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Catalog Publications
Year 2024
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A Data-Driven Comparative Analysis of Machine-Learning Models for Familial Hypercholesterolemia Detection
PublicationThis study presents an assessment of familial hypercholesterolemia (FH) probability using different algorithms (CatBoost, XGBoost, Random Forest, SVM) and its ensembles, leveraging electronic health record data. The primary objective is to explore an enhanced method for estimating FH probability, surpassing the currently recommended Dutch Lipid Clinic Network (DLCN) Score. The models were trained using the largest Polish cohort...
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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 high-gain gap waveguide-based 16 × 16 slot antenna array with low sidelobe level for mmwave applications
PublicationThis study presents the design of a high-gain 16 × 16-slot antenna array with a low sidelobe level (SLL) using a tapered ridge gap waveguide feeding network for Ka-band applications. The proposed antenna element includes four cavity-backed slot antennas. A tapered feeding network is designed and utilized for unequal feeding of the radiating elements. Ridge gap waveguide technology is used to reduce the feeding network loss and...
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A Highly Compact Split Ring Resonator Based Rectangular Dielectric Resonator Antenna with Multiband Characterization
PublicationThis work encompasses a novel highly compact Split Ring Resonator (SRR) based quad-band Dielectric Resonator Antenna (DRA) for 4G and 5G applications. The proposed antenna comprises of an extended rectangular feedline and a rectangular DR in combination with two SRRs. The DRA uses the extended rectangular microstrip feedline for providing better impedance matching and enhanced performance. Remarkably, the introduction of SRRs on...
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A learning community model: the Center for Innovative Education supporting academic didactics at Gdańsk University of Technology, Poland
PublicationThe current digital transformation requires academics to apply their pedagogical and technological skills to their teaching and professional development to address the newly emerging needs of the digital era. This study aims to analyse the operating model of the Center for Innovative Education (CIE) at Gdańsk University of Technology (Gdańsk Tech), Poland, as an incubator for professional development of academic staff at Gdańsk...
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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 modified DC Hebb–Wagner polarization method for determining the partial protonic electrical conductivity in mixed-conducting BaGd0.3La0.7Co2O6−δ
PublicationIn this work, partial protonic conductivity in mixed conducting (BZCY721) and BaGd0.3La0.7Co2O6−d (BGLC137) was studied. For this purpose, a modified DC Hebb–Wagner polarization method was used. A four-wire type of galvanic cell as well as a suitable calculation model was applied. The method was validated using proton conducting electrolyte – BaZr0.7Ce0.2Y0.1O3−d – as a reference material. For the first time, protonic partial conductivity...
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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 Probabilistic Optimisation Approach to the Equitable Controller Location Problem
PublicationThe ability of the Software-Defined Network (SDN) to transport traffic flows depends, in particular, on the SDN switches being able to communicate with SDN controllers, which are responsible for the setup of network connections and the configuration of switches. Since in principle the number of SDN controllers is limited they must be installed in a set of carefully selected node locations. Whereas the problem of controller placement...
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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 Review on Machine Learning Deployment Patterns and Key Features in the Prediction of Preeclampsia
PublicationPrevious 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
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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A Flexible Way of Coarse Coordinates Estimation for Sodars
PublicationThe 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
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 Analysis of the Performance of Lightweight CNNs in the Context of Object Detection on Mobile Phones
PublicationConvolutional 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
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 Empirical Study of a Dynamic Stop Loss Strategy with Deep Reinforcement Learning on the NASDAQ Stock Market
PublicationThe 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
PublicationThe 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
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 Open Platform Tool for 2D Multipactor Simulations in Metallic Microwave Components
PublicationThe 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
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 Drone Signals Based on Change Point Detection Algorithm
PublicationThe 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
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...