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Wydział Elektroniki, Telekomunikacji i Informatyki
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Rok 2025
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AI-Driven Sustainability in Agriculture and Farming
PublikacjaIn 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...
Rok 2024
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3D-Breast System for Determining the Volume of Tissue Needed for Breast Reconstruction
Publikacja3D 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
PublikacjaA 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 gap waveguide-based mechanically reconfigurable phase shifter for high-power Ku-band applications
PublikacjaThis 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
PublikacjaIn 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
PublikacjaThis 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
PublikacjaOvertime 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
PublikacjaAccording 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 Novel Iterative Decoding for Iterated Codes Using Classical and Convolutional Neural Networks
PublikacjaForward 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
PublikacjaIn 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 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 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 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 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 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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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 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 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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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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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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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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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 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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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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Automatic Correction of Non-Anechoic Antenna Measurements Using Complex Morlet Wavelets
PublikacjaReal-world performance of antennas is normally tested in anechoic chambers (ACs). Alternatively, experimental validation can be performed in non-anechoic environments and refined in the course of post-processing. Unfortunately, the existing methods are difficult to setup and prone to failure. In this letter, a wavelet-based framework for correction of non-anechoic antenna measurements has been proposed. The method involves automatic...
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Bi-GRU-APSO: Bi-Directional Gated Recurrent Unit with Adaptive Particle Swarm Optimization Algorithm for Sales Forecasting in Multi-Channel Retail
PublikacjaIn the present scenario, retail sales forecasting has a great significance in E-commerce companies. The precise retail sales forecasting enhances the business decision making, storage management, and product sales. Inaccurate retail sales forecasting can decrease customer satisfaction, inventory shortages, product backlog, and unsatisfied customer demands. In order to obtain a better retail sales forecasting, deep learning models...
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Bimodal deep learning model for subjectively enhanced emotion classification in films
PublikacjaThis research delves into the concept of color grading in film, focusing on how color influences the emotional response of the audience. The study commenced by recalling state-of-the-art works that process audio-video signals and associated emotions by machine learning. Then, assumptions of subjective tests for refining and validating an emotion model for assigning specific emotional labels to selected film excerpts were presented....
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Catheter-induced coronary artery and aortic dissections. A study of the mechanisms, risk factors, and propagation causes
PublikacjaBackground: Only the incidence, management, and prognosis of catheter-induced coronary artery and aortic dissections have been systematically studied until now. We sought to evaluate their mechanisms, risk factors, and propagation causes. Methods: Electronic databases containing 76,104 procedures and complication registries from 2000– –2020 were searched and relevant cineangiographic studies adjudicated. Results: Ninety-six dissections...
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Circularly Polarized Metalens Antenna Design for 5G NR Sub-6 GHz Communication Systems
Publikacja5G NR (new radio) FR1 range refers to as Sub-6GHz band (410MHz to 7125MHz and 3.4GHz to 6GHz). In this paper, the frequency range of interest is from 3.4 to 6GHz, as many cellular companies are focusing on this Sub-6GHz band. A wideband circularly polarized (CP) antenna radiator is designed with diamond shape patches, fed by a microstrip line at the bottom through a rectangular shape wide slot on a ground plane. The proposed CP...
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Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network
PublikacjaCOVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...
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CNN-CLFFA: Support Mobile Edge Computing in Transportation Cyber Physical System
PublikacjaIn the present scenario, the transportation Cyber Physical System (CPS) improves the reliability and efficiency of the transportation systems by enhancing the interactions between the physical and cyber systems. With the provision of better storage ability and enhanced computing, cloud computing extends transportation CPS in Mobile Edge Computing (MEC). By inspecting the existing literatures, the cloud computing cannot fulfill...
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Compact Substrate-Integrated Hexagonal Cavity-Backed Self-Hexaplexing Antenna for Sub-6 GHz Applications
PublikacjaA self-multiplexing SIW antenna based on hexagonal SIW cavity is proposed. The self-hexaplexing antenna consists of different sizes of resonating elements, which provide the hexaband operations. The antenna resonates at 5 GHz, 5.17 GHz, 5.32 GHz, 5.53 GHz, 5.62 GHz, and 5.72 GHz by employing different slot lengths between the resonating elements. The proposed antenna provides the individual tunable characteristics of the operating...
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Comparison of 3D Point Cloud Completion Networks for High Altitude Lidar Scans of Buildings
PublikacjaHigh altitude lidar scans allow for rapid acquisition of big spatial data representing entire city blocks. Unfortunately, the raw point clouds acquired by this method are largely incomplete due to object occlusions and restrictions in scanning angles and sensor resolution, which can negatively affect the obtained results. In recent years, many new solutions for 3D point cloud completion have been created and tested on various objects;...
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Comparison of Deep Neural Network Learning Algorithms for Mars Terrain Image Segmentation
PublikacjaThis paper is dedicated to the topic of terrain recognition on Mars using advanced techniques based on the convolutional neural networks (CNN). The work on the project was conducted based on the set of 18K images collected by the Curiosity, Opportunity and Spirit rovers. The data were later processed by the model operating in a Python environment, utilizing Keras and Tensorflow repositories. The model benefits from the pretrained...