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Triangulation-based Constrained Surrogate Modeling of Antennas
PublicationDesign of contemporary antenna structures is heavily based on full-wave electromagnetic (EM) simulation tools. They provide accuracy but are CPU-intensive. Reduction of EM-driven design procedure cost can be achieved by using fast replacement models (surrogates). Unfortunately, standard modeling techniques are unable to ensure sufficient predictive power for real-world antenna structures (multiple parameters, wide parameter ranges,...
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Application 2D Descriptors and Artificial Neural Networks for Beta-Glucosidase Inhibitors Screening
PublicationBeta-glucosidase inhibitors play important medical and biological roles. In this study, simple two-variable artificial neural network (ANN) classification models were developed for beta-glucosidase inhibitors screening. All bioassay data were obtained from the ChEMBL database. The classifiers were generated using 2D molecular descriptors and the data miner tool available in the STATISTICA package (STATISTICA Automated Neural...
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Processing data on sea bottom structure obtained by means of the parametric sounding
PublicationThe aim of the paper is to analyze data obtain during sounding of the Gdansk Bay by means of the parametric sonar. The accuracy of the sea bottom structure investigation needs the correct configuration of research equipment and the proper calibration of peripheral devices (GPS, heading sensor, motion sensor MRU-Z and navigation units) which provide necessary data to bathymetrical measurement system enabling its work with whole...
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Monte-Carlo Modeling of Optical Sensors for Postoperative Free Flap Monitoring
PublicationThis work aims to develop a numerical tissue model and implement software to simulate photon propagation using the Monte Carlo method to determine design guidelines for a physical measurement system. C++ was used for the simulation program, and Python as a programming environment to create an interface that allows the user to customize individual simulation elements, allowing for increased accuracy and flexibility when simulating...
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Applications of the discrete green's function in the finite-difference time-domain method
PublicationIn this paper, applications of the discrete Green's function (DGF) in the three-dimensional (3-D) finite-difference time-domain (FDTD) method are presented. The FDTD method on disjoint domains was developed employing DGF to couple the subdomains as well as to compute the electromagnetic field outside these subdomains. Hence, source and scatterer are simulated in separate subdomains and updating of vacuum cells, being of little...
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Comparison and Analysis of Service Selection Algorithms
PublicationIn Service Oriented Architecture, applications are developed by integration of existing services in order to reduce development cost and time. The approach, however, requires algorithms that select appropriate services out of available, alternative ones. The selection process may consider both optimalization requirements, such as maximalization of performance, and constraint requirements, such minimal security or maximum development...
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Problems in estimation of hand grip force based on EMG signal
PublicationThere has recently been a significant increase in the number of publications on and applications of bioelectric signals for diagnostic purposes. While the use of ECG (electrocardiography) is not surprising, the use of signals from registration of brain activity (EEG) and muscles activity (EMG) still finds new applications in various fields. The authors focus on the use of EMG signals for estimating hand grip force. Currently,...
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A new approach to determination of the two-mass model parameters of railway current collector
PublicationThe paper presents two mathematical models of railway current collectors both with two degrees of freedom. The first one, hereinafter Pantograph Articulated Model (PAM), has one degree of freedom in rotational motion and the second degree of freedom in translational motion. The second model, called henceforth as Pantograph Reference Model (PRM), has both degrees of freedom in translational motion. Differential equations of the...
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A new approach to determination of the two-mass model parameters of railway current collector
PublicationThe paper presents two mathematical models of railway current collectors both with two degrees of freedom. The first one, hereinafter Pantograph Articulated Model (PAM), has one degree of freedom in rotational motion and the second degree of freedom in translational motion. The second model, called henceforth as Pantograph Reference Model (PRM), has both degrees of freedom in translational motion. Differential equations of the...
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Accurate simulation-driven modeling and design optimization of compact microwave structures
PublicationCost efficient design optimization of microwave structures requires availability of fast yet reliable replacement models so that multiple evaluations of the structure at hand can be executed in reasonable timeframe. Direct utilization of full-wave electromagnetic (EM) simulations is often prohibitive. On the other hand, accurate data-driven modeling normally requires a very large number of training points and it is virtually infeasible...
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Application of twin-plane ECT sensor for identification of the internal imperfections inside concrete beams
PublicationThe main purpose of this paper is to investigate application of special construction of Electrical Capacitance Tomography (ECT) sensor to concrete beams internal homogeneity tests. Identification of internal imperfection inside the concrete beams is one of the main problems related to analysis of the construction structure bearing capacity. Therefore, this paper shows attempts to study the measurement prospects for this non-invasive,...
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SIMULATION OF PROCEED® SURGICAL MESH APPLIED TO VENTRAL HERNIA REPAIR
PublicationIn the present research, Proceed® implant is considered. The system is subjected to short-time dynamic pressure load, similar to post-operative cough naturally occurring in human abdomen. The model refers to a clinical case of 5cm of hernia operated by Proceed implant fixed by 15 joints every 3cm around the orifice. The simulations of the implanted mesh are performed by means of the Finite Element Method. The implant is modelled...
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Cost-Effective and Sufficiently Precise Integration Method Adapted to the FEM Calculations of Bone Tissue
PublicationThe technique of Young’s modulus variation in the finite element is not spread in biomechanics. Our future goal is to adapt this technique to bone tissue strength calculations. The aim of this paper is to present the necessary studies of the element’s integration method that takes into account changes in material properties. For research purposes, a virtual sample with the size and distribution of mechanical properties similar...
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A PROPOSAL FOR ONE-IMAGE PHOTOGRAMMETRY SYSTEM FOR MEASURING THE CLEARANCE DISTANCE. CASE STUDY
PublicationMeasurement of the clearance distance (both in the context of the rail and road) is one of the current and increasingly discussed topics in the context of photogrammetric and image processing (computer vision) methods. The article presents a description of a simple and rapid method of measure the clearance distance between the obstacles by using one-image photogrammetry. The proposed method was tested for the railway, tram and...
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Processing data on sea bottom structure obtained by means of the parametric sounding
PublicationThe aim of the paper is to analyze data obtained during sounding the Gdansk Bay sea bed by means of the parametric echo-sounder. The accuracy of the sea bottom structure investigation needs correct configuration of research equipment and proper calibration of peripheral devices (GPS, heading sensor, MRU-Z motion sensor and navigation instruments which provide necessary data to bathymetrical measurement system, enabling its work...
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The investment process in the power supply industry
PublicationThe basis for power supply industry programming in a market economy should be the principle of sustainable development, which must take into account maintaining an adequate level of energy security on the one hand, and the aim to preserve the maximum degree of non-renewable resources on the other hand. Therefore, the overriding aim should be a strive to meet the current and prospective demand for energy and fuel, in conjugation...
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Correlations between organic pollution indicators in municipal wastewater
PublicationThe paper presents the results of a study of parameters used for determining the amount of organic pollutants in wastewater flowing into a collective wastewater treatment plant with a population equivalent of about 120 000 PE. The plant constituted part of a sewage system. Assays were performed for biochemical oxygen demand (BOD5), chemical oxygen demand (CODCr), permanganete index (CODMn) and total organic carbon (TOC). In addition,...
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Calculating the Partition Coefficients of Organic Solvents in Octanol/Water and Octanol/Air
PublicationPartition coefficients define how a solute is distributed between two immiscible phases at equilibrium. The experimental estimation of partition coefficients in a complex system can be an expensive, difficult, and time-consuming process. Here a computational strategy to predict the distributions of a set of solutes in two relevant phase equilibria is presented. The octanol/water and octanol/air partition coefficients are predicted...
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublicationForecasting 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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Uncertainty quantification of modal parameter estimates obtained from subspace identification: An experimental validation on a laboratory test of a large-scale wind turbine blade
PublicationThe uncertainty afflicting modal parameter estimates stems from e.g., the finite data length, unknown, or partly measured inputs and the choice of the identification algorithm. Quantification of the related errors with the statistical Delta method is a recent tool, useful in many modern modal analysis applications e.g., damage diagnosis, reliability analysis, model calibration. In this paper, the Delta method-based uncertainty...
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Non-Linear Analysis of Structures Utilizing Load-Discretization of Stiffness Matrix Method with Coordinate Update
PublicationThis paper proposes a stiffness method based structural analysis algorithm for geometrically non-linear structures. In this study, the applied load on the joints has been discretized to a sequence of a few loadings applied. Each loading step produces incremental external nodal displacements, which are added to the corresponding coordinates to get a new geometrical shape of the structure. This process is iteratively repeated until...
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When all we have is not enough: a search for the optimal method of quantifying inflation expectations
PublicationAlthough inflation expectations are pivotal variables for central banks, they are not directly observable. Therefore, central banks use qualitative survey results to proxy consumer expectations, and their quantification in this manner is often criticized. In this study, we investigate and identify an optimal quantification procedure for survey results based on a set of regression and probabilistic models. Specifically, we seek...
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Emotion Recognition from Physiological Channels Using Graph Neural Network
PublicationIn recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work, GraphSleepNet (a GNN for classifying the stages of sleep) was adjusted for emotion recognition and validated for this purpose. The...
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Estimation of Average Speed of Road Vehicles by Sound Intensity Analysis
PublicationConstant monitoring of road traffic is important part of modern smart city systems. The proposed method estimates average speed of road vehicles in the observation period, using a passive acoustic vector sensor. Speed estimation based on sound intensity analysis is a novel approach to the described problem. Sound intensity in two orthogonal axes is measured with a sensor placed alongside the road. Position of the apparent sound...
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Self-Adaptive Mesh Generator for Global Complex Roots and Poles Finding Algorithm
PublicationIn any global method of searching for roots and poles, increasing the number of samples increases the chances of finding them precisely in a given area. However, the global complex roots and poles finding algorithm (GRPF) (as one of the few) has direct control over the accuracy of the results. In addition, this algorithm has a simple condition for finding all roots and poles in a given area: it only requires a sufficiently dense...
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Monolithic capsule phase microextraction prior to gas chromatography-mass spectrometry for the determination of organochlorine pesticides in environmental water samples
PublicationIn this study, a capsule phase microextraction (CPME) protocol followed by gas chromatography-mass spectrometry is proposed for the accurate and sensitive monitoring of organochlorine pesticides (OCPs) in environmental water samples. Different monolithic sol–gel encapsulated sorbents were compared and monolithic sol–gel poly(ethylene glycol)-based sorbent incorporated into porous microextraction capsules resulted in the highest...
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High-temperature Corrosion of ~ 30 Pct Porous FeCr Stainless Steels in Air: Long-Term Evaluation Up to Breakaway
PublicationIn this work, a long-term (up to 6000 hours) corrosion evaluation of three porous (~ 30 pct of initial porosity) ferritic iron-chromium alloys with different Cr contents (20, 22, and 27 wt pct of Cr) was carried out at 600 C, 700 C, 800 C, and 900 C in air. Mass gain measurements and SEM analyses revealed that at temperatures above 600 C, all alloys exhibit breakaway corrosion, whereas at 600 C, none of the alloys were heavily...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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EVALUATION OF 3D MODEL OF REBAR FOR QUANTITATIVE PARAMETERS
PublicationThe construction industry practices and processes are evolving constantly, and with the emergence of Industry 4.0, the use of technologies is expanding. Construction progress monitoring is an essential project lifecycle process; project success and timely completion are linked with effective progress monitoring operations and adopted tools. In the domain of automated construction progress monitoring, 3D modeling techniques have...
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Monte-Carlo Modeling of Optical Sensors for Postoperative Free Flap Monitoring
PublicationThis work aims to develop a numerical tissue model and implement software to simulate photon propagation using the Monte Carlo method to determine design guidelines for a physical measurement system. C++ was used for the simulation program, and Python as a programming environment to create an interface that allows the user to customize individual simulation elements, allowing for increased accuracy and flexibility when simulating...
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3D MODELLING OF CYLINDRICAL-SHAPED OBJECTS FROM LIDAR DATA - AN ASSESSMENT BASED ON THEORETICAL MODELLING AND EXPERIMENTAL DATA
PublicationDespite the increasing availability of measured laser scanning data and their widespread use, there is still the problem of rapid and correct numerical interpretation of results. This is due to the large number of observations that carry similar information. Therefore, it is necessary to extract from the results only the essential features of the modelled objects. Usually, it is based on a process using filtration, followed by...
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Flexible Knowledge–Vision–Integration Platform for Personal Protective Equipment Detection and Classification Using Hierarchical Convolutional Neural Networks and Active Leaning
PublicationThis work is part of an effort to develop of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. The paper focuses on hazards resulted from the non-use of personal protective equipment (PPE). The objective is to test the capability of the platform to adapt to different industrial environments by simulating the process of randomly selecting...
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Ultrasound assisted dispersive solid phase microextraction using polystyrene-polyoleic acid graft copolymer for determination of Sb(III) in various bottled beverages by HGAAS
PublicationA new polyoleic acid-polystyrene (PoleS) block/graft copolymer was synthesized and applied as adsorbent for ultrasound assisted dispersive solid phase microextraction (UA-DSPME) of Sb(III) in different bottled beverages and analysis using hydride generation atomic absorption spectrometry (HGAAS). Adsorption capacity of the PoleS was 150 mg g−1. Several sample preparation parameters such as sorbent amount, solvent type, pH, sample...
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Noise profiling for speech enhancement employing machine learning models
PublicationThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...
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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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Hyperbolic Asynchronous Method of a Radio Navigation Technique
PublicationHumans have always wanted to determine position in an unknown environment. At the beginning methods were simple. They were based on the observation of characteristic points, in the case of shipping additional observations of the coastline. Then came navigation based on astronomical methods (astronavigation). At the beginning of the XX-century a new way of determining the current location was developed. It has used radiowave signals....
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IoT for healthcare applications
PublicationThis chapter summarizes IRACON contributions related to the application of IoT in healthcare. It consists of the following three sections. Section 8.1 presents the measurement campaigns and the related statistical analysis to obtain various channel models for wearable and implantable devices. In addition, the importance of physical human-body phantoms used for channel, Specific Absorption Rate (SAR), and Electromagnetic (EM) exposure...
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Thermal buckling of functionally graded piezomagnetic micro- and nanobeams presenting the flexomagnetic effect
PublicationGalerkin weighted residual method (GWRM) is applied and implemented to address the axial stability and bifurcation point of a functionally graded piezomagnetic structure containing flexomagneticity in a thermal environment. The continuum specimen involves an exponential mass distributed in a heterogeneous media with a constant square cross section. The physical neutral plane is investigated to postulate functionally graded material...
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Using UAV Photogrammetry to Analyse Changes in the Coastal Zone Based on the Sopot Tombolo (Salient) Measurement Project
PublicationThe main factors influencing the shape of the beach, shoreline and seabed include undulation, wind and coastal currents. These phenomena cause continuous and multidimensional changes in the shape of the seabed and the Earth’s surface, and when they occur in an area of intense human activity, they should be constantly monitored. In 2018 and 2019, several measurement campaigns took place in the littoral zone in Sopot, related to...
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Development of a simple biogas analyzer module (BAM) for real-time biogas production monitoring
PublicationAnaerobic digestion (AD) relies on the cooperation of specific microbial communities, making it susceptible to process disruptions that could impact biogas production. In this regard, this study presents a technological solution based on the Arduino platform, in the form of a simple online monitoring system that can track the produced biogas profile, named as biogas analyzer module (BAM). The applicability of the BAM focused on...
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Development of an orbital shaker-assisted fatty acid-based switchable solvent microextraction procedure for rapid and green extraction of amoxicillin from complex matrices: Central composite design
PublicationIn this study, a cheap, fast and simple orbital shaker-assisted fatty acid-based switchable solvent microextraction (OS-FASS-ME) procedure was developed for the extraction of amoxicillin (AMOX) in dairy products, pharmaceutical samples and wastewater prior to its spectrophotometric analysis. Fatty acid-based switchable solvents were investigated for extracting AMOX. The key factors of the OS-FASS-ME procedure were optimized using...
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublicationExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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Investigation of use of hydrophilic/hydrophobic NADESs for selective extraction of As(III) and Sb(III) ions in vegetable samples: Air assisted liquid phase microextraction and chemometric optimization
PublicationIn this paper, a green, cost-effective sample preparation method based on air assisted liquid phase microextraction (AA-LPME) was developed for the simultaneous extraction of As(III) and Sb(III) ions from vegetable samples using hydrophilic/hydrophobic natural deep eutectic solvents (NADESs). Central composite design was used for the optimization of extraction factors including NADES volume, extraction cycle, pH, and curcumin concentration....
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Ab initio chemical kinetics of Isopropyl acetate oxidation with OH radicals
PublicationGlobal reactivity descriptors of isopropyl acetate (IPA) and thermo-kinetic aspects of its oxidation via OH radicals have been studied. Transition state theory (TST) was utilized to estimate the bimolecular rate constants. Ten oxidation pathways have been investigated, and all of them are exothermic. The potential energy diagram has been sketched using different pre- and post-reactive complexes for all reaction pathways. Rate coefficient...
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Evaluation of high-frequency roughness measurement errors for composite and ceramic surfaces after machining
PublicationPrecise characterisation of surface topography is of the greatest importance since many factors directly affect the accuracy of the whole measurement process. In this paper, the variety of surface topographies from machined composite and ceramic workpieces was studied with a special emphasis on the measurement results. Surfaces were subjected to the ground diamond, honing and milling processes. Measurement results were analysed...
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Magnetic hydrophobic deep eutectic solvents for orbital shaker-assisted dispersive liquid-liquid microextraction (MAGDES-OS-DLLME) - determination of nickel and copper in food and water samples by FAAS
PublicationIn this work, a cheap and widely applicable dispersive liquid-liquid microextraction (DLLME) method was developed for the extraction of Ni(II) and Cu(II) from water and food samples and analysis using flame atomic absorption spectrometry. DLLME was assisted by orbital shaker, while ferrofluid as an extractant was based on deep eutectic solvent (DES). This ferrofluid was made of hydrophobic DES (hDES), composed of lauric acid and...
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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
PublicationRNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA....
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Detection of the First Component of the Received LTE Signal in the OTDoA Method
PublicationIn a modern world there is a growing demand for localization services of various kinds. Position estimation can be realized via cellular networks, especially in the currently widely deployed LTE (Long Term Evolution) networks. However, it is not an easy task in harsh propagation conditions which often occur in dense urban environments. Recently, time-methods of terminal localization within the network have been the focus of attention,...
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Automatic singing quality recognition employing artificial neural networks
PublicationCelem artykułu jest udowodnienie możliwości automatycznej oceny jakości technicznej głosów śpiewaczych. Pokrótce zaprezentowano w nim stworzoną bazę danych głosów śpiewaczych oraz zaimplementowane parametry. Przy pomocy sztucznych sieci neuronowych zaprojektowano system decyzyjny, który oceniono w pięciostopniowej skali jakość techniczną głosu. Przy pomocy metod statystycznych udowodniono, że wyniki generowane przez ten system...
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Numerical Investigation on Dynamic Performance of a Multi-storey Steel Structure Model and Comparison with Experimental Results
PublicationShaking table testing is the most commonly adopted method to simulate earthquake forces. This approach allows us to analyze the dynamic performance and provides a valuable insight into the dynamics of building structures, which helps to improve their future safety and reliability. The present study aims to conduct a numerical evaluation of dynamic response of a multi-storey steel structure model, which was previously examined during...