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Catalog Publications
Year 2025
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AI-Driven Sustainability in Agriculture and Farming
PublicationIn this chapter, we discuss the role of artificial intelligence (AI) in promoting sustainable agriculture and farming. Three main themes run through the chapter. First, we review the state of the art of smart farming and explore the transformative impact of AI on modern agricultural practices, focusing on its contribution to sustainability. With this in mind, our analysis focuses on topics such as data collection and storage, AI...
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Follow-up assessment of the microvascular function in patients with long COVID
PublicationLong COVID is a complex pathophysiological condition. However, accumulating data suggests that COVID-19 is a systemic microvascular endothelial dysfunction with different clinical manifestations. In this study, a microvascular function was assessed in long COVID patients (n = 33) and healthy controls (n = 30) using flow-mediated skin fluorescence technique (FMSF), based on measurements of nicotinamide adenine dinucleotide fluorescence...
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Isolation Improvement in MIMO Antenna with a Simple Hybrid Technique of Orthogonal and Inverse Currents
PublicationThis paper presents a compact high-isolation multiple-input multiple-output (MIMO) antenna developed using a hybrid approach. The proposed technique combines induced orthogonal currents and self-inverse currents to enhance the antenna's performance. Orthogonal currents are generated by strategically etching open slots on the antenna patches, while self-inverse currents are introduced by integration of annular vias. By carefully...
Year 2024
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3-D Printable Metal-Dielectric Metasurface for Risley Prism-Based Beam-Steering Antennas
PublicationA 3-D printable, planar, metal-dielectric metasurface-based, 2-D beam-steering system for aperture-type antennas is presented in this paper. This beam steering system, also known as the near-field meta-steering system, comprises two fully passive phase-gradient metasurfaces placed in the antenna’s nearfield region to steer the radiation beam. To address the non-uniform electric field phase of the aperture antenna, phase correction...
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3D-Breast System for Determining the Volume of Tissue Needed for Breast Reconstruction
Publication3D imaging systems can be used to effectively determine breast volumes for surgical applications. This article presents methods for surface reconstruction and volume determination based on the point cloud created by 3D imaging. Such a system would be used to accurately estimate breast volume in patients classified for breast reconstruction surgery at plastic surgery centers. To develop such a system, various methods of determining...
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A 0.5 V Nanowatt Biquadratic Low-Pass Filter with Tunable Quality Factor for Electronic Cochlea Applications
PublicationA novel implementation of an analogue low-power, second-order, low-pass filter with tunable quality factor (Q) is presented and discussed. The filter feature is a relatively simple, buffer-based, circuit network consisting of eleven transistors operating in a subthreshold region. Q tuning is accomplished by injecting direct current into a network node, which changes the output resistance of the transistors and, as a result, modifies...
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A Compact Circularly Polarized Dielectric Resonator Antenna with MIMO Characterizations for UWB Applications
PublicationUltra-wideband (UWB) technology is extensively used in indoor navigation, medical applications, and Internet of Things (IoT) devices due to its low power consumption and resilience against multipath fading and losses. This paper examines a multiple input multiple-output (MIMO), circularly polarized (CP) dielectric resonator antenna (DRA) for UWB systems. Compact form factor, high gain, wideband response, improved port isolation,...
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A Comparison of Directional Beamforming Capabilities: High-Order Ambisonic Microphone vs. Shotgun Microphones
PublicationThis article presents the practical implications of the directional beamforming capability of a higher-order ambisonic microphone compared with popular shotgun microphones. Five different microphones were used in the study: Sennheiser MKH 416, Rode NTG2, Panasonic AG-MC200, Zoom SGH-6, and Zylia ZM-1 (ambisonic microphone). The results highlight the versatility of higher-order ambisonics for non-immersive use, which allows for...
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A gap waveguide-based mechanically reconfigurable phase shifter for high-power Ku-band applications
PublicationThis paper presents a novel design of a low-loss, reconfgurable broadband phase shifter based on groove gap waveguide (GGW) technology. The proposed phase shifter consists of a folded GGW and three bends with a few pins forming the GGW and one bend attached to a movable plate. This movable plate allows for adjustments to the folded waveguide length, consequently altering the phase of electromagnetic waves. The advantage of GGW...
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A Low-Profile 3-D Printable Metastructure for Performance Improvement of Aperture Antennas
PublicationIn order to increase the radiation performance of aperture-type antennas, this paper demonstrates a low-profile, planar, single-layer, three-dimensional (3-D) printable metastructure. The proposed hybridized metastructure is highly transparent as it is made out of novel hybrid meta-atoms having transmission coefficient magnitudes greater than -0.72 dB and fully complies with the near-field phase transformation principle. The hybridized...
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A Low-Profile Metal-backed Dipole Loaded with Closely Coupled Arc-shaped Open Stubs for On-metal Tag Design with Wide Frequency Tuning Capability
PublicationThis research has presented a single-layer metal-backed dipole antenna, which consists of a feedline loaded with two pairs of closely-coupled arc-shaped open stubs, for designing a metal-mountable tag that features tuning capability over a wide range of frequency. Here, the stubs can generate sufficient inductive reactance for bringing down the tag resonant frequency tunable in both the regulated UHF RFID passbands (North American...
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A Machine Learning Approach for Estimating Overtime Allocation in Software Development Projects
PublicationOvertime planning in software projects has traditionally been approached with search-based multi-objective optimization algorithms. However, the explicit solutions produced by these algorithms often lack applicability and acceptance in the software industry due to their disregard for project managers' intuitive knowledge. This study presents a machine learning model that learns the preferred overtime allocation patterns from solutions...
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A machine learning approach to classifying New York Heart Association (NYHA) heart failure
PublicationAccording to the European Society of Cardiology, globally the number of patients with heart failure nearly doubled from 33.5 million in 1990 to 64.3 million in 2017, and is further projected to increase dramatically in this decade, still remaining a leading cause of morbidity and mortality. One of the most frequently applied heart failure classification systems that physicians use is the New York Heart Association (NYHA) Functional...
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A Mammography Data Management Application for Federated Learning
PublicationThis study aimed to develop and assess an application designed to enhance the management of a local client database consisting of mammographic images with a focus on ensuring that images are suitably and uniformly prepared for federated learning applications. The application supports a comprehensive approach, starting with a versatile image-loading function that supports DICOM files from various medical imaging devices and settings....
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A Novel Device and System for Fall Detection Under the Shower
PublicationIn this paper, device construction and preliminary results for shower safety assistance are presented. The device allows monitoring of shower-taking persons without violating privacy and intimacy, while it has the ability to detect a persons entering and leaving the shower and detecting fall conditions. It allows better supervision of elders living independently at their locations.
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A Novel Iterative Decoding for Iterated Codes Using Classical and Convolutional Neural Networks
PublicationForward error correction is crucial for communication, enabling error rate or required SNR reduction. Longer codes improve correction ratio. Iterated codes offer a solution for constructing long codeswith a simple coder and decoder. However, a basic iterative code decoder cannot fully exploit the code’s potential, as some error patterns within its correction capacity remain uncorrected.We propose two neural network-assisted decoders:...
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A Planar-Structured Circularly Polarized Single-Layer MIMO Antenna for Wideband Millimetre-Wave Applications
PublicationIn this paper, a simple geometry, planar-structured printed multiple-input-multiple-output (MIMO) antenna utilizing dual circular polarization (CP) is presented. The proposed numerically and experimentally validated design features a fully grounded coplanar waveguide (CPW) and a systematically perturbed feedline radiator. The fringing electric (E) field along the feedline is altered by extruding periodic stubs on each side of the...
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A procedure for the visualization of fingerprint traces on standard and thermal paper using the electron excitation energy of 1,8-diazafluoren-9- one aggregates in a polyvinylpyrrolidone polymer
PublicationThe scope of this study is a new procedure for visualizing dactyloscopic traces on an absorbent surface using a solution based on aggregates of 1,8-diazafluoren-9-one (DFO) in a polyvinylpyrrolidone polymer (PVP). An absorbent surface is defined as a plain or thermal paper, which is considered to be a difficult surface due to its varying chemical composition. In the case of the thermal paper surface, the procedure can be further...
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A prototype information system for managing and pricing e-waste
PublicationThere is no doubt that innovation drives development in all areas of human activity, including electrical and electronic equipment. However, the production of new equipment has a significant impact on the natural environment and a relatively high consumption of natural resources. To address these issues, the circular economy has been implemented in recent years by promoting and introducing numerous measures to facilitate the recycling...
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A review of explainable fashion compatibility modeling methods
PublicationThe paper reviews methods used in the fashion compatibility recommendation domain. We select methods based on reproducibility, explainability, and novelty aspects and then organize them chronologically and thematically. We presented general characteristics of publicly available datasets that are related to the fashion compatibility recommendation task. Finally, we analyzed the representation bias of datasets, fashion-based algorithms’...
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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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A simple route of providing a soft interface for PEDOT: PSS film metallic electrodes without loss of their electrical interface parameters
PublicationThe work presents the development of a soft interface at PEDOT:PSS film without changing its electrical interface parameters. In the first step, PEDOT:PSS is electrodeposited on the commercial platinum electrode under the state-of-the-art conditions desirable for different electrochemical electrodes. Secondly, a pure hydrogel layer is deposited on the top of the electrodeposited PEDOT:PSS film under conditions that provide desirable...
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A simplified channel estimation procedure for NB-IoT downlink
PublicationThis paper presents a low-complexity channel estimation procedure which is suitable for use in energy-efficient NB-IoT user equipment devices. The procedure is based on the well-established least squares scheme, followed by linear interpolation in the time domain and averaging in the frequency domain. The quality of channel estimation vs. signal-to-noise ratio is evaluated for two channel models and compared with the performance...
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A Survey on the Datasets and Algorithms for Satellite Data Applications
PublicationThis survey compiles insights and describes datasets and algorithms for applications based on remote sensing. The goal of this review is twofold: datasets review for particular groups of tasks and high-level steps of data flow between satellite instruments and end applications from an implementation and development perspective. The article outlines the generalized data processing pipelines, taking into account the variations in...
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A tool for designing water tanks for measuring hydroacoustic transducers
PublicationSpecial water tanks are commonly used to measure the parameters of underwater acoustic systems. They must meet specific requirements, the fulfilment of which ensures very small but acceptable measurement errors. These requirements define the size of the tank and its shape as well as the strong attenuation of reflected waves. At the design stage, it is necessary to determine the impact of the tank structure on the measurement errors...
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Absorbing Boundary Conditions Derived Based on Pauli Matrices Algebra
PublicationIn this letter, we demonstrate that a set of absorbing boundary conditions (ABCs) for numerical simulations of waves, proposed originally by Engquist and Majda and later generalized by Trefethen and Halpern, can alternatively be derived with the use of Pauli matrices algebra. Hence a novel approach to the derivation of one-way wave equations in electromagnetics is proposed. That is, the classical wave equation can be factorized...
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Accuracy of marine gravimetric measurements in terms of geodetic coordinates of land reference benchmark
PublicationThe article presents how the values of (3D) coordinates of land reference points affect the results of gravimetric measurements made from the ship in sea areas. These measurements are the basis for 3D maritime inertial navigation, improving ships' operational safety. The campaign verifying the network absolute point coordinates used as a reference point for relative marine gravity measurements was described. The obtained values...
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Accurate Post-processing of Spatially-Separated Antenna Measurements Realized in Non-Anechoic Environments
PublicationAntenna far-field performance is normally evaluated in expensive laboratories that maintain strict control over the propagation environment. Alternatively, the responses can be measured in non-anechoic conditions and then refined to extract the information on the structure field-related behavior. Here, a framework for correction of antenna measurements performed in non-anechoic test site has been proposed. The method involves automatic...
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Actual and reference evapotranspiration for a natural, temperate zone fen wetland – Upper Biebrza case study
PublicationEvapotranspiration is the key and predominant component of the water balance in wetlands. Direct evapotranspiration measurements are challenging in wetlands due to their remoteness and high surface water level. This article describes the actual (ETa and reference evapotranspiration (ET0) from a cultivated wet meadow located in the Biebrza National Park – the largest national park in north-east Poland, Central Europe. The data were...
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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublicationIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...
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Adaptive Hounsfield Scale Windowing in Computed Tomography Liver Segmentation
PublicationIn computed tomography (CT) imaging, the Hounsfield Unit (HU) scale quantifies radiodensity, but its nonlinear nature across organs and lesions complicates machine learning analysis. This paper introduces an automated method for adaptive HU scale windowing in deep learning-based CT liver segmentation. We propose a new neural network layer that optimizes HU scale window parameters during training. Experiments on the Liver Tumor...
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Adaptive Hyperparameter Tuning within Neural Network-based Efficient Global Optimization
PublicationIn this paper, adaptive hyperparameter optimization (HPO) strategies within the efficient global optimization (EGO) with neural network (NN)-based prediction and uncertainty (EGONN) algorithm are proposed. These strategies utilize Bayesian optimization and multiarmed bandit optimization to tune HPs during the sequential sampling process either every iteration (HPO-1itr) or every five iterations (HPO-5itr). Through experiments using...
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Adaptive Optimal Discrete-Time Output-Feedback Using an Internal Model Principle and Adaptive Dynamic Programming
PublicationIn order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming (ADP) technique based on the internal model principle (IMP). The proposed method, termed as IMP-ADP, does not require complete state feedback, merely the measurement of input and output data. More specifically, based on the IMP, the output control problem can first be converted into a stabilization...
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Adaptive Sampling for Non-intrusive Reduced Order Models Using Multi-Task Variance
PublicationNon-intrusive reduced order modeling methods (ROMs) have become increasingly popular for science and engineering applications such as predicting the field-based solutions for aerodynamic flows. A large sample size is, however, required to train the models for global accuracy. In this paper, a novel adaptive sampling strategy is introduced for these models that uses field-based uncertainty as a sampling metric. The strategy uses...
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Advanced Sensor for Non-Invasive Breast Cancer and Brain Cancer Diagnosis Using Antenna Array with Metamaterial-Based AMC
PublicationMicrowave imaging techniques can identify abnormal cells in early development stages. This study introduces a microstrip patch antenna coupled with artificial magnetic conductor (AMC) to realize improved sensor for non-invasive (early-stage) breast cancer and brain cancer diagnosis. The frequency selectivity of the proposed antenna has been increased by the presence of AMC by creating an additional resonance at 2.276 GHz associated...
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AI-Powered Cleaning Robot: A Sustainable Approach to Waste Management
PublicationThe world is producing a massive amount of single use waste, especially plastic waste made from polymers. Such waste is usually distributed in large areas within cities, near roads, parks, forests, etc. It is a challenge to collect them efficiently. In this work, we propose a Cleaning Robot as an autonomous vehicle for waste collection, utilizing the Nvidia Jetson Nano platform for precise arm movements guided by computer...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublicationSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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An Efficient PEEC-Based Method for Full-Wave Analysis of Microstrip Structures
PublicationThis article introduces an efficient method for the equivalent circuit characterization and full-wave analysis of microstrip structures, leveraging the full-wave partial element equivalent circuit (PEEC). In particular, the multilayered Green's function is evaluated using the discrete complex-image method (DCIM) and employed to establish the mixed potential integral equations. The proposed strategy considers time delays for the...
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An improvement of body surface area formulas using the 3D scanning technique
PublicationObjectives: Body surface area (BSA) is one of the major parameters used in several medical fields. However, there are concerns raised about its usefulness, mostly due to the ambiguity of its estimation. Material and Methods: Authors have conducted a voluntary study to investigate BSA distribution and estimation in a group of 179 adult people of various sex, age, and physique. Here, there is provided an extended analysis of the...
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An intelligent cellular automaton scheme for modelling forest fires
PublicationForest fires have devastating consequences for the environment, the economy and human lives. Understanding their dynamics is therefore crucial for planning the resources allocated to combat them effectively. In a world where the incidence of such phenomena is increasing every year, the demand for efficient and accurate computational models is becoming increasingly necessary. In this study, we perform a revision of an initial proposal...
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An Optimized Ka-Band Low Profile Dual-Polarized Transmitarray Antenna With 2D Beam Switching
PublicationThis article presents an optimized dual-polarized transmitarray antenna (TA) designed for MIMO applications at the Ka-band, capable of switching beams in two directions. The antenna aperture uses a small unit cell with three layers of Taconic RF-35 dielectric substrates, which can be easily fabricated using PCB technology. The unit cell achieved a 360-degree phase shift and a transmission magnitude exceeding –0.4 dB at 28 GHz....
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An optimized system for sensor ontology meta-matching using swarm intelligent algorithm
PublicationIt is beneficial to annotate sensor data with distinct sensor ontologies in order to facilitate interoperability among different sensor systems. However, for this interoperability to be possible, comparable sensor ontologies are required since it is essential to make meaningful links between relevant sensor data. Swarm Intelligent Algorithms (SIAs), namely the Beetle Swarm Optimisation Algorithm (BSO), present a possible answer...
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ANALIZA POSTACI SYGNAŁU SYNCHRONIZACYJNEGO NPSS W NB-IOT
PublicationW artykule zaprezentowane zostały możliwości zmiany postaci sekwencji Zadoff-Chu używanej do wygenerowania sygnału synchronizacyjnego NPSS w interfejsie radiowym NB-IoT. Modyfikacji poddano elementy charakterystyczne sekwencji z uwzględnieniem: root index, ciągu binarnego czy składnika funkcji wykładniczej w celu poprawy właściwości korelacyjnych na potrzeby synchronizacji pracy terminali użytkowników.
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Analysis of friction ridge evidence for trace amounts of paracetamol in various pharmaceutical industries by Raman spectroscopy
PublicationThe detection of potentially harmful substances presents a multifaceted challenge. On one hand, it can directly save lives, on the other, it can significantly aid and enhance police work, thereby increasing the effectiveness of investigations. The research conducted in this study primarily aims to identify paracetamol in fingerprints, considering situations involving direct contact of a person with paracetamol either chronically...
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Analyzing the relationship between sound, color, and emotion based on subjective and machine-learning approaches
PublicationThe aim of the research is to analyze the relationship between sound, color, and emotion. For this purpose, a survey application was prepared, enabling the assignment of a color to a given speaker’s/singer’s voice recordings. Subjective tests were then conducted, enabling the respondents to assign colors to voice/singing samples. In addition, a database of voice/singing recordings of people speaking in a natural way and with expressed...
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Anomaly Detection in Railway Sensor Data Environments: State-of-the-Art Methods and Empirical Performance Evaluation
PublicationTo date, significant progress has been made in the field of railway anomaly detection using technologies such as real-time data analytics, the Internet of Things, and machine learning. As technology continues to evolve, the ability to detect and respond to anomalies in railway systems is once again in the spotlight. However, railway anomaly detection faces challenges related to the vast infrastructure, dynamic conditions, aging...
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Antenna Optimization Using Machine Learning with Reduced-Dimensionality Surrogates
PublicationIn modern times, antenna design has become more demanding than ever. The escalating requirements for performance and functionality drive the development of intricately structured antennas, where parameters must be meticulously adjusted to achieve peak performance. Often, global adjustments to geometry are necessary for optimal results. However, direct manipulation of antenna responses evaluated with full-wave electromagnetic (EM)...
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Application Of Generative Adversarial Network for Data Augmentation and Multiplication to Automated Cell Segmentation of the Corneal Endothelium
PublicationConsidering the automatic segmentation of the endothelial layer, the available data of the corneal endothelium is still limited to a few datasets, typically containing an average of only about 30 images. To fill this gap, this paper introduces the use of Generative Adversarial Networks (GANs) to augment and multiply data. By using the ``Alizarine'' dataset, we train a model to generate a new synthetic dataset with over 513k images....
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Application of the Flipped Learning Methodology at a Business Process Modelling Course – A Case Study
PublicationFlipped learning has been known for a long time, but its modern use dates back to 2012, with the publication of Bergmann and Saams. In the last decade, it has become an increasingly popular learning method. Every year, the number of publications on implementing flipped learning experiments is growing, just as the amount of research on the effectiveness of this educational method. The aim of the article is to analyze the possibilities...
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Approximate and analytic flow models for leak detection and identification
PublicationThe article presents a comprehensive quantitative comparison of four analytical models that, in different ways, describe the flow process in transmission pipelines necessary in the task of detecting and isolating leaks. First, the analyzed models are briefly presented. Then, a novel model comparison framework was introduced along with a methodology for generating data and assessing diagnostic effectiveness. The study presents basic...