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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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Optimizing FSO networks resilient to adverse weather conditions by means of enhanced uncertainty sets
PublicationThis work deals with dimensioning of wireless mesh networks (WMN) composed of FSO (free space optics) links. Although FSO links realize broadband transmission at low cost, their drawback is sensitivity to adverse weather conditions causing transmission degradation on multiple links. Hence, designing such FSO networks requires an optimization model to find the cheapest configuration of link capacities that will be able to carry...
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Comparison of 3D Point Cloud Completion Networks for High Altitude Lidar Scans of Buildings
PublicationHigh altitude lidar scans allow for rapid acquisition of big spatial data representing entire city blocks. Unfortunately, the raw point clouds acquired by this method are largely incomplete due to object occlusions and restrictions in scanning angles and sensor resolution, which can negatively affect the obtained results. In recent years, many new solutions for 3D point cloud completion have been created and tested on various objects;...
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A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
PublicationThis article proposes the use of a feedforward neural network (FNN) to select the starting point for the first iteration in well-known iterative location estimation algorithms, with the research objective of finding the minimum size of a neural network that allows iterative position estimation algorithms to converge in an example positioning network. The selected algorithms for iterative position estimation, the structure of the...
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Wireless Link Selection Methods for Maritime Communication Access Networks—A Deep Learning Approach
PublicationIn recent years, we have been witnessing a growing interest in the subject of communication at sea. One of the promising solutions to enable widespread access to data transmission capabilities in coastal waters is the possibility of employing an on-shore wireless access infrastructure. However, such an infrastructure is a heterogeneous one, managed by many independent operators and utilizing a number of different communication...
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Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublicationRenal cell carcinoma is one of the most common cancers in Europe, with a total incidence rate of 18.4 cases per 100 000 population. There is currently significant overdiagnosis (11% to 30.9%) at times of planned surgery based on radiological studies. The purpose of this study was to create an artificial neural network (ANN) solution based on computed tomography (CT) images as an additional tool to improve the differentiation of...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublicationIn 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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New Alternative Passive Networks to Improve the Range Output Voltage Regulation of the PWM Inverters
PublicationThis paper presents different topologies of buck-boost converters with passive input networks that have alternative topologies; this is known in the literature as a Z-source inverter. Alternative passive networks were named by the authors as T-inverters; these improve output voltage regulation of the PWM inverters. T-inverter has fewer reactive components in comparison to conventional Z-source inverter. The most significant advantage...
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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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On the Usefulness of the Generalised Additive Model for Mean Path Loss Estimation in Body Area Networks
PublicationIn this article, the usefulness of the Generalised Additive Model for mean path loss estimation in Body Area Networks is investigated. The research concerns a narrow-band indoor off-body network operating at 2.45 GHz, being based on measurements performed with four different users. The mean path loss is modelled as a sum of four components that depend on path length, antenna orientation angle, absolute difference between transmitting...
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Development of cooperation in localized cooperation networks: A comparative study of cluster organizations and technology parks
PublicationThe main aim of the paper is to analyze the level of development of cooperative relationships in localized cooperation networks – among enterprises associated in cluster organizations and park tenants. The author reports the findings from the quantitative study carried out in the selected cluster organizations and technology parks functioning in Poland. The basic method of data collection was a survey questionnaire. The research...
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Networkig activities of general judiciary - from theory to practice
PublicationOver the last three decades, networks - as a field of research - have acquired a significant place among management sciences. Unfortunately, in the judiciary they have become a subject of more careful analyses only recently, which resulted in a large discrepancy of knowledge - both in theory and in its practical adaptation for the needs of the courts. In order to fill this cognitive gap, an attempt was made to identify levels of...
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Security Evaluation of IT Systems Underlying Critical Networked Infrastructures
PublicationCritical infrastructures have become highly dependent on information and communication technology (ICT). The drawback of this situation is that the consequences of disturbances of the underlying ICT networks may be serious as cascading effects can occur. This raises a high demand for security assurance, with a high importance assigned to security evaluations. In this paper we present an experiment-centric approach for the characterisation...
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On the Importance of Resilience Engineering for Networked Systems in a Changing World
PublicationResilience is featured increasingly often in the media, usually applied to society when faced, for example, with disasters such as flooding and the enormous challenges that the Covid-19 pandemic posed. There are now many resilience-related discussion groups worldwide, and some standards initiatives devoted in particular to city resilience. However, there is relatively little explicit interest in resilience engineering for communication...
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Application of Generalized Regression Neural Network and Gaussian Process Regression for Modelling Hybrid Micro-Electric Discharge Machining: A Comparative Study
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Burst loss probability for the combination of extended offset time based service differentiation scheme and PPS in optical burst switching network
PublicationIn the paper analytical model for calculating burst loss probabilities for the combination of two service differentiation schemes for OBS network namely: extended offset time based scheme and PPS (Preemption Priority Schemes) is revised. Moreover authors introduce analytical model for calculating burst loss probabilities for an optical path when OBS network employs both service differentiation schemes and JET signaling. The comparison...
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Prediction of skin color, tanning and freckling from DNA in Polish population: linear regression, random forest and neural network approaches
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Artificial neural network model of hardness, porosity and cavitation erosion wear of APS deposited Al2O3 -13 wt% TiO2 coatings
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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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Partycypacja obywatelska młodzieży w opinii gmin polskich na przykładzie projektu South Baltic Youth Core Group Network
PublicationCelem badań było ukazanie partycypacji obywatelskiej młodzieży w opinii gmin polskich na przykładzie projektu South Baltic Youth Core Group Network
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The significance of institutions' potential to increase Youth civic participation – case study of the South Baltic Youth Core Groups Network Project
PublicationYoung people are a very important group of modern societies, they will replace the currently ruling generation and will shape our common future. Due to that, young people have become the relevant target of national and international policy and science researches. Youth civic participation is a key aspect of the development of a society and should be shaped by effective youth policy at the national and international levels. This...
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Personalized nutrition in ageing society: redox control of major-age related diseases through the NutRedOx Network (COST Action CA16112)
PublicationA healthy ageing process is important when it is considered that one-third of the population of Europe is already over 50 years old, although there are regional variations. This proportion is likely to increase in the future, and maintenance of vitality at an older age is not only an important measure of the quality of life but also key to participation and productivity. So, the binomial “nutrition and ageing” has different aspects...
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Recurrent Neural Network Based Adaptive Variable-Order Fractional PID Controller for Small Modular Reactor Thermal Power Control
PublicationThis paper presents the synthesis of an adaptive PID type controller in which the variable-order fractional operators are used. Due to the implementation difficulties of fractional order operators, both with a fixed and variable order, on digital control platforms caused by the requirement of infinite memory resources, the fractional operators that are part of the discussed controller were approximated by recurrent neural networks...
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Energy Management for PV Powered Hybrid Storage System in Electric Vehicles Using Artificial Neural Network and Aquila Optimizer Algorithm
PublicationIn an electric vehicle (EV), using more than one energy source often provides a safe ride without concerns about range. EVs are powered by photovoltaic (PV), battery, and ultracapacitor (UC) systems. The overall results of this arrangement are an increase in travel distance; a reduction in battery size; improved reaction, especially under overload; and an extension of battery life. Improved results allow the energy to be used efficiently,...
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Związki endokrynne w środowisku. Problemy i wyzwania cz. I Emisja i los środowiskowy
PublicationWzrost świadomości dotyczącej niekorzystnego wpływu działalności człowieka na stan środowiska oraz dynamiczny rozwój technik analitycznych spowodował, że w ostatnich latach wzrosło zainteresowanie problematyką związków zakłócających prawidłowe funkcjonowanie układu endokrynnego. W opracowaniu zamieszczono informacje o niektórych związkach z grupy estrogenów, ich losie środowiskowym oraz oddziaływaniu na organizmy żywe.
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Classification of objects in the LIDAR point clouds using Deep Neural Networks based on the PointNet model
PublicationThis 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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Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural Networks
PublicationEstimation 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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Formation of Protein Networks between Mucins: Molecular Dynamics Study Based on the Interaction Energy of the System
PublicationMolecular dynamics simulations have been performed for a model aqueous solution of mucin. As mucin is a central part of lubricin, a key component of synovial fluid, we investigate its ability to form cross-linked networks. Such network formation could be of major importance for the viscoelastic properties of the soft-matter system and crucial for understanding the lubrication mechanism in articular cartilage. Thus,the inter- and...
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Evidence-Based Risk Management for Civil Engineering Projects Using Bayesian Belief Networks (BBN)
PublicationThe authors are seeking new methods for improving the efficiency of the investments associated with the maintenance and operation of existing civil engineering structures. It is demonstrated how the knowledge about the elements of construction and operation phases and their relationships, combined with monitoring data can be used for more effective management of the risks associated with civil engineering projects. The methodology...
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Assessment of Therapeutic Progress After Acquired Brain Injury Employing Electroencephalography and Autoencoder Neural Networks
PublicationA method developed for parametrization of EEG signals gathered from participants with acquired brain injuries is shown. Signals were recorded during therapeutic session consisting of a series of computer assisted exercises. Data acquisition was performed in a neurorehabilitation center located in Poland. The presented method may be used for comparing the performance of subjects with acquired brain injuries (ABI) who are involved...
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Determination of Odour Interactions in Gaseous Mixtures Using Electronic Nose Methods with Artificial Neural Networks
PublicationThis paper presents application of an electronic nose prototype comprised of eight sensors, five TGS-type sensors, two electrochemical sensors and one PID-type sensor, to identify odour interaction phenomenon in two-, three-, four- and five-component odorous mixtures. Typical chemical compounds, such as toluene, acetone, triethylamine, α-pinene and n-butanol, present near municipal landfills and sewage treatment plants were subjected...
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INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublicationIn 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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Deep neural networks for human pose estimation from a very low resolution depth image
PublicationThe 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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A novel genetic approach to provide differentiated levels of service resilience in IP-MPLS/WDM networks
PublicationThis paper introduces a novel class-based method of survivable routing for connection-oriented IP-MPLS/WDM networks, called MLS-GEN-H. The algorithm is designed to provide differentiated levels of service survivability in order to respond to varying requirements of end-users. It divides the complex problem of survivable routing in IP-MPLS/WDM networks into two subproblems, one for each network layer, which enables finding the...
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SNAIL Promotes Metastatic Behavior of Rhabdomyosarcoma by Increasing EZRIN and AKT Expression and Regulating MicroRNA Networks
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Efficient handover scheme for Mobile IPv4 over IEEE 802.11 networks with IEEE 802.21 triggers.
PublicationEfektywność przełączania jest bardzo istotnym parametrem, decydującym o pracy sieci bezprzewodowych, realizujacych usługi multimedialne na wysokim poziomie jakości. Użytkownicy takich sieci oczekują ciągłej obsługi podczas procesu przemieszczania się. Okazuje się, że istotnym źródlem opóźnień są nieefektywne procedury przełączania w warstwach drugiej i trzeciej, wynikający częściowo z postulatu o separacji funkcji realizowanych...
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Multiservice Optical Fibre Local Area Networks For Data Transmission And Telemetry In The Electric Power Industry
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A novel class-based protection algorithm providing fast service recovery in IP/WDM networks
PublicationW artykule rozważa się warstwową strukturę sieci IP-MPLS/WDM. Węzły sieci mają funkcjonalność zarówno optycznych krotnic transferowych (OXC), jak i routerów IP. Dowolne dwa routery IP mogą być ze sobą połączone poprzez logiczne łącze IP realizowane przez ścieżkę optyczną WDM. Zaproponowano metodę klasową doboru tras przeżywalnych zapewniającą szybkie odtwarzanie uszkodzonych strumieni ruchu zarówno w warstwie WDM jak i IP-MPLS....
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Deformation Analysis of Geodetic Networks by Applying M split Estimation with Conditions Binding the Competitive Parameters
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Set membership estimation of parameters and variables in dynamic networks by recursive algorithms with moving measurment window
PublicationW artykule rozważana jest łączna estymacja przedziałowa zmiennych i parametrów w złożonej sieci dynamicznej w oparciu niepewne modele parametryczne i ograniczoną liczbę pomiarów. Opracowany został rekursywny algorytm estymacji z przesuwnym oknem pomiarowym, odpowiedni dla monitorowania sieci on-line. Okno pomiarowe pozwala na stabilizowanie klasycznego algorytmu rekurencyjnego estymacji i znacznie poprawienie obcisłości estymat....
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Testbed analysis of video and VoIP transsmission performance in IEEE 802.11 b/g/n networks
PublicationThe aim of the work is to analyze capabilities and limitations of different implementations of IEEE 802.11 technologies (IEEE 802.11 b/g/n), utilized for both video streaming and VoIP calls directed to mobile devices. Our preliminary research showed that results obtained with currently popular simulation tools can be drastically different than these possible in real-world environment, so, in order to correctly evaluate performance...
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Quantum superadditivity in linear optics networks: Sending bits via multiple-access Gaussian channels
PublicationSuperadditivity effects of communication capacities are known in the case of discrete variable quantum channels. We describe the continuous variable analog of one of these effects in the framework of Gaussian multiple access channels (MACs). Classically, superadditivity-type effects are strongly restricted: For example, adding resources to one sender is never advantageous to other senders in sending their respective information...
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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublicationABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest...
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Long-distance quantum communication over noisy networks without long-time quantum memory
PublicationThe problem of sharing entanglement over large distances is crucial for implementations of quantum cryptography. A possible scheme for long-distance entanglement sharing and quantum communication exploits networks whose nodes share Einstein-Podolsky-Rosen (EPR) pairs. In Perseguers et al. [Phys. Rev. A 78, 062324 (2008)] the authors put forward an important isomorphism between storing quantum information in a dimension D and transmission...
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Efficient Usage of Dense GNSS Networks in Central Europe for the Visualization and Investigation of Ionospheric TEC Variations
PublicationThe technique of the orthogonal projection of ionosphere electronic content variations for mapping total electron content (TEC) allows us to visualize ionospheric irregularities. For the reconstruction of global ionospheric characteristics, numerous global navigation satellite system (GNSS) receivers located in different regions of the Earth are used as sensors. We used dense GNSS networks in central Europe to detect and investigate...
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Nodal cooperation equilibrium analysis in multi-hop wireless ad hoc networks with a reputation system
PublicationMotivated by the concerns of cooperation security, this work examines selected principles of state-of-the-art reputation systems for multi-hop ad hoc networks and their impact upon optimal strategies for rational nodes. An analytic framework is proposed and used for identification of effective cooperation-enforcement schemes. It is pointed out that optimum rather than high reputation can be expected to be sought by rational nodes.
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Application of Bayesian Networks in risk diagnostics arising from the degree of urban regeneration area degradation
PublicationUrban regeneration as a complex project, generates many extremely specific threats affecting the increase of investment risk. Its unique nature causes that probability parameter, normally applied in the process of risk quantification, is extremely difficult to estimate. Due to lack of historical data urban regeneration related activities are therefore associated with uncertainty. According to the authors, a useful tool for resolving...
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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublicationThe article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...
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Optimum Choice of Randomly Oriented Carbon Nanotube Networks for UV-Assisted Gas Sensing Applications
PublicationWe investigated the noise and photoresponse characteristics of various optical transparencies of nanotube networks to identify an optimal randomly oriented network of carbon nanotube (CNT)-based devices for UV-assisted gas sensing applications. Our investigation reveals that all of the studied devices demonstrate negative photoconductivity upon exposure to UV light. Our studies confirm the effect of UV irradiation on the electrical...