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Wyniki wyszukiwania dla: artificial neural network
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Metabolic Profiling of Jasminum grandiflorum L. Flowers and Protective Role against Cisplatin-Induced Nephrotoxicity: Network Pharmacology and In Vivo Validation
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A Dynamic Forecast Demand Scenario Analysis to Design an Automated Parcel Lockers Network in Pamplona (Spain) Using a Simulation-Optimization Model
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Corrosion behaviour of low carbon steel in artificial seawater using TP, LP, EIS, Harmonic Analysis (HA) and new method Dynamic Electrochemical Impedance Spectroscopy (DEIS)
PublikacjaZe względu na istotną rolę technik elektrochemicznych w badaniach procesów korozyjnych są one szeroko stosowane w monitorowaniu korozji. Celem niniejszej pracy jest zgromadzenie rezultatów wyników doświadczalnych uzyskanych różnymi technikami i znalezienie korelacji między nimi. Własności korozyjne stali stopowej (AISI 1026) w sztucznej wodzie morskiej zostały zbadane z wykorzystaniem ekstrapolacji tafelowskiej (TP), polaryzacji...
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First Measurements of the Earth’s Electric Field at the Arctowski Antarctic Station, King George Island, by the New Polish Atmospheric Electricity Observation Network
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Synergistic effect of carbon fibers and carbon nanotubes on improving thermal stability and flame retardancy of polypropylene: a combination of a physical network and chemical crosslinking
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Korporacja Guggenheima- globalny charakter sieci muzeów a tożsamość miasta = Guggenheim's Corporation- global character of museums' network vresus city identity
PublikacjaFundacja Solomona R. Guggenheima jest instytucją zajmującą się promowaniem współczesnej kultury wizualnej za pomocą organizowanych wystaw, badań, programów edukacyjnych oraz publikacji. Architektura obiektów wystawienniczych związanych z Fundacją, jest przedmiotem i zarazem pełni rolę środka promocji współczesnej sztuki. Status instytucji przewiduje globalną ekspansję, jednak dotychczas w gestii władz Fundacji znajdują się: siedziba...
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APPLICATION OF THE GWR MODEL FOR PREDICTING THE ROAD FATALITIES RATE ON THE ROAD NETWORK IN THE NUTS 3 REGIONS IN EUROPE ON THE EXAMPLE OF KUYAVIAN- -POMERANIAN VOIVODESHIP
PublikacjaThe article presents the application of the GWR (Geographically Weighted Regression) model to the description of differences in the level of road traffic safety in individual counties on the example of the Kuyavian-Pomeranian Voivodeship. The GWR model developed for counties, taking into account the diversity of NUTS 3 regions, can be a helpful tool for traffic safety management in voivodships and lower administrative units, and...
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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublikacjaTo successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublikacjaThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
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Cognitive motivations and foundations for building intelligent decision-making systems
PublikacjaConcepts based on psychology fit well with current research trends related to robotics and artificial intelligence. Biology-inspired cognitive architectures are extremely useful in building agents and robots, and this is one of the most important challenges of modern science. Therefore, the widely viewed and far-reaching goal of systems research and engineering is virtual agents and autonomous robots that mimic human behavior in...
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The role of EMG module in hybrid interface of prosthetic arm
PublikacjaNearly 10% of all upper limb amputations concern the whole arm. It affects the mobility and reduces the productivity of such a person. These two factors can be restored by using prosthetics. However, the complexity of human arm makes restoring its basic functions quite difficult. When the osseointegration and/or targeted muscle reinnervation (TMR) are not possible, different modalities can be used to control the prosthesis. In...
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Synergistic effect of nanoscale carbon black and ammonium polyphosphate on improving thermal stability and flame retardancy of polypropylene: A reactive network for strengthening carbon layer
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Correction: Synergistic effect of carbon fibers and carbon nanotubes on improving thermal stability and flame retardancy of polypropylene: a combination of a physical network and chemical crosslinking
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Central nervous system involvement in mantle cell lymphoma: clinical features, prognostic factors and outcomes from the European Mantle Cell Lymphoma Network†
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Partycypacja obywatelska młodzieży z perspektywy polskich i litewskich instytucji na przykładzie projektu South Baltic Youth Core Group Network
PublikacjaCelem artykułu było ukazanie partycypacji obywatelskiej młodzieży w opinii pracowników instytucji działających na terenie 5 polskich gmin: Dzierzgoń, Elbląg, Gdynia, Iława i Nowe Miasto Lubawskie i litewskiej gminy Teslai. W ramach projektu SB YCGN przeprowadzono badanie metodą sondażu diagnostycznego z wykorzystaniem techniki ankiety internetowej na 118 respondentach z 53 polskich instytucji i 47 respondentach z 10 litewskich...
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Data regarding a new, vector-enzymatic DNA fragment amplification-expression technology for the construction of artificial, concatemeric DNA, RNA and proteins, as well as biological effects of selected polypeptides obtained using this method
PublikacjaApplications of bioactive peptides and polypeptides are emerging in areas such as drug development and drug delivery systems. These compounds are bioactive, biocompatible and represent a wide range of chemical properties, enabling further adjustments of obtained biomaterials. However, delivering large quantities of peptide derivatives is still challenging. Several methods have been developed for the production of concatemers –...
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Using Long-Short term Memory networks with Genetic Algorithm to predict engine condition
PublikacjaPredictive 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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Zarządzanie (współzarządzanie) sieciowe i zarządzanie sieciami w wymiarze sprawiedliwości – wyzwania (15 stron) Governance network and networks governance in the justice system – challenges
PublikacjaCelem artykułu jest próba odpowiedzi na pytania czy w wymiarze sprawiedliwości jest miejsce i podstawa do wdrożenia zarządzania sieciowego (współzarządzania) oraz czy w działalności pomocniczej wymiaru sprawiedliwości istnieje potencjał do jego wdrożenia. W wymiarze sprawiedliwości istnieje duży potencjał do wykorzystania mechanizmów sieciowej współpracy. W ramach przestrzeni wymiaru sprawiedliwości współpraca międzyorganizacyjna...
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Policy Evaluation Network (PEN): Protocol for systematic literature reviews examining the evidence for impact of policies on physical activity across seven different policy domains
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Radioimmunotherapy with 90Y-ibritumomab tiuxetan is a safe and efficient treatment for patients with B-cell lymphoma relapsed after auto-SCT: an analysis of the international RIT-Network
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Neuronowa symulacja temperatury i ciśnienia pary w upuście parowego bloku energetycznego = Neural simulation of pressure and temperature fluctuations at steam extraction of power units with steam turbine
PublikacjaW artykule przedstawiono metodę symulacji neuronowej dla zastosowań w diagnostyce on-line bloków energetycznych. Model neuronowy opiera się na statycznych jednokierunkowych sieciach neuronowych (SSN) oraz na danych z parowego bloku energetycznego o mocy 200 MW. SSN obliczają wartości referencyjne parametrów cieplno-przepływowych dla aktualnego obciążenia obiektu. Określono wpływ architektury sieci i danych uczących na jakość symulacji...
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Analysis of Denoising Autoencoder Properties Through Misspelling Correction Task
PublikacjaThe paper analyzes some properties of denoising autoencoders using the problem of misspellings correction as an exemplary task. We evaluate the capacity of the network in its classical feed-forward form. We also propose a modification to the output layer of the net, which we called multi-softmax. Experiments show that the model trained with this output layer outperforms traditional network both in learning time and accuracy. We...
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The Use of an Autoencoder in the Problem of Shepherding
PublikacjaThis paper refers to the problem of shepherding clusters of passive agents consisting of a large number of objects by a team of active agents. The problem of shepherding and the difficulties that arise with the increasing number of data describing the location of agents have been described. Several methods for reducing the dimensionality of data are presented. Selected autoencoding method using a Restricted Boltzmann Machine is...
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Musical Instrument Identification Using Deep Learning Approach
PublikacjaThe work aims to propose a novel approach for automatically identifying all instruments present in an audio excerpt using sets of individual convolutional neural networks (CNNs) per tested instrument. The paper starts with a review of tasks related to musical instrument identification. It focuses on tasks performed, input type, algorithms employed, and metrics used. The paper starts with the background presentation, i.e., metadata...
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Video of LEGO Bricks on Conveyor Belt Dataset Series
PublikacjaThe dataset series titled Video of LEGO bricks on conveyor belt is composed of 14 datasets containing video recordings of a moving white conveyor belt. The recordings were created using a smartphone camera in Full HD resolution. The dataset allows for the preparation of data for neural network training, and building of a LEGO sorting machine that can help builders to organise their collections.
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Ionospheric scintillations computation using real-time GPS observations
PublikacjaThe following paper presents the results of quasi-real-time determination of the values of phase scintillations indices at the period of ionospheric disturbances that occurred as a consequence of the Sun flares observed on March 7 and 9, 2012. Double-frequency observations with 1-second measurement interval from the EPN (EUREF Permanent Network) network sites located at high latitudes were used for the analysis. To determine the phase...
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Classifying Emotions in Film Music - A Deep Learning Approach
PublikacjaThe paper presents an application for automatically classifying emotions in film music. A model of emotions is proposed, which is also associated with colors. The model created has nine emotional states, to which colors are assigned according to the color theory in film. Subjective tests are carried out to check the correctness of the assumptions behind the adopted emotion model. For that purpose, a statistical analysis of the...
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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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Automatic labeling of traffic sound recordings using autoencoder-derived features
PublikacjaAn approach to detection of events occurring in road traffic using autoencoders is presented. Extensions of existing algorithms of acoustic road events detection employing Mel Frequency Cepstral Coefficients combined with classifiers based on k nearest neighbors, Support Vector Machines, and random forests are used. In our research, the acoustic signal gathered from the microphone placed near the road is split into frames and converted...
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Współpraca patentowa nauki i biznesu na przykładzie województwa podkarpackiego – analiza sieci / Network analysis of patent cooperation between science and business - the case of Subcarpathian region
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TOWARDS EXPLAINABLE CLASSIFIERS USING THE COUNTERFACTUAL APPROACH - GLOBAL EXPLANATIONS FOR DISCOVERING BIAS IN DATA
PublikacjaThe paper proposes summarized attribution-based post-hoc explanations for the detection and identification of bias in data. A global explanation is proposed, and a step-by-step framework on how to detect and test bias is introduced. Since removing unwanted bias is often a complicated and tremendous task, it is automatically inserted, instead. Then, the bias is evaluated with the proposed counterfactual approach. The obtained results...
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Semantic segmentation training using imperfect annotations and loss masking
PublikacjaOne of the most significant factors affecting supervised neural network training is the precision of the annotations. Also, in a case of expert group, the problem of inconsistent data annotations is an integral part of real-world supervised learning processes, well-known to researchers. One practical example is a weak ground truth delineation for medical image segmentation. In this paper, we have developed a new method of accurate...
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublikacjaTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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A method of self-testing of analog circuits based on fully differential op-amps with theTCBF classifier
PublikacjaA new approach of self-testing of analog circuits based on fully differential op-amps of mixed-signal systems controlled by microcontrollers is presented. It consists of a measurement procedure and a fault diagnosis procedure. We measure voltage samples of a time response of a tested circuit on a stimulation of a unit step function given at the common-mode reference voltage input of the op-amp. The fault detection and fault localization...
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Corrigendum to “Synthesis and photoelectrochemical behaviour of hydrogenated titania nanotubes modified with conducting polymer infiltrated by redox active network” [Electrochim. Acta 222 (20 December) (2016) 1281–1292]
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Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
PublikacjaThe economic sustainability of aquifers across the world relies on accurate and rapid estimates of groundwater storage changes, but this becomes difficult due to the absence of insitu groundwater surveys in most areas. By closing the water balance, hydrologic remote sensing measures offer a possible method for quantifying changes in groundwater storage. However, it is uncertain to what extent remote sensing data can provide an...
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Assessment of Emotional Expressions after Full-Face Transplantation
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Application of autoencoder to traffic noise analysis
PublikacjaThe aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...
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Pose-Invariant Face Detection by Replacing Deep Neurons with Capsules for Thermal Imagery in Telemedicine
PublikacjaAbstract— The aim of this work was to examine the potential of thermal imaging as a cost-effective tool for convenient, non- intrusive remote monitoring of elderly people in different possible head orientations, without imposing specific behavior on users, e.g. looking toward the camera. Illumination and pose invariant head tracking is important for many medical applications as it can provide information, e.g. about vital signs, sensory...
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Orientation-aware ship detection via a rotation feature decoupling supported deep learning approach
PublikacjaShip imaging position plays an important role in visual navigation, and thus significant focuses have been paid to accurately extract ship imaging positions in maritime videos. Previous studies are mainly conducted in the horizontal ship detection manner from maritime image sequences. This can lead to unsatisfied ship detection performance due to that some background pixels maybe wrongly identified as ship contours. To address...
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User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning
PublikacjaIn this paper, the issue of detecting a user’s position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for...
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CNN Architectures for Human Pose Estimation from a Very Low Resolution Depth Image
PublikacjaThe paper is dedicated to proposing and evaluating a number of convolutional neural network architectures for calculating a multiple regression on 3D coordinates of human body joints tracked in a single low resolution depth image. The main challenge was to obtain a high precision in case of a noisy and coarse scan of the body, as observed by a depth sensor from a large distance. The regression network was expected to reason about...
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublikacjaBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
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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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Wstępne wyniki badań dostępności sieci ASG-Eupos podczas inwentaryzacji trasy kolejowej Kościerzyna - Kartuzy = Preliminary research results of ASG-Eupos network availability during surveying of Kościerzyna-Kartuzyrailway route
PublikacjaW artykule przedstawiono wyniki pomiarów dostępności określonej wartości błędu współrzędnych, wyznaczonych przy wykorzystaniu sieci ASG-EUPOS, uzyskane podczas pomiarów inwentaryzacyjnych testowego odcinka linii kolejowej. Pomiary z wykorzystaniem4 odbiorników GNSS przeprowadzono w miesiącu lutym bieżącego roku na odcinku trasy kolejowej Kościerzyna - Kartuzy. Program badań zakładał montaż, na pokładzie platformy kolejowej napędzanej...
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LSTM-based method for LOS/NLOS identification in an indoor environment
PublikacjaDue to the multipath propagation, harsh indoor environment significantly impacts transmitted signals which may adversely affect the quality of the radiocommunication services, with focus on the real-time ones. This negative effect may be significantly reduced (e.g. resources management and allocation) or compensated (e.g. correction of position estimation in radiolocalisation) by the LOS/NLOS identification algorithm. This paper...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublikacjaIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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Data augmentation for improving deep learning in image classification problem
PublikacjaThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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Optimized Computational Intelligence Model for Estimating the Flexural Behavior of Composite Shear Walls
PublikacjaThis article presents a novel approach to estimate the flexural capacity of reinforced concrete-filled composite plate shear walls using an optimized computational intelligence model. The proposed model was developed and validated based on 47 laboratory data points and the Transit Search (TS) optimization algorithm. Using 80% of the experimental dataset, the optimized model was selected by determining the unknown coefficients of...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublikacjaSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...