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Search results for: SURROGATE-MODEL-ASSISTED EVOLUTIONARY ALGORITHM
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Nonlinear material identification of heterogeneous isogeometric Kirchhoff–Love shells
PublicationThis work presents a Finite Element Model Updating inverse methodology for reconstructing heterogeneous materialdistributions based on an efficient isogeometric shell formulation. It uses nonlinear hyperelastic material models suitable fordescribing incompressible material behavior as well as initially curved shells. The material distribution is discretized by bilinearelements such that the nodal values...
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Characterization of Defects Inside the Cable Dielectric With Partial Discharge Modeling
PublicationThe continuous monitoring of power system devices is an important step toward keeping such capital assets safe. Partial discharge (PD)-based measurement tools provide a reliable and accurate condition assessment of power system insulations. It is very common that voids or cavities exist in every solid dielectric insulation medium. In this article, different voids are modeled and analyzed using an advanced finite element (FE)-based...
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The Idea of Using Bayesian Networks in Forecasting Impact of Traffic-Induced Vibrations Transmitted through the Ground on Residential Buildings
PublicationTraffic–induced vibrations may constitute a considerable load to buildings. In this paper, vibrations transmitted through the ground caused by wheeled vehicles are considered. This phenomenon may cause cracking of plaster, cracks in load-bearing elements or even, in extreme cases, collapse of the whole structure. Measurements of vibrations of real structures are costly and laborious. Therefore, the aim of the present paper is to...
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Cross-talk Between the Heart and Arteries in Older 65+ Adults
PublicationRegulatory synchronization between the heart and the arterial walls is essential for optimal blood delivery to tissues. We investigated functional coherence between heart rhythm and aortic wall compliance in 30 volunteers aged 65 – 74. ECG and carotid and iliac pulse-wave were recorded and digitized at 2 kHz. Carotid-femoral pulse-wave transit time (cfTT) which reflex aortic compliance was assessed using the intersecting tangent...
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Testing the Effect of Bathymetric Data Reduction on the Shape of the Digital Bottom Model
PublicationDepth data and the digital bottom model created from it are very important in the inland and coastal water zones studies and research. The paper undertakes the subject of bathymetric data processing using reduction methods and examines the impact of data reduction according to the resulting representations of the bottom surface in the form of numerical bottom models. Data reduction is an approach that is meant to reduce the size...
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Topology recognition and leader election in colored networks
PublicationTopology recognition and leader election are fundamental tasks in distributed computing in networks. The first of them requires each node to find a labeled isomorphic copy of the network, while the result of the second one consists in a single node adopting the label 1 (leader), with all other nodes adopting the label 0 and learning a path to the leader. We consider both these problems in networks whose nodes are equipped with...
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Towards Scalable Simulation of Federated Learning
PublicationFederated learning (FL) allows to train models on decentralized data while maintaining data privacy, which unlocks the availability of large and diverse datasets for many practical applications. The ongoing development of aggregation algorithms, distribution architectures and software implementations aims for enabling federated setups employing thousands of distributed devices, selected from millions. Since the availability of...
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Knowledge-Based Expedited Parameter Tuning of Microwave Passives by Means of Design Requirement Management and Variable-Resolution EM Simulations
PublicationThe importance of numerical optimization techniques has been continually growing in the design of microwave components over the recent years. Although reasonable initial designs can be obtained using circuit theory tools, precise parameter tuning is still necessary to account for effects such as electromagnetic (EM) cross coupling or radiation losses. EM-driven design closure is most often realized using gradient-based procedures,...
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Exploring the Usability and User Experience of Social Media Apps through a Text Mining Approach
PublicationThis study aims to evaluate the applicability of a text mining approach for extracting UUX-related issues from a dataset of user comments and not to evaluate the Instagram (IG) app. This study analyses textual data mined from reviews in English written by IG mobile application users. The article’s authors used text mining (based on the LDA algorithm) to identify the main UUX-related topics. Next, they mapped the identified topics...
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Optimization of the Hardware Layer for IoT Systems using a Trust Region Method with Adaptive Forward Finite Differences
PublicationTrust-region (TR) algorithms represent a popular class of local optimization methods. Owing to straightforward setup and low computational cost, TR routines based on linear models determined using forward finite differences (FD) are often utilized for performance tuning of microwave and antenna components incorporated within the Internet of Things systems. Despite usefulness for design of complex structures, performance of TR methods...
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublicationBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublicationBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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Discrimination of Apple Liqueurs (Nalewka) Using a Voltammetric Electronic Tongue, UV-Vis and Raman Spectroscopy
PublicationThe capability of a phthalocyanine-based voltammetric electronic tongue to analyze strong alcoholic beverages has been evaluated and compared with the performance of spectroscopic techniques coupled to chemometrics. Nalewka Polish liqueurs prepared from five apple varieties have been used as a model of strong liqueurs. Principal Component Analysis has demonstrated that the best discrimination between liqueurs prepared from different...
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Seismic damage diagnosis in adjacent steel and RC MRFs considering pounding effects through improved wavelet-based damage-sensitive feature
PublicationThis paper aims to propose complex Morlet (cmorfb-fc) wavelet-based refined damage-sensitive feature (rDSF) as a new and more precise damage indicator to diagnose seismic damages in adjacent steel and Reinforced Concrete (RC) Moment Resisting Frames (MRFs) assuming pounding conditions using acceleration responses. The considered structures include 6- and 9-story steel and 4- and 8-story RC benchmark...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublicationWetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral...
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Rapid design optimization of antennas using variable-fidelity EM models and adjoint sensitivities
PublicationPurpose – Development of techniques for expedited design optimization of complex and numerically expensive electromagnetic (EM) simulation models of antenna structures validated both numerically and experimentally. The paper aims to discuss these issues. Design/methodology/approach – The optimization task is performed using a technique that combines gradient search with adjoint sensitivities, trust region framework, as well as...
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Investigation of long-range dependencies in the stochastic part of daily GPS solutions
PublicationThe long-range dependence (LRD) of the stochastic part of GPS-derived topocentric coordinates change (North, East, Up) results with relatively high autocorrelation values with a focus on self-similarity. One of the reasons for such self-similarity in the GPS time series are noises that are commonly recognised to prevail in the form of the flicker noise model. To prove the self-similarity of the stochastic part of GPS time series...
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Improving methods to calculate the loss of ecosystem services provided by urban trees using LiDAR and aerial orthophotos
PublicationIn this paper we propose a methodology for combining remotely sensed data with field measurements to assess selected tree parameters (diameter at breast height (DBH) and tree species) required by the i-Tree Eco model to estimate ecosystem services (ES) provided by urban trees. We determined values of ES provided by trees in 2017 in Racibórz (a city in South Poland) and estimated the loss of ES from January 1, 2017 to March 5, 2017,...
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System subwencjonowania jednostek samorządu terytorialnego w Polsce: dysfunkcje i pożądane kierunki racjonalizacji
PublicationMonografia poświęcona jest problematyce racjonalizacji subwencjonowania samorządu terytorialnego w Polsce. Jej głównym celem jest określenie roli i znaczenia subwencji w systemie finansowym jednostek samorządu terytorialnego. Za dysfunkcje w największym stopniu zniekształcające system subwencjonowania uznano: ― brak powiązania globalnej kwoty subwencji ogólnej ze składowymi budżetu państwa, ― pomijanie, przy ocenie potencjału...
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Segmentation-Based BI-RADS ensemble classification of breast tumours in ultrasound images
PublicationBackground: The development of computer-aided diagnosis systems in breast cancer imaging is exponential. Since 2016, 81 papers have described the automated segmentation of breast lesions in ultrasound images using arti- ficial intelligence. However, only two papers have dealt with complex BI-RADS classifications. Purpose: This study addresses the automatic classification of breast lesions into binary classes (benign vs. ma- lignant)...