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Deep neural networks approach to skin lesions classification — A comparative analysis
PublicationThe paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...
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A Novel Bitrate Adaptation Method for Heterogeneous Wireless Body Area Networks
PublicationIn the article, a novel bitrate adaptation method for data streams allocation in heterogeneous Wireless Body Area Networks (WBANs) is presented. The efficiency of the proposed algorithm was compared with other known algorithms of data stream allocation using computer simulation. A dedicated simulator has been developed using results of measurements in the real environment. The usage of the proposed adaptive data streams allocation...
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An Off-Body Channel Model for Body Area Networks in Indoor Environments
PublicationThis paper presents an off-body channel model for body area networks (BANs) in indoor environments. The proposed model, which is based on both simulations and measurements in a realistic environment, consists of three components: mean path loss, body shadowing, and multipath fading. Seven scenarios in a realistic indoor office environment containing typical scatterers have been measured: five were static (three standing and two...
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Adaptive prediction of stock exchange indices by state space wavelet networks
PublicationThe paper considers the forecasting of the Warsaw Stock Exchange price index WIG20 by applying a state space wavelet network model of the index price. The approach can be applied to the development of tools for predicting changes of other economic indicators, especially stock exchange indices. The paper presents a general state space wavelet network model and the underlying principles. The model is applied to produce one session...
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The reliability of any-hop star networks with respect to failures of communication nodes.
PublicationThis paper investigated the reliability of any-hop star networks. The any-hop star topology is used in centralized computer networks. We will assume that the all nodes fail independently, links are failure-free. Following measures of network reliability are assumed: the expected number of nodes, which can communicate with the central node; the expected number of node pairs, which are connected by a path through the central node;...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublicationIn 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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Local variance factors in deformation analysis of non-homogenous monitoring networks
PublicationThis paper proposes a modification of the classical deformation analysis algorithm for non-homogeneous (e.g. linear-angular) monitoring networks. The basis for the proposed solution is the idea of local variance factors. The theoretical discussion was complemented with an example of its application on a simulated horizontal monitoring network. The obtained results confirm the usefulness of the proposed solution.
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THE USE OF GNSS GEODETIC NETWORKS ON THE APPROACH TO THE PORTS � GULF OF GDANSK STUDY
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Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublicationThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
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Applying artificial neural networks for modelling ship speed and fuel consumption
PublicationThis paper deals with modelling ship speed and fuel consumption using artificial neural network (ANN) techniques. These tools allowed us to develop ANN models that can be used for predicting both the fuel consumption and the travel time to the destination for commanded outputs (the ship driveline shaft speed and the propeller pitch) selected by the ship operator. In these cases, due to variable environmental conditions, making...
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Trust-Based Model for the Assessment of the Uncertainty of Measurements in Hybrid IoT Networks
PublicationThe aim of this paper is to introduce a NUT model (NUT: network-uncertainty-trust) that aids the decrease of the uncertainty of measurements in autonomous hybrid Internet of Things sensor networks. The problem of uncertainty in such networks is a consequence of various operating conditions and varied quality of measurement nodes, making statistical approach less successful. This paper presents a model for decreasing the uncertainty...
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Application of the neural networks for developing new parametrization of the Tersoff potential for carbon
PublicationPenta-graphene (PG) is a 2D carbon allotrope composed of a layer of pentagons having sp2- and sp3-bonded carbon atoms. A study carried out in 2018 has shown that the parameterization of the Tersoff potential proposed in 2005 by Ehrhart and Able (T05 potential) performs better than other potentials available for carbon, being able to reproduce structural and mechanical properties of the PG. In this work, we tried to improve the...
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Application of Artificial Neural Networks to Predict Insulation Properties of Lightweight Concrete
PublicationPredicting the properties of concrete before its design and application process allows for refining and optimizing its composition. However, the properties of lightweight concrete are much harder to predict than those of normal weight concrete, especially if the forecast concerns the insulating properties of concrete with artificial lightweight aggregate (LWA). It is possible to use porous aggregates and precisely modify the composition...
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Influence of User Mobility and Antenna Placement on System Loss in B2B Networks
PublicationIn this paper, the influence of user mobility and on-body antenna placement on system loss in body-to-body communications in indoor and outdoor environments and different mobility scenarios is studied, based on system loss measurements at 2.45 GHz. The novelty of this work lies on the proposal of a classification model to characterise the effect of user mobility and path visibility on system loss, allowing to identify the best...
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Mitigating Traffic Remapping Attacks in Autonomous Multi-hop Wireless Networks
PublicationMultihop wireless networks with autonomous nodes are susceptible to selfish traffic remapping attacks (TRAs). Nodes launching TRAs leverage the underlying channel access function to receive an unduly high Quality of Service (QoS) for packet flows traversing source-to-destination routes. TRAs are easy to execute, impossible to prevent, difficult to detect, and harmful to the QoS of honest nodes. Recognizing the need for providing...
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Routing Method for Interplanetary Satellite Communication in IoT Networks Based on IPv6
PublicationThe matter of interplanetary network (IPN) connection is a complex and sophisticated topic. Space missions are aimed inter alia at studying the outer planets of our solar system. Data transmission itself, as well as receiving data from satellites located on the borders of the solar system, was only possible thanks to the use of powerful deep space network (DSN) receivers, located in various places on the surface of the Earth. In...
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublicationArtificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...
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Modeling of Surface Roughness in Honing Processes by UsingFuzzy Artificial Neural Networks
PublicationHoning processes are abrasive machining processes which are commonly employed to improve the surface of manufactured parts such as hydraulic or combustion engine cylinders. These processes can be employed to obtain a cross-hatched pattern on the internal surfaces of cylinders. In this present study, fuzzy artificial neural networks are employed for modeling surface roughness parameters obtained in finishing honing operations. As...
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An Automated Method for Biometric Handwritten Signature Authentication Employing Neural Networks
PublicationHandwriting biometrics applications in e-Security and e-Health are addressed in the course of the conducted research. An automated graphomotor analysis method for the dynamic electronic representation of the handwritten signature authentication was researched. The developed algorithms are based on dynamic analysis of electronically handwritten signatures employing neural networks. The signatures were acquired with the use of the...
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Face with Mask Detection in Thermal Images Using Deep Neural Networks
PublicationAs the interest in facial detection grows, especially during a pandemic, solutions are sought that will be effective and bring more benefits. This is the case with the use of thermal imaging, which is resistant to environmental factors and makes it possible, for example, to determine the temperature based on the detected face, which brings new perspectives and opportunities to use such an approach for health control purposes. The...
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A Novel Bitrate Adaptation Method for Heterogeneous Wireless Body Area Networks
PublicationIn the article, a novel bitrate adaptation method for data streams allocation in heterogeneous Wireless Body Area Networks (WBANs) is presented. The efficiency of the proposed algorithm was compared with other known algorithms of data stream allocation using computer simulation. A dedicated simulator has been developed using results of measurements in the real environment. The usage of the proposed adaptive data streams allocation...
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Bees Detection on Images: Study of Different Color Models for Neural Networks
PublicationThis 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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Diffusion equations with spatially dependent coefficients and fractal Cauer-type networks
PublicationIn this article, we formulate and solve the representation problem for diffusion equations: giving a discretization of the Laplace transform of a diffusion equation under a space discretization over a space scale determined by an increment h > 0, can we construct a continuous in h family of Cauer ladder networks whose constitutive equations match for all h > 0 the discretization. It is proved that for a finite differences discretization...
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Role of miR-15b/16–2 cluster network in endometrial cancer: An in silico pathway and prognostic analysis
PublicationEndometrial cancer (EC) is the second most common cancer in women. A large number of human cancers exhibit dysregulation of microRNA expression including EC. MiR-15b/16–2 is one of the best-known miRNA clusters that is expressed in many types of cancer tissues. Herein, we analyzed the expression of individual miR-15b/16–2 cluster members, its paralogues, and their target network analysis, as well as their prognostic significance...
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Role of miR-15b/16–2 cluster network in endometrial cancer: An in silico pathway and prognostic analysis
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<title>Recurrent neural network application to image filtering: 2-D Kalman filtering approach</title>
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Designing of an effective structure of system for the maintenance of a technical object with the using information from an artificial neural network
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Interdyscyplinary collaboration of Polish universities. The case of egocentric network analysis of the West Pomeranian University of Technology in Szczecin
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CLEPSYDRA Data Aggregation and Enrichment Framework: Design, Implementation and Deployment in the PIONIER Network Digital Libraries Federation
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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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Method to solve the non-linear systems of equations for steady gradually varied flow in open channel network.
PublicationW artykule omówiono rozwiązanie systemu równań nieliniowych opisujacych przepływ ustalony wolnozmienny w sieci kanałów otwartych. Niewiadomymi są glębokości w poszczególnych przekrojach oraz natężenia przepływów w poszczególnych gałęziach systemu. Układ musi być rozwiązywany iteracyjnie. Klasyczne metody Picarda i Newtona mogą okazać się nieskuteczne ze względu na oscylacje rozwiązania w kolejnych iteracjach i związany z tym brak...
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The pollutant transport equation for a steady, gradually varied flow in an open channel network: a solution of high accuracy
PublicationW pracy przedstawiono metodę rozwiązania jednowymiarowego równania adwekcji-dyfuzji opisującego transport zanieczyszczeń w warunkach przepływu ustalonego wolnozmiennego w sieci kanałów otwartych. Zastosowano technikę dekompozycji. Zlineoryzowane równanie adwekcji-dyfuzji rozwiązano stosując całkę Duhamela, zaś równanie zacierające człon źródłowy-metodą różnic skończonych. Metoda zapewnia bardzo dużą dokładność rozwiązania nawet...
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Pedestrian protection, speed enforcement and road network structure the key action for implementing Poland's Vision Zero
PublicationSince 1991 Poland's road safety has been systematically improving with a 60% reduction in road deaths. Despite the progress Poland continues to be one of the European Union' worst performing countries. The country's main road safety problems remain unchanged: dangerous behaviour of road users, underdeveloped system of road safety management and low quality of road infrastructure. This is why subsequent road safety programmes (implemented...
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Synthesis and photoelectrochemical behaviour of hydrogenated titania nanotubes modified with conducting polymer infiltrated by redox active network
PublicationIn this work, we show preparation of ordered inorganic-organic composite electrode material where hydrogenated titania nanotubes H-TiO2 with tubularly developed surface modified with poly(3,4-ethylenedioxythiophene) matrix permeated by Prussian Blue (PB) inorganic redox network in order to reach highly photoactive heterojunction. The polymer deposition was realized via two subsequent processes covering: i) potentiostatic polymerization...
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Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network
PublicationCOVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublicationWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this objective...
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Mutual Coupling Reduction in Antenna Arrays Using Artificial Intelligence Approach and Inverse Neural Network Surrogates
PublicationThis paper presents a novel approach to reduce undesirable coupling in antenna arrays using custom-designed resonators and inverse surrogate modeling. To illustrate the concept, two stand-ard patch antenna cells with 0.07λ edge-to-edge distance are designed and fabricated to operate at 2.45 GHz. A stepped-impedance resonator is applied between the antennas to suppress their mutual coupling. For the first time, the optimum values...
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New Two-center Ellipsoidal Basis Function Neural Network for Fault Diagnosis of Analog Electronic Circuits
PublicationIn the paper a new fault diagnosis-oriented neural network and a diagnostic method for localization of parametric faults in Analog Electronic Circuits (AECs) with tolerances is presented. The method belongs to the class of dictionary Simulation Before Test (SBT) methods. It utilizes dictionary fault signatures as a family of identification curves dispersed around nominal positions by component tolerances of the Circuit Under Test...
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublicationWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this...
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The mechanisms of technological innovation in SMEs: a Bayesian Network Analysis of EU regional policy impact on Polish firms.
PublicationWe study the underlying mechanisms of technological innovation in SMEs in the context of ex-post evaluation of European Union’s regional policy. Our aim is to explain the observed change in firms’ innovativeness after receiving EU support for technological investment. To do so, we take an approach that is novel in innovation studies: a Bayesian Network Analysis to assess the effectiveness of EU policy instrument for technological...
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Multipath routing for quality of service differentiation and network capacity optimization in broadband low-earth orbit systems
PublicationThis paper shows the importance of employing multiple different paths for routing in Inter-Satellite Link (ISL) networks in broadband Low-Earth Orbit (LEO) satellite systems. A theoretical analysis is presented and a routing concept is proposed to demonstrate three facts that make multipath routing especially important in broadband LEO networks: (1) differences in the propagation delays have a much greater impact on end-to-end...
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Rapid Design Tuning of Miniaturized Rat-Race Couplers Using Regression-Based Equivalent Network Surrogates
PublicationA simple technique for fast design tuning of compact rat-race couplers is presented. Our approach involves equivalent circuit representation, corrected by nonlinear functions of frequency with coefficients extracted through nonlinear regression. At the same time, the tuning process connects two levels of coupler representation: EM simulation of the entire circuit and re-optimization of the coupler building blocks (slow-wave cells...
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Bilateral power supply of the traction network as a first stage of Smart Grid technology implementation in electric traction
PublicationSince 2001, trolleybus system in Gdynia has been involved in many activities related to the reduction of power consumption, both in terms of implementation and research and development. In PKT, in cooperation with SESTO company, started applications of Smart Grid technologies in supply network: the bilateral supply. The paper presents results of this this novel investment.
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Biotrickling filtration of n-butanol vapors: process monitoring using electronic nose and artificial neural network
PublicationBiotrickling filtration is one of the techniques used to reduce odorants in the air. It is based on the aerobic degradation of pollutants by microorganisms located in the filter bed. The research presents the possibility of using the electronic nose prototype combined with artificial neural network for biofiltration process monitoring in terms of reduction in n-butanol concentration and odour intensity of treated air. The study...
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A reactive algorithm for deducing nodal forwarding behavior in a multihop ad-hoc wireless network in the presence of errors
PublicationA novel algorithm is presented to deduce individual nodal forwarding behavior from standard end-to-end acknowledgments. The algorithm is based on a well-established mathematical method and is robust to network related errors and nodal behavior changes. The proposed solution was verified in a network simulation, during which it achieved sound results in a challenging multihop ad-hoc network environment.
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Real‐Time PPG Signal Conditioning with Long Short‐Term Memory (LSTM) Network for Wearable Devices
PublicationThis paper presents an algorithm for real‐time detection of the heart rate measured on a person’s wrist using a wearable device with a photoplethysmographic (PPG) sensor and accelerometer. The proposed algorithm consists of an appropriately trained LSTM network and the Time‐Domain Heart Rate (TDHR) algorithm for peak detection in the PPG waveform. The Long Short‐Term Memory (LSTM) network uses the signals from the accelerometer...
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Generalized regression neural network and fitness dependent optimization: Application to energy harvesting of centralized TEG systems
PublicationThe 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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Relay-aided Wireless Sensor Network Discovery Algorithm for Dense Industrial IoT utilizing ESPAR Antennas
PublicationIndustrial Internet of Things (IIoT) applicationsrequire reliable and efficient wireless communication. Assumingdense Wireless Sensor Networks (WSNs) operating in a harshenvironment, a concept of a Time Division Multiple Access(TDMA) based WSN enriched with Electronically SteerableParasitic Array Radiator (ESPAR) antennas is proposed andexamined in this work. The utilized...
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Cross-layer integration of network mechanisms for increasing efficiency of multimedia session support in IEEE 802.11s environment
PublicationWith an IEEE 802.11 wireless networks operating in Point-to-Multipoint mode being the most popular WLAN access technology employed today, it can be expected that a Wireless Mesh Network (WMN) based on the technology can provide significant advantages for such network systems. The IEEE 802.11s standard amendment provides the comprehensive set of mechanisms required to implement and deploy a WMN utilizing this widely popular technology....
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Effect of User Mobility upon Trust Building among Autonomous Content Routers in an Information-Centric Network
PublicationThe capability of proactive in-network caching and sharing of content is one of the most important features of an informationcentric network (ICN). We describe an ICN model featuring autonomous agents controlling the content routers. Such agents are unlikely to share cached content with other agents without an incentive to do so. To stimulate cooperation between agents, we adopt a reputation and trust building scheme that is able...