Wyniki wyszukiwania dla: SURROGATE-MODEL-ASSISTED EVOLUTIONARY ALGORITHM
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Microwave Characterization of Dielectric Sheets in a Plano-Concave Fabry-Perot Open Resonator
PublikacjaDespite its long history, a double-concave (DC) Fabry-Perot open resonator (FPOR) has recently gained popularity in the characterization of dielectrics in the 20–110 GHz range, mainly due to such novel accomplishments as full automation of the measurement process and the development of even ore accurate and computationally efficient electromagnetic model. However, it has been discovered that such a DC resonator suffers from unwanted...
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Probabilistic assessment of SMRFs with infill masonry walls incorporating nonlinear soil-structure interaction
PublikacjaInfill Masonry Walls (IMWs) are used in the perimeter of a building to separate the inner and outer space. IMWs may affect the lateral behavior of buildings, while they are different from those partition walls that separate two inner spaces. This study focused on the seismic vulnerability assessment of Steel Moment-Resisting Frames (SMRFs) assuming different placement of IMWs incorporating nonlinear Soil-Structure Interaction (SSI)....
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Predicting the seismic collapse capacity of adjacent SMRFs retrofitted with fluid viscous dampers in pounding condition
PublikacjaSevere damages of adjacent structures due to structural pounding during earthquakes have emphasized the need to use some seismic retrofit strategy to enhance the structural performance. The purpose of this paper is to study the influence of using linear and nonlinear Fluid Viscous Dampers (FVDs) on the seismic collapse capacities of adjacent structures prone to pounding and proposing modification factors to modify the median...
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Multi-objective optimization of the cavitation generation unit structure of an advanced rotational hydrodynamic cavitation reactor
PublikacjaHydrodynamic cavitation (HC) has been widely considered a promising technique for industrial-scale process intensifications. The effectiveness of HC is determined by the performance of hydrodynamic cavitation reactors (HCRs). The advanced rotational HCRs (ARHCRs) proposed recently have shown superior performance in various applications, while the research on the structural optimization is still absent. The present study, for the...
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Cross-talk Between the Heart and Arteries in Older 65+ Adults
PublikacjaRegulatory 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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Topology recognition and leader election in colored networks
PublikacjaTopology 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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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublikacjaBreast 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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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublikacjaBreast 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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Knowledge-Based Expedited Parameter Tuning of Microwave Passives by Means of Design Requirement Management and Variable-Resolution EM Simulations
PublikacjaThe 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
PublikacjaThis 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
PublikacjaTrust-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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Towards Scalable Simulation of Federated Learning
PublikacjaFederated 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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Seismic damage diagnosis in adjacent steel and RC MRFs considering pounding effects through improved wavelet-based damage-sensitive feature
PublikacjaThis 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
PublikacjaWetlands 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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Discrimination of Apple Liqueurs (Nalewka) Using a Voltammetric Electronic Tongue, UV-Vis and Raman Spectroscopy
PublikacjaThe 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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Rapid design optimization of antennas using variable-fidelity EM models and adjoint sensitivities
PublikacjaPurpose – 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
PublikacjaThe 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
PublikacjaIn 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
PublikacjaMonografia 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
PublikacjaBackground: 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)...