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Search results for: SYSTEM TESTING , SENSITIVITY , COMPUTATIONAL MODELING , NEURAL NETWORKS , OBJECT DETECTION , DISTORTION , DATA MODELS
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Estimation the rhythmic salience of sound with association rules and neural networks
PublicationW referacie przedstawiono eksperymenty mające na celu automatyczne wyszukiwanie wartości rytmicznych we frazie muzycznej. W tym celu wykorzystano metody data mining i sztuczne sieci neuronowe.
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Damage Detection Strategies in Structural Health Monitoring of Overhead Power Transmission System
PublicationOverhead power transmission lines, their supporting towers, insulators and other elements create a highly distributed system that is vulnerable to damage. Typical damage scenarios cover cracking of foundation, breakage of insulators, loosening of rivets, as well as cracking and breakage of lines. Such scenarios may result from various factors: groundings, lightning strikes, floods, earthquakes, aeolian vibrations, conductors galloping,...
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A compact smart sensor based on a neural classifier for objects modeled by Beaunier's model
PublicationA new solution of a smart microcontroller sensor based on a simple direct sensor-microcontroller interface for technical objects modeled by two-terminal networks and by the Beaunier’s model of anticorrosion coating is proposed. The tested object is stimulated by a square pulse and its time voltage response is sampled four times by the internal ADC of microcontroller. A neural classifier based on measurement data classifies the...
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Computer Networks-laboratories - 2023
e-Learning CoursesAcquiring the skills to design, build and configure computer networks. Demonstration of skills to identify and analyze selected protocols and mechanisms of LAN and WAN networks.
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Computer Networks laboratories 2024
e-Learning CoursesAcquiring the skills to design, build and configure computer networks. Demonstration of skills to identify and analyze selected protocols and mechanisms of LAN and WAN networks.
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Neural Modelling of Steam Turbine Control Stage
PublicationThe paper describes possibility of steam turbine control stage neural model creation. It is of great importance because wider application of green energy causes severe conditions for control of energy generation systems operation Results of chosen steam turbine of 200 MW power measurements are applied as an example showing way of neural model creation. They serve as training and testing data of such neural model. Relatively simple...
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Resource constrained neural network training
PublicationModern applications of neural-network-based AI solutions tend to move from datacenter backends to low-power edge devices. Environmental, computational, and power constraints are inevitable consequences of such a shift. Limiting the bit count of neural network parameters proved to be a valid technique for speeding up and increasing efficiency of the inference process. Hence, it is understandable that a similar approach is gaining...
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Accuracy Investigations of Turbine Blading Neural Models Applied to Thermal and Flow Diagnostics
PublicationPossibility of replacing computional fluid dynamics simulations by a neural model for fluid flow and thermal diagnostics of steam turbines is investigated. Results of calculations of velocity magnitude of steam for 3D model of the stator of steam turbine is presented.
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublicationThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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Data-Driven Modeling of Mechanical Properties of Fiber-Reinforced Concrete: A Critical Review
PublicationFiber-reinforced concrete (FRC) is extensively used in diverse structural engineering applications, and its mechanical properties are crucial for designing and evaluating its performance. The compressive, flexural, splitting tensile, and shear strengths of FRCs are among the most important attributes, which have been discussed more extensively than other properties. The accurate prediction of these properties, which are required...
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Correlation–polarization effects in electron/positron scattering from acetylene: A comparison of computational models
PublicationDifferent computational methods are employed to evaluate elastic (rotationally summed) integral and differential cross sections for low energy (below about 10 eV) positron scattering off gas-phase C2H2 molecules. The computations are carried out at the static and static-plus-polarization levels for describing the interaction forces and the correlation–polarization contributions are found to be an essential component for the correct...
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System Loss Model for Body-to-Body Networks in Indoor and Outdoor Environments
PublicationA system loss model for body-to-body networks in indoor and outdoor environments is proposed in this paper, based on measurements taken at 2.45 GHz. The influence of the type of environment, antenna visibility and user mobility on model parameters has been investigated. A significant impact of mutual antennas’ placement and their visibility is shown. The proposed model fits well to empirical data, with the average root mean square...
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Comparison of Traffic Flow Models with Real Traffic Data Based on a Quantitative Assessment
PublicationThe fundamental relationship of traffic flow and bivariate relations between speed and flow, speed and density, and flow and density are of great importance in transportation engineering. Fundamental relationship models may be applied to assess and forecast traffic conditions at uninterrupted traffic flow facilities. The objective of the article was to analyze and compare existing models of the fundamental relationship. To that...
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublicationHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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PHONEME DISTORTION IN PUBLIC ADDRESS SYSTEMS
PublicationThe quality of voice messages in speech reinforcement and public address systems is often poor. The sound engineering projects of such systems take care of sound intensity and possible reverberation phenomena in public space without, however, considering the influence of acoustic interference related to the number and distribution of loudspeakers. This paper presents the results of measurements and numerical simulations of the...
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Uniform Model Interface for Assurance Case Integration with System Models
PublicationAssurance cases are developed and maintained in parallel with corresponding system models and therefore need to reference each other. Managing the correctness and consistency of interrelated safety argument and system models is essential for system dependability and is a nontrivial task. The model interface presented in this paper enables a uniform process of establishing and managing assurance case references to various types...
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DFMA guidelines and a data base system in integrated development of hydraulic pumps
PublicationPrzedstawiono koncepcję budowy systemu decyzyjnego, dla zintegrowanego rozwoju pomp hydraulicznych oraz doboru adekwatnych technik wytworzenia komponentów i procesów montażu, z zastosowaniem metodyki SADT/IDEF0 oraz ogólnych wytycznych DFMA. Omówiono stosowane w przemyśle krajowym konstrukcje pomp zębatych z łożyskami tocznymi oraz udoskonalone rozwiązania projektowe tych pomp z łożyskami ślizgowymi (polimerowymi). Wskazano na...
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublicationDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
PublicationThe paper presents research on the approximation of variable-order fractional operators by recurrent neural networks. The research focuses on two basic variable-order fractional operators, i.e., integrator and differentiator. The study includes variations of the order of each fractional operator. The recurrent neural network architecture based on GRU (Gated Recurrent Unit) cells functioned as a neural approximation for selected...
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Minimizing Distribution and Data Loading Overheads in Parallel Training of DNN Acoustic Models with Frequent Parameter Averaging
PublicationIn the paper we investigate the performance of parallel deep neural network training with parameter averaging for acoustic modeling in Kaldi, a popular automatic speech recognition toolkit. We describe experiments based on training a recurrent neural network with 4 layers of 800 LSTM hidden states on a 100-hour corpora of annotated Polish speech data. We propose a MPI-based modification of the training program which minimizes the...
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Predicting Performance of Lightweight Concrete with Granulated Expanded Glass and Ash Aggregate by Means of Using Artificial Neural Networks
PublicationLightweight concrete (LWC) is a group of cement composites of the defined physical, mechanical, and chemical performance. The methods of designing the composition of LWC with the assumed density and compressive strength are used most commonly. The purpose of using LWC is the reduction of the structure’s weight, as well as the reduction of thermal conductivity index. The highest possible strength, durability and low thermal conductivity...
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Rating by detection: an artifact detection protocol for rating EEG quality with average event duration
PublicationQuantitative evaluation protocols are critical for the development of algorithms that remove artifacts from real EEG optimally. However, visually inspecting the real EEG to select the top-performing artifact removal pipeline is infeasible while hand-crafted EEG data allow assessing artifact removal configurations only in a simulated environment. This study proposes a novel, principled approach for quantitatively evaluating algorithmically...
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Computational modeling of molecularly imprinted polymers as a green approach to the development of novel analytical sorbents
PublicationThe development of novel molecularly imprinted polymers (MIP) sorbents for specific chemical compounds require a lot of tedious and time-consuming laboratory work. Significant quantities of solvents and reagents are consumed in the course of the verification of appropriate configurations of polymerization reagents. Implementation of molecular modeling in the MIP sorbent development process appears to provide a solution to this...
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Optical Sensor Based Gestures Inference Using Recurrent Neural Network in Mobile Conditions
PublicationIn this paper the implementation of recurrent neural network models for hand gesture recognition on edge devices was performed. The models were trained with 27 hand gestures recorded with the use of a linear optical sensor consisting of 8 photodiodes and 4 LEDs. Different models, trained off-line, were tested in terms of different network topologies (different number of neurons and layers) and different effective sampling frequency...
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Submerged object imaging using virtual reality modeling language.
PublicationArtykuł przedstawia sposób wykorzystania języka opisu wirtualnej rzeczywistości w archeologii podwodnej. Przedstawiono propozycję wizualizacji objektów znajdujących się na dnie morskim, a w szczególności zaprezentowano technikę rekonstrukcji obrazu trójwymiarowego z danych pochodzących z sonaru wielowiązkowego.
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Distributed Detection of Selected Features in Data Streams Using Grid-class Systems
PublicationThis chapter describes basic methodology of distributed digital signal processing. A choice of distributed methods of detection of selected features in data streams using grid-class systems is discussed. Problems related to distribution of data for processing are addressed. A mitigating method for data distribution and result merging is described.
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The structure of the data flow in integrated urban traffic management systems – the case of TRISTAR system
PublicationThe purpose of the article is to offer some insight into the data flow architecture in the Tri-City’s integrated traffic management system called TRISTAR. To that end selected elements of TRISTAR are identified and described as well as the structure for collecting and exchanging data within different sub-systems. Finally, the article highlights how the TRISTAR system can be extended by adding new elements and modules.
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Viewpoint independent shape-based object classification for video surveillance
PublicationA method for shape based object classification is presented.Unlike object dimension based methods it does not require any system calibration techniques. A number of 3D object models are utilized as a source of training dataset for a specified camera orientation. Usage of the 3D models allows to perform the dataset creation process semiautomatically. The background subtraction method is used for the purpose of detecting moving objects...
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Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification
PublicationLiquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community...
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GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition
PublicationIn the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, Resnet50 and Resnet152 were tested using systems with Nvidia Quadro RTX 6000 as well as Nvidia V100 GPUs. Using GPU power capping we found other than default configurations minimizing...
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Situational Awareness Network for the Electric Power System: the Architecture and Testing Metrics
PublicationThe contemporary electric power system is highly dependent on Information and Communication Technologies which results in its exposure to new types of threats, such as Advanced Persistent Threats (APT) or Distributed-Denial-of-Service (DDoS) attacks. The most exposed components are Industrial Control Systems in substations and Distributed Control Systems in power plants. Therefore, it is necessary to ensure the cyber security of...
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Object Programming
e-Learning Courses -
Two- and three-dimensional elastic networks with rigid junctions: modeling within the theory of micropolar shells and solids
PublicationFor two- and three-dimensional elastic structures made of families of flexible elastic fibers undergoing finite deformations, we propose homogenized models within the micropolar elasticity. Here we restrict ourselves to networks with rigid connections between fibers. In other words, we assume that the fibers keep their orthogonality during deformation. Starting from a fiber as the basic structured element modeled by the Cosserat...
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Special Issue: “Non-Destructive Testing of Structures”
PublicationThe Special Issue “Non-Destructive Testing of Structures” has been proposed to present recent developments in the field of diagnostics of structural materials and components in civil and mechanical engineering. The papers highlighted in this editorial concern various aspects of non-invasive diagnostics, including such topics as condition assessments of civil and mechanical structures and connections of structural elements, the...
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Voltage Harmonic Distortion Measurement Issue in Smart-Grid Distribution System
PublicationThis paper presents the investigation results ofvoltage harmonic transfer accuracy problems through voltagetransformers which are widely used in power quality monitoringsystems in medium and high voltage grids. A simplified lumpedparameters circuit model of the voltage transformer is presentedand verified by simulation and experimental investigations. Anumber voltage transformers typically used in medium voltagegrid has been tested...
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How Integration of a Brain-Machine Interface and Obstacle Detection System Can Improve Wheelchair Control via Movement Image
PublicationThis study presents a human-computer interaction combined with a brain-machine interface (BMI) and obstacle detection system for remote control of a wheeled robot through movement imagery, providing a potential solution for individuals facing challenges with conventional vehicle operation. The primary focus of this work is the classification of surface EEG signals related to mental activity when envisioning movement and deep relaxation...
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Computational Fluid Dynamic study on the wind characteristics of a multifunctional building system model in developed coastal cities
PublicationThis paper presents an approach for providing innovative technology by applying fluid mechanics to the field of architectural design. The aim is to make a building’s shape profitable and strengthen environmental protection by using the wind force to create an integrated wind absorption definition for a multifunctional building system model. Furthermore, taking control of the wind flow over an object can have an impact on not only...
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The System of the Supervision and the Visualization of Multimedia Data for BG
PublicationMonitoring of country maritime border is an important task of the Border Guard. This task can be facilitated with the use of the technology enabling gathering information from distributed sources and its supervision and visualization. The system presented in the paper is an extension and enhancement of the previously developed distributed system map data exchange system. The added functionalities allow supplementation of map data...
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Estimating the Average Speed of Public Transport Vehicles Based on Traffic Control System Data
PublicationIntelligent Transport Systems are a valuable source of traffic information, covering both private and public vehicles. The main problem, however, is that very few studies are conducted to determine the speed of buses, trams and trolleys in urban networks in relation to traffic conditions. The paper investigates how ITS systems data could be used to model the speed of Public Transport vehicles. This is now possible thanks to the...
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Electronic nose algorithm design using classical system identification for odour intensity detection
PublicationThe two elements considered crucial for constructing an efficient environmental odour intensity monitoring systems are sensors and algorithms typically addressed to as electronic nose sensor (e-nose). Due to operational complexity of biochemical sensors developed in human bodies algorithms based on computational methods of artificial intelligence are typically considered superior to classical model based approaches in development...
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An interactive system for remote modeling and design validation of hybrid photovoltaic systems
PublicationAbstract: A multi-functional demonstrator of the interactive system is presented. The demostrator enables modeling, monitoring and design validation of hybrid photovoltaic systems assisted by fuel cells and thermoelectric generators, as well as experimentation and scientific research. A block diagram of the system is presented and the selection of its components is discussed. Availability of the system via Ethernet or GSM...
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Application of mechanistic and data-driven models for nitrogen removal in wastewater treatment systems
PublicationIn this dissertation, the application of mechanistic and data-driven models in nitrogen removal systems including nitrification and deammonification processes was evaluated. In particular, the influential parameters on the activity of the Nitrospira activity were assessed using response surface methodology (RSM). Various long-term biomass washout experiments were operated in two parallel sequencing batch reactor (SBR) with a different...
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Recent Advances in Performance-Driven Surrogate Modeling of High-Frequency Structures
PublicationDesign of high‐frequency structures, including microwave and antenna components, heavily relies on full‐wave electromagnetic (EM) simulation models. Their reliability comes at a price of a considerable computational cost. This may lead to practical issues whenever numerous EM analyses are to be executed, e.g., in the case of parametric optimization. The difficulties entailed by massive simulations may be mitigated by the use of...
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Justyna Signerska-Rynkowska dr inż.
PeopleI am currently an assistant professor (adjunct) at Gdansk University of Technology (Department of Differential Equations and Mathematics Applications). My scientific interests include dynamical systems theory, chaos theory and their applications to modeling of biological phenomena, especially to neurosciences. In June 2013 I completed PhD in Mathematics at the Institute of Mathematics of Polish Academy of Sciences (IMPAN) (thesis...
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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublicationWhether 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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The methods of secure data transmission in the KNX system
PublicationThe article presents the demands concerning data security in distributed building automation systems and shows the need for providing mechanisms of secure communication in the KNX system. Three different methods developed for KNX data protection are discussed: EIBsec, KNX Data Security and the author's method. Their properties are compared and potential areas of application are presented.
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A literature review on computational models for laminated composite and sandwich panels
PublicationW artykule przedstawiono przegląd modeli obliczeniowych stosowanych w analizie laminowanych powłok kompozytowych i sandwiczowych. W przeglądzie uwzględniono ponad 200 pozycji literatury traktujących o modelach teoretycznych dla płyt i powłok wielo-warstowych oraz/lub o implementacjach numerycznych różnych modeli obliczeniowych. Jako podstawową konkluzję z dokonanego przeglądu, należy uznać, że nie istnieje jeden uniwersalny model...
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GROUP COMPOSER - System for Modeling Agents’ Team Building for Tasks
PublicationMulti-agent systems consist of many autonomous units, called agents, that can interact when trying to achieve their goals. The selection of interaction partners is called team formation. Three basic approaches can be considered to match multi-agent system resources to the problem at hand. To research the properties of different approaches, a software for modeling team formation in multi-agent systems has been created and is presented...
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Improvement of derivatized amino acid detection sensitivity in micellar electrokinetic capillary chromatography by means of acid-induced pH-mediated stacking technique
PublicationDerivatization is a frequently used sample prepara-tion procedure applicable to the enhancement of analyte de-tection sensitivity. Amino acids mostly require derivatization prior to electrophoretic or chromatographic analysis, especial-ly if spectrophotometric detection is used. This study presents an on-line preconcentration technique for derivatized amino acids. The sensitivity of the method was improved by the utilization of...
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The Use of Artificial Neural Networks and Decision Trees to Predict the Degree of Odor Nuisance of Post-Digestion Sludge in the Sewage Treatment Plant Process
PublicationThis paper presents the application of artificial neural networks and decision trees for the prediction of odor properties of post-fermentation sludge from a biological-mechanical wastewater treatment plant. The input parameters were concentrations of popular compounds present in the sludge, such as toluene, p-xylene, and p-cresol, and process parameters including the concentration of volatile fatty acids, pH, and alkalinity in...