AN ATTEMPT AT IDENTIFYING THE INFLUENCE OF TEST HEAD ASSEMBLY STIFFNESS ON THE RESULTS OF A TRIBOLOGICAL EXPERIMENT CONDUCTED UNDER MICRO-OSCILLATION CONDITIONS
PublikacjaThe outcome of experimental research on a group of dry bearing materials carried out under small oscillation conditi ons and using a test rig designed and made at Gdansk University of Technology inspired the decision to find out if the stiffness of test head elements in fluenced the generated results. Therefore, a computer model utilising finite elements was devised and used to simulate the workings of the test head. The mode l...
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Intelligent turbogenerator controller based on artifical neural network
PublikacjaThe paper presents a desing of an intelligent controller based on neural network (ICNN). The ICNN ensures at the same time two fundamental functions : the maintaining of generator voltage at the desired value and the damping of the electromechanical oscillations. Its performance is evaluted on a single machine infinite bus power system through computer simulations. The dynamic and transient operation of the proposed controller...
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Optimizing the computation of a parallel 3D finite difference algorithm for graphics processing units
PublikacjaThis paper explores the possibilities of using a graphics processing unit for complex 3D finite difference computation via MUSTA‐FORCE and WENO algorithms. We propose a novel algorithm based on the new properties of CUDA surface memory optimized for 2D spatial locality and compare it with 3D stencil computations carried out via shared memory, which is currently considered to be the best approach. A case study was performed for...
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Measurement of the Development of a Learning IT Organization Supported by a Model of Knowledge Acquisition and Processing
PublikacjaThe paper presents a model of knowledge acquisition and processing for the development of learning organizations. The theory of a learning organization provides neither metrics nor tools to measure its development The authors' studies in this field are based on their experience gathered after projects realized in real IT organizations. The authors have described the construction of the model and the methods of its verification...
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Rare pain syndromes of the head and neck
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Robustness in Compressed Neural Networks for Object Detection
PublikacjaModel compression techniques allow to significantly reduce the computational cost associated with data processing by deep neural networks with only a minor decrease in average accuracy. Simultaneously, reducing the model size may have a large effect on noisy cases or objects belonging to less frequent classes. It is a crucial problem from the perspective of the models' safety, especially for object detection in the autonomous driving...
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Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural Networks
PublikacjaEstimation of vital signs using image processing techniques have already been proved to have a potential for supporting remote medical diagnostics and replacing traditional measurements that usually require special hardware and electrodes placed on a body. In this paper, we further extend studies on contactless Respiratory Rate (RR) estimation from extremely low resolution thermal imagery by enhancing acquired sequences using Deep...
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Towards bees detection on images: study of different color models for neural networks
PublikacjaThis paper presents an approach to bee detection in videostreams using a neural network classifier. We describe the motivationfor our research and the methodology of data acquisition. The maincontribution to this work is a comparison of different color models usedas an input format for a feedforward convolutional architecture appliedto bee detection. The detection process has is based on a neural...
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A survey of neural networks usage for intrusion detection systems
PublikacjaIn recent years, advancements in the field of the artificial intelligence (AI) gained a huge momentum due to the worldwide appliance of this technology by the industry. One of the crucial areas of AI are neural networks (NN), which enable commer‐ cial utilization of functionalities previously not accessible by usage of computers. Intrusion detection system (IDS) presents one of the domains in which neural networks are widely tested...
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Comparison of EHD devices with parallel and in series spiked electrodes
PublikacjaIn this paper two electrohydrodynamic (EHD) devices for gas pumping and cleaning are presented. In both cases to induce an airflow in these EHD devices corona discharge was used. The discharge was generated between the spiked electrodes set parallel (the first case) or in series (the second case) and the plate electrodes. An asymmetric electric field and generated discharge result in unidirectional gas flow through the EHD device....
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Comparison of image pre-processing methods in liver segmentation task
PublikacjaAutomatic liver segmentation of Computed Tomography (CT) images is becoming increasingly important. Although there are many publications in this field there is little explanation why certain pre-processing methods were utilised. This paper presents a comparison of the commonly used approach of Hounsfield Units (HU) windowing, histogram equalisation, and a combination of these methods to try to ascertain what are the differences...
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Efficient signal processing in spectroscopic optical coherence tomography
PublikacjaSpectroscopic optical coherence tomography (SOCT) is an extension of a standard OCT technique, which allows to obtain depth-resolved, spectroscopic information on the examined sample. It can be used as a source of additional contrast in OCT images e.g. by encoding certain features of the light spectrum into the hue of the image pixels. However, SOCT require computation of time-frequency distributions of each OCT A-scan, what is...
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Ship Resistance Prediction with Artificial Neural Networks
PublikacjaThe paper is dedicated to a new method of ship’s resistance prediction using Artificial Neural Network (ANN). In the initial stage selected ships parameters are prepared to be used as a training and validation sets. Next step is to verify several network structures and to determine parameters with the highest influence on the result resistance. Finally, other parameters expected to impact the resistance are proposed. The research utilizes...
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Global Surrogate Modeling by Neural Network-Based Model Uncertainty
PublikacjaThis work proposes a novel adaptive global surrogate modeling algorithm which uses two neural networks, one for prediction and the other for the model uncertainty. Specifically, the algorithm proceeds in cycles and adaptively enhances the neural network-based surrogate model by selecting the next sampling points guided by an auxiliary neural network approximation of the spatial error. The proposed algorithm is tested numerically...
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Data Acquisition and Processing for GeoAI Models to Support Sustainable Agricultural Practices
PublikacjaThere are growing opportunities to leverage new technologies and data sources to address global problems related to sustainability, climate change, and biodiversity loss. The emerging discipline of GeoAI resulting from the convergence of AI and Geospatial science (Geo-AI) is enabling the possibility to harness the increasingly available open Earth Observation data collected from different constellations of satellites and sensors...
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Statistically efficient smoothing algorithm for time-varying frequency estimation
PublikacjaThe problem of extraction/elimination of a nonstationary sinusoidal signal from noisy measurements is considered. This problem is usually solved using adaptive notch filtering (ANF) algorithms. It is shown that the accuracy of frequency estimates can be significantly increased if the results obtained from ANF are backward-time filtered by an appropriately designed lowpass filter. The resulting adaptive notch smoothing (ANS) algorithm...
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Influence of accelerometer signal pre-processing and classification method on human activity recognition
PublikacjaA study of data pre-processing influence on accelerometer-based human activity recognition algorithms is presented. The frequency band used to filter-out the accelerometer signals and the number of accelerometers involved were considered in terms of their influence on the recognition accuracy. In the test four methods of classification were used: support vector machine, decision trees, neural network, k-nearest neighbor.
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Dynamically positioned ship steering making use of backstepping method and artificial neural networks
PublikacjaThe 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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Optical properties of thin TiO2 film deposited on the fiber optic sensor head
PublikacjaThe presented study was focused on investigation of the titanium dioxide (TiO2) thin film deposited on the fiber tip. The intention of this investigation was using TiO2 film in the construction of the optical fiber sensor head. In the demonstrated construction TiO2 thin layer was deposited on the tip of a commonly used telecommunication single mode optical fiber (SMF-28) by means of the Atomic Layer Deposition (ALD). Thickness...