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Wydział Elektroniki, Telekomunikacji i Informatyki
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Rok 2024
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A prototype information system for managing and pricing e-waste
PublikacjaThere 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
PublikacjaThe 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 Review on Machine Learning Deployment Patterns and Key Features in the Prediction of Preeclampsia
PublikacjaPrevious reviews have investigated machine learning (ML) models used to predict the risk of developing preeclampsia. However, they have not addressed the intended deployment of these models throughout pregnancy, nor have they detailed feature performance. This study aims to provide an overview of existing ML models and their intended deployment patterns and performance, along with identified features of high importance. This review...
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A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
PublikacjaThis 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
PublikacjaThe 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
PublikacjaThis 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
PublikacjaThis 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
PublikacjaSpecial 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
PublikacjaIn 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
PublikacjaThe 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
PublikacjaAntenna 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
PublikacjaEvapotranspiration 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
PublikacjaIn 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
PublikacjaIn 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
PublikacjaIn 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
PublikacjaIn 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
PublikacjaNon-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
PublikacjaMicrowave 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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A Flexible Way of Coarse Coordinates Estimation for Sodars
PublikacjaThe publication presents a flexible approach to implementing coarse coordinate estimation of an object observed with a sodar. This flexibility permits any arrangement of sound sources as well as microphones. Only minimal requirements are imposed on the probing signal, which can particularly be broadband. The algorithms have been tested on both synthetic data and data recorded with an actual device.
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AI-Powered Cleaning Robot: A Sustainable Approach to Waste Management
PublikacjaThe 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 Analysis of the Performance of Lightweight CNNs in the Context of Object Detection on Mobile Phones
PublikacjaConvolutional Neural Networks (CNNs) are widely used in computer vision, which is now increasingly used in mobile phones. The problem is that smartphones do not have much processing power. Initially, CNNs focused solely on increasing accuracy. High-end computing devices are most often used in this type of research. The most popular application of lightweight CNN object detection is real-time image processing, which can be found...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublikacjaSentiment 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
PublikacjaThis 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 Empirical Study of a Dynamic Stop Loss Strategy with Deep Reinforcement Learning on the NASDAQ Stock Market
PublikacjaThe objective of this paper is to empirically investigate the efficacy of using Deep Reinforcement Learning (DRL) to maximize investment returns by incorporating expected optimal closing prices of long positions into a daily strategy. This paper extends existing research on the impact of stop-loss orders on investment strategy results and brings contribution of these orders to trading strategies into a completely new perspective....
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An Extremely Compact Frequency Reconfigurable Antenna Diplexer Employing Dielectric Liquids
PublikacjaThe letter presents an extremely compact frequency reconfigurable antenna diplexer based on fluidic channels for sub6 GHz applications. The proposed antenna diplexer is modelled by employing half-mode (HM) and quarter-mode (QM) substrateintegrated rectangular cavities, two slots, orthogonal feed lines, and fluidic vias. To comprehend the radiation mechanism, the equivalent circuit, electric field distributions, and frequency responses...
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An improvement of body surface area formulas using the 3D scanning technique
PublikacjaObjectives: 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
PublikacjaForest 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 Open Platform Tool for 2D Multipactor Simulations in Metallic Microwave Components
PublikacjaThe paper presents a computer simulation software aimed at assessing the multipactor threshold power in a rectangular waveguide working with single tone excitation. Initial tests demonstrate a strong agreement between the simulation results obtained and those from commercial software. Contrary to the existing commercial software, our tool will be provided as Open Platform, for free use and popularisation of knowledge about physical...
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An Optimized Ka-Band Low Profile Dual-Polarized Transmitarray Antenna With 2D Beam Switching
PublikacjaThis 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
PublikacjaIt 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
PublikacjaW 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 Drone Signals Based on Change Point Detection Algorithm
PublikacjaThe work presents an algorithm characterized by high precision and efficiency in identifying signals related to data transmission between the controller and the drone. Using an efficient change point detection algorithm and parallel analysis capabilities, this method facilitates rapid signal analysis. These features make the proposed algorithm a solid basis for developing an effective anti-drone defense system.
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Analysis of friction ridge evidence for trace amounts of paracetamol in various pharmaceutical industries by Raman spectroscopy
PublikacjaThe 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
PublikacjaThe 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
PublikacjaTo 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
PublikacjaIn 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
PublikacjaConsidering 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
PublikacjaFlipped 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
PublikacjaThe 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...
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Approximation algorithms for job scheduling with block-type conflict graphs
PublikacjaThe problem of scheduling jobs on parallel machines (identical, uniform, or unrelated), under incompatibility relation modeled as a block graph, under the makespan optimality criterion, is considered in this paper. No two jobs that are in the relation (equivalently in the same block) may be scheduled on the same machine in this model. The presented model stems from a well-established line of research combining scheduling theory...
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Architectural Modifications to Enhance Steganalysis with Convolutional Neural Networks
PublikacjaThis paper investigates the impact of various modifications introduced to current state-of-the-art Convolutional Neural Network (CNN) architectures specifically designed for the steganalysis of digital images. Usage of deep learning methods has consistently demonstrated improved results in this field over the past few years, primarily due to the development of newer architectures with higher classification accuracy compared to...
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Artificial Intelligence for Wireless Avionics Intra-Communications
PublikacjaThis chapter presents a summary of the description and preliminary results of the use case related to the implementation of artificial intelligence tools in the emerging technology called wireless avionics intra-communications (WAICs). WAICs aims to replace some of the cable buses of modern aircraft. This replacement of infrastructure leads to: (1) complexity reduction of future airplanes, (2) creation of innovative services where...
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Artificial Intelligence in the Diagnosis of Onychomycosis—Literature Review
PublikacjaOnychomycosis is a common fungal nail infection that is difficult to diagnose due to its similarity to other nail conditions. Accurate identification is essential for effective treatment. The current gold standard methods include microscopic examination with potassium hydroxide, fungal cultures, and Periodic acid-Schiff biopsy staining. These conventional techniques, however, suffer from high turnover times, variable sensitivity,...
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Assessment of High-Temperature Oxidation Properties of 316L Stainless Steel Powder and Sintered Porous Supports for Potential Solid Oxide Cells Applications
PublikacjaIn this work, oxidation properties of austenitic 316L stainless steel powder and sintered porous support were investigated at the temperature range of ~600-750 °C for 100 hours in ambient air. Oxidation kinetics was determined by continuous thermogravimetry and analyzed employing parabolic rate law. It was observed that oxidation leads to the formation of an oxide scale, with substantial oxidation occurring at ≥ 650 °C in the powder....
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Assessment Of the Relevance of Best Practices in The Development of Medical R&D Projects Based on Machine Learning
PublikacjaMachine learning has emerged as a fundamental tool for numerous endeavors within health informatics, bioinformatics, and medicine. However, novices among biomedical researchers and IT developers frequently lack the requisite experience to effectively execute a machine learning project, thereby increasing the likelihood of adopting erroneous practices that may result in common pitfalls or overly optimistic predictions. The paper...
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Auto-Correction of Non-Anechoic Antenna Measurements Based on Multi-Taper Approach
PublikacjaMeasurements of antenna prototypes are normally performed in dedicated, yet costly environments such as anechoic chambers (ACs). However, the AC construction cost might be unjustified when the measurements aim to support education, or budget-tight research. Alternatively, experiments can be realized in non-anechoic regime and refined using appropriate methods. In this letter, a framework for correction of antenna far-field measurements...
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Automated Generation of Modular Assurance Cases with the System Assurance Reference Model
PublikacjaAssurance cases are structured arguments used to demonstrate specific system properties such as safety or security. They are used in many industrial sectors including automotive, aviation and medical devices. Assurance cases are usually divided into modules which address goals allocated to specific system properties, components, functions, modes of operation or environmental conditions. Depending on the system and assurance process...
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Automated hearing loss type classification based on pure tone audiometry data
PublikacjaHearing problems are commonly diagnosed with the use of tonal audiometry, which measures a patient’s hearing threshold in both air and bone conduction at various frequencies. Results of audiometry tests, usually represented graphically in the form of an audiogram, need to be interpreted by a professional audiologist in order to determine the exact type of hearing loss and administer proper treatment. However, the small number of...
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Automated measurement method for assessing thermal-dependent electronic characteristics of thin boron-doped diamond-graphene nanowall structures
PublikacjaThis paper investigates the electrical properties of boron-doped diamond-graphene (B:DG) nanostructures, focusing on their semiconductor characteristics. These nanostructures are synthesized on fused silica glass and Si wafer substrates to compare their behaviour on different surfaces. A specialized measurement system, incorporating Python-automated code, was developed for an in-depth analysis of electronic properties under various...
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Automated Parking Management for Urban Efficiency: A Comprehensive Approach
PublikacjaEffective parking management is essential for ad-dressing the challenges of traffic congestion, city logistics, and air pollution in densely populated urban areas. This paper presents an algorithm designed to optimize parking management within city environments. The proposed system leverages deep learning models to accurately detect and classify street elements and events. Various algorithms, including automatic segmentation of...