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Wyniki wyszukiwania dla: APPROXIMATION METHODS, FRACTIONAL CALCULUS, MODELING, NEURAL NETWORKS, RECURRENT NEURAL NETWORKS
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Practical Trial for Low-Energy Effective Jamming on Private Networks With 5G-NR and NB-IoT Radio Interfaces
PublikacjaFourth-generation (4G) mobile networks are successively replaced by fifth-generation (5G) ones, based on the new releases of the 3rd Generation Partnership Project (3GPP) standard. 5G generation is dedicated to civilian users and the conducted analytical work shows that it has numerous technological gaps that prevent its direct implementation in military communications systems. However, the recent armed world conflicts showed that...
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Fault diagnosing system of wheeled tractors
PublikacjaA defect of complex wheeled tractor assembles most frequently negative influence on exploitation efficiency, safety and exhaust gases emission. Structure complexity of wheeled tractors requires more and more advanced diagnostic methods for identification of their serviceable possibilities as well in manufacturing step as in exploitation. In classical diagnosing methods of wheeled tractor defects states mapping by measured diagnostic...
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Cost-Efficient Surrogate Modeling of High-Frequency Structures Using Nested Kriging with Automated Adjustment of Model Domain Lateral Dimensions
PublikacjaSurrogate models are becoming popular tools of choice in mitigating issues related to the excessive cost of electromagnetic (EM)-driven design of high-frequency structures. Among available techniques, approximation modeling is by far the most popular due to its versatility. In particular, the surrogates are exclusively based on the sampled simulation data with no need to involve engineering insight or problem-specific knowledge....
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Glacial Landform Classification with Vision Transformer and Digital Elevation Model
PublikacjaClassification of glacial landforms is a task in geomorphology that has not been widely explored with deep neural network methods. This study uses Vision Transformer (ViT) architecture to classify glacial landforms using Digital Elevation Model (DEM) in three study sites: Elise Glacier in Svalbard, Norway; Gardno-Leba Plain and Lubawa Upland in Poland. In datasets each of those sites has different DEM resolutions and terrain types...
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Towards Cancer Patients Classification Using Liquid Biopsy
PublikacjaLiquid biopsy is a useful, minimally invasive diagnostic and monitoring tool for cancer disease. Yet, developing accurate methods, given the potentially large number of input features, and usually small datasets size remains very challenging. Recently, a novel feature parameterization based on the RNA-sequenced platelet data which uses the biological knowledge from the Kyoto Encyclopedia of Genes and Genomes, combined with a classifier...
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New trends in development of micro heat exchangers for ORC's
PublikacjaIn the paper, new trends in development of micro heat exchangers for CHP are presented. Main attention is concentrated on the question, how channels size and thermal development lenght affect the heat transfer. New types of micro heat exchangers developed at the Institute of Fluid-Flow Machinery PAS and the methoda of their design are presented. The new experimental testing methods of the micro-channel heat exchangers, new algorithms...
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GNSS INVENTORY OF HISTORIC NARROW-GAUGE RAILWAY LINE IN KOSZALIN UNDER EXTREMELY UNFAVORABLE MEASUREMENTS CONDITIONS FROM THE POINT OF VIEW OF SATELLITE SIGNALS AVAILABILITY
PublikacjaA team of academic researchers from the Gdańsk University of Technology, Gdynia Maritime University and the Polish Naval Academy have been working since 2009 on the methodology of using active GNSS geodetic networks for geodetic inventory of railways and on adapting this measurement technique for designing geometric layouts of railway and tram lines. Over the years, the team tested a variety of configurations of receivers and settings...
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A Development of a Capacitive Voltage Divider for High Voltage Measurement as Part of a Combined Current and Voltage Sensor
PublikacjaThis article deals with the development of capacitive voltage divider for high voltage measurements and presents a method of analysis and optimization of its parameters. This divider is a part of a combined voltage and current sensor for measurements in high voltage power networks. The sensor allows continuous monitoring of the network distribution status and performs a quick diagnosis and location of possible network failures....
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Rapid Design of 3D Reflectarray Antennas by Inverse Surrogate Modeling and Regularization
PublikacjaReflectarrays (RAs) exhibit important advantages over conventional antenna arrays, especially in terms of realizing pencil-beam patterns without the employment of the feeding networks. Unfortunately, microstrip RA implementations feature narrow bandwidths, and are severely affected by losses. A considerably improved performance can be achieved for RAs involving grounded dielectric layers, which are also easy to manufacture using...
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INVESTIGATION OF THE LOMBARD EFFECT BASED ON A MACHINE LEARNING APPROACH
PublikacjaThe Lombard effect is an involuntary increase in the speaker’s pitch, intensity, and duration in the presence of noise. It makes it possible to communicate in noisy environments more effectively. This study aims to investigate an efficient method for detecting the Lombard effect in uttered speech. The influence of interfering noise, room type, and the gender of the person on the detection process is examined. First, acoustic parameters...
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Consciousness Study of Subjects with Unresponsive Wakefulness Syndrome Employing Multimodal Interfaces
PublikacjaThe paper presents a novel multimodal-based methodology for consciousness study of individuals with unresponsive wakefulness syndrome. Two interfaces were employed in the experiments: eye gaze tracking system – CyberEye developed at the Multimedia Systems Department, and EEG device with electrode placement in the international 10-20 standard. It was a pilot study for checking if it is possible to determine objective methods based...
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MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences
Publikacja—Machine Learning (ML) methods have been used with varying degrees of success on protein prediction tasks, with two inherent limitations. First, prediction performance often depends upon the features extracted from the proteins. Second, experimental data may be insufficient to construct reliable ML models. Here we introduce MP3vec, a transferable representation for protein sequences that is designed to be used specifically for sequence-to-sequence...
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Dynamic GPU power capping with online performance tracing for energy efficient GPU computing using DEPO tool
PublikacjaGPU accelerators have become essential to the recent advance in computational power of high- performance computing (HPC) systems. Current HPC systems’ reaching an approximately 20–30 mega-watt power demand has resulted in increasing CO2 emissions, energy costs and necessitate increasingly complex cooling systems. This is a very real challenge. To address this, new mechanisms of software power control could be employed. In this...
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublikacjaIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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total number and biomass of bacteria in drinking water distribution systems.
PublikacjaIn the vast water supply network using traditional methods of treatment it is often impossible to maintain a constant and acceptable microbiological quality of water. In Poland the main reason of bacterial re-growth is presence of organic matter and nutrients in the circulating water and prolonged water retention in the network systems due to the decrease of water consumption, which has been observed for the last 20 years. In the...
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Improving the Survivability of Carrier Networks to Large-Scale Disasters
PublikacjaThis chapter is dedicated to the description of methods aiming to improve the survivability of carrier networks to large-scale disasters. First, a disaster classification and associated risk analysis is described, and the disaster-aware submarine fibre-optic cable deployment is addressed aiming to minimize the expected costs in case of natural disasters. Then, the chapter addresses the improvement of the network connectivity resilience...
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublikacjaThis chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...
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Dimensionality-Reduced Antenna Modeling with Stochastically Established Constrained Domain
PublikacjaOver the recent years, surrogate modeling methods have become increasingly widespread in the design of contemporary antenna systems. On the one hand, it is associated with a growing awareness of numerical optimization, instrumental in achieving high-performance structures. On the other hand, considerable computational expenses incurred by massive full-wave electromagnetic (EM) analyses, routinely employed as a major design tool,...
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublikacjaForecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...
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REAL-TIME VOICE QUALITY MONITORING TOOL FOR VOIP OVER IPV6 NETWORKS
PublikacjaThe primary aim of this paper is to present a new application which is at this moment the only open source real-time VoIP quality monitoring tool that supports IPv6 networks. The application can keep VoIP system administrators provided at any time with up-to-date voice quality information. Multiple quality scores that are automatically obtained throughout each call reflect influence of variable packet losses and delays on voice...
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Mobility Management Solutions for IP Networks Comparative Analysis of IP-based Mobility Protocols and Handover Algorithms Invited Paper
PublikacjaA rapid growth of IP-based networks and services hascreated a vast collection of resources and functionalities availableto users by means of a uniform method of access offered by the IPprotocol. At the same time, advances in the design of mobileelectronic devices allowed them to reach a utility levelcomparable to desktop computers, while still retaining theirmobility advantage. Unfortunately, the base IP protocol does notperform...
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Optimal selection of input features and an acompanying neural network structure for the classification purposes - skin lesions case study
PublikacjaMalignant melanomas are the most deadly type of skin cancers however detected early enough give a high chances for successful treatment. The last years saw the dynamic growth of interest of automatic computer-aided skin cancer diagnosis. Every month brings new research results on new approaches to this problem, new methods of preprocessing, new classifiers, new ideas to follow etc. In particular, the rapid development of dermatoscopy,...
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Combining Road Network Data from OpenStreetMap with an Authoritative Database
PublikacjaComputer modeling of road networks requires detailed and up-to-date dataset. This paper proposes a method of combining authoritative databases with OpenStreetMap (OSM) system. The complete route is established by finding paths in the graph constructed from partial data obtained from OSM. In order to correlate data from both sources, a method of coordinate conversion is proposed. The algorithm queries road data from OSM and provides...
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Application of Least Squares with Conditional Equations Method for Railway Track Inventory Using GNSS Observations
PublikacjaSatellite geodetic networks are commonly used in surveying tasks, but they can also be used in mobile surveys. Mobile satellite surveys can be used for trackage inventory, diagnostics and design. The combination of modern technological solutions with the adaptation of research methods known in other fields of science offers an opportunity to acquire highly accurate solutions for railway track inventory. This article presents the...
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Revisiting serotonin’s role in spatial memory: A call for sensitive analytical approaches
PublikacjaThe serotonergic system is involved in various psychiatric and neurological conditions, with serotonergic drugs often used in treatment. These conditions frequently affect spatial memory, which can serve as a model of declarative memory due to well-known cellular components and advanced methods that track neural activity and behavior with high temporal resolution. However, most findings on serotonin's effects on spatial learning...
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Behavior Analysis and Dynamic Crowd Management in Video Surveillance System
PublikacjaA concept and practical implementation of a crowd management system which acquires input data by the set of monitoring cameras is presented. Two leading threads are considered. First concerns the crowd behavior analysis. Second thread focuses on detection of a hold-ups in the doorway. The optical flow combined with soft computing methods (neural network) is employed to evaluate the type of crowd behavior, and fuzzy logic aids detection...
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Standard of living in Poland at regional level - classification with Kohonen self-organizing maps
PublikacjaThe standard of living is spatially diversified and its analyzes enable shaping regional policy. Therefore, it is crucial to assess the standard of living and to classify regions due to their standard of living, based on a wide set of determinants. The most common research methods are those based on composite indicators, however, they are not ideal. Among the current critiques moved to the use of composite...
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Highlighting interlanguage phoneme differences based on similarity matrices and convolutional neural network
PublikacjaThe goal of this research is to find a way of highlighting the acoustic differences between consonant phonemes of the Polish and Lithuanian languages. For this purpose, similarity matrices are employed based on speech acoustic parameters combined with a convolutional neural network (CNN). In the first experiment, we compare the effectiveness of the similarity matrices applied to discerning acoustic differences between consonant...
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Knowledge management in the IPv6 migration process
PublikacjaThere are many reasons to deploy IPv6 protocol with IPv4 address space depletion being the most obvious. Unfortunately, migration to IPv6 protocol seems slower than anticipated. To improve pace of the IPv6 deployment, authors of the article developed an application that supports the migration process. Its main purpose is to help less experienced network administrators to facilitate the migration process with a particular target...
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Estimation and Prediction of Vertical Deformations of Random Surfaces, Applying the Total Least Squares Collocation Method
PublikacjaThis paper proposes a method for determining the vertical deformations treated as random fields. It is assumed that the monitored surfaces are subject not only to deterministic deformations, but also to random fluctuations. Furthermore, the existence of random noise coming from surface’s vibrations is also assumed. Such noise disturbs the deformation’s functional models. Surface monitoring with the use of the geodetic levelling...
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Verification of GNSS Measurements of the Railway Track Using Standard Techniques for Determining Coordinates
PublikacjaThe problem of the reproduction of the railway geometric layout in the global spatial system is currently solved in the form of measurements that use geodetic railway networks and also, in recent years, efficient methods of mobile positioning (mainly satellite and inert). The team of authors from the Gdańsk University of Technology and the Maritime University in Gdynia as part of the research project InnoSatTrack is looking for...
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Analiza danych osobowych przetwarzanych w systemach telekomunikacyjnych klasy IP PBX oraz metod ich anonimizacji za pomocą systemów SBC
PublikacjaOpisano wyniki realizacji pracy, dotyczącej analizy systemu telekomunikacyjnego, opartego na technologii VoIP, pod względem wymagań prawnych powstałych wraz z wejściem w życie przepisów Ogólnego Rozporządzenia o Ochronie Danych Osobowych (RODO). Przedstawiono wyniki analizy przykładowego systemu IP PBX Asterisk oraz wykorzystywanego w nim protokołu sygnalizacyjnego SIP, w kontekście przetwarzania danych osobowych, a także metody...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublikacjaDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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APPLICATION OF STATISTICAL FEATURES AND MULTILAYER NEURAL NETWORK TO AUTOMATIC DIAGNOSIS OF ARRHYTHMIA BY ECG SIGNALS
PublikacjaAbnormal electrical activity of heart can produce a cardiac arrhythmia. The electrocardiogram (ECG) is a non-invasive technique which is used as a diagnostic tool for cardiac diseases. Non-stationarity and irregu- larity of heartbeat signal imposes many difficulties to clinicians (e.g., in the case of myocardial infarction arrhythmia). Fortunately, signal processing algorithms can expose hidden information within ECG signal contaminated...
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Vehicle Detection with Self-Training for Adaptative Video Processing Embedded Platform
PublikacjaTraffic monitoring from closed-circuit television (CCTV) cameras on embedded systems is the subject of the performed experiments. Solving this problem encounters difficulties related to the hardware limitations, and possible camera placement in various positions which affects the system performance. To satisfy the hardware requirements, vehicle detection is performed using a lightweight Convolutional Neural Network (CNN), named...
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Equal Baseline Camera Array—Calibration, Testbed and Applications
PublikacjaThis paper presents research on 3D scanning by taking advantage of a camera array consisting of up to five adjacent cameras. Such an array makes it possible to make a disparity map with a higher precision than a stereo camera, however it preserves the advantages of a stereo camera such as a possibility to operate in wide range of distances and in highly illuminated areas. In an outdoor environment, the array is a competitive alternative...
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ASYNCHRONICZNE METODY RADIOLOKALIZACYJNE
PublikacjaW pracy przedstawiono wybrane problemy lokalizowania obiektów w asynchronicznych sieciach radiowych. W pierwszej kolejności zostały zdefiniowane kryteria jakościowe do oceny efektywności pracy opracowanych metod oraz przedstawiono model symulacyjny, który został użyty do badań. W kolejnych trzech rozdziałach szczegółowo opisano trzy oryginalne asynchroniczne metody radiolokalizacyjne w różnych wariantach. Przeprowadzono analizę...
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Computationally Efficient Surrogate-Assisted Design of Pyramidal-Shaped 3D Reflectarray Antennas
PublikacjaReflectarrays (RAs) have been attracting considerable interest in the recent years due to their appealing features, in particular, a possibility of realizing pencil-beam radiation patterns, as in the phased arrays, but without the necessity of incorporating the feeding networks. These characteristics make them attractive solutions, among others, for satellite communications or mobile radar antennas. Notwithstanding, available microstrip...
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Towards systemic functional safety and security management in hazardous plants
PublikacjaThe aim of this article is to identify and discuss some issues related to functional safety and security management in hazardous industrial plants. The safety functions are to be realised using the electric / electronic / programmable electronic systems (E/E/PESs) or the safety instrumented systems (SISs) that are designed and operated respectively according to IEC 61508 and IEC 61511 requirements in life cycle. Although the role...
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3D porous graphene-based structures- synthesis and applications
PublikacjaPorous carbon-based materials are of the great industrial and academic interest due to their high surface area, low density, good electrical conductivity, chemical inertness and low cost of fabrication. Up to now, the main approach to obtain porous carbon structures has involved the pyrolysis of carbonaceous natural or synthetic precursors. After the isolation of graphene, the interest in 3D porous graphene-based structures (called...
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Ocena efektywności monitoringu obiektów inżynierskich za pomocą sieci Bayesa
PublikacjaW swojej pracy autorzy zaproponowali zastosowanie sieci Bayesa do projektowania monitoringu i podejmowania decyzji w działaniach eksploatacyjnych. Ponadto pokazano dwie metody oceny wartości informacji diagnostycznych. Pierwszą z nich jest wartość oczekiwana EVSI (ang. Expected Value of Sample Information), która stanowi podstawę do wyboru spośród alternatywnych obserwacji symptomów zmiennej diagnostycznej. Natomiast drugą metodą...
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Visualization of short-term heart period variability with network tools as a method for quantifying autonomic drive
PublikacjaWe argue that network methods are successful in detecting nonlinear properties in the dynamics of autonomic nocturnal regulation in short-term variability. Two modes of visualization of networks constructed from RR-increments are proposed. The first is based on the handling of a state space. The state space of RR-increments can be modified by a bin size used to code a signal and by the role of a given vertex as the representation...
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Recent advances in high-frequency modeling by means of domain confinement and nested kriging
PublikacjaDevelopment of modern high-frequency components and circuits is heavily based on full-wave electromagnetic (EM) simulation tools. Some phenomena, although important from the point of view of the system performance, e.g., EM cross-coupling effects, feed radiation in antenna arrays, substrate anisotropy, cannot be adequately accounted for using simpler means such as equivalent network representations. Consequently, the involvement...
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Design-Oriented Two-Stage Surrogate Modeling of Miniaturized Microstrip Circuits with Dimensionality Reduction
PublikacjaContemporary microwave design heavily relies on full-wave electromagnetic (EM) simulation tools. This is especially the case for miniaturized devices where EM cross-coupling effects cannot be adequately accounted for using equivalent network models. Unfortunately, EM analysis incurs considerable computational expenses, which becomes a bottleneck whenever multiple evaluations are required. Common simulation-based design tasks include...
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Economical methods for measuring road surface roughness
PublikacjaTwo low-cost methods of estimating the road surface condition are presented in the paper, the first one based on the use of accelerometers and the other on the analysis of images acquired from cameras installed in a vehicle. In the first method, miniature positioning and accelerometer sensors are used for evaluation of the road surface roughness. The device designed for installation in vehicles is composed of a GPS receiver and...
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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublikacjaWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...
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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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Baltic Smart Asset Management - Training Module
Kursy OnlineBaltic Smart Asset Management is an international project co-financed by the funds from Interreg South Baltic Programme 2014-2020. The aim of the project is to develop methods, transnational collaboration processes and knowledge about Smart Asset Management (SAM) for District Heating (DH) sector. The training module will help to spread the professional knowledge on new solutions and applications of SAM methods to promote data-driven...
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Uczenie maszynowe do samoorganizacji systemów rozproszonych w zastosowaniach gospodarczych
PublikacjaW pracy omówiono uczenie maszynowe do samoorganizacji systemów rozproszonych w zastosowaniach gospodarczych ze szczególnym uwzględnieniem sieci neuronowych do predykcji finansowych oraz szacowania ratingu przedsiębiorstw. Oprócz sieci neuronowych, istotną rolę w przygotowaniu i testowaniu informatycznych systemów finansowych może pełnić programowanie genetyczne. Z tego powodu omówiono uczenie maszynowe w aplikacjach konstruowanych...
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublikacjaThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...