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Search results for: computational methods
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Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublicationMusic analysis and processing aims at understanding information retrieved from music (Music Information Retrieval). For the purpose of music data mining, machine learning (ML) methods or statistical approach are employed. Their primary task is recognition of musical instrument sounds, music genre or emotion contained in music, identification of audio, assessment of audio content, etc. In terms of computational approach, music databases...
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Fast EM-Driven Nature-Inspired Optimization of Antenna Input Characteristics Using Response Features and Variable-Resolution Simulation Models
PublicationUtilization of optimization technique is a must in the design of contemporary antenna systems. Often, global search methods are necessary, which are associated with high computational costs when conducted at the level of full-wave electromagnetic (EM) models. In this study, we introduce an innovative method for globally optimizing reflection responses of multi-band antennas. Our approach uses surrogates constructed based on response...
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Rapid Design Centering of Multi-Band Antennas Using Knowledge-Based Inverse Models and Response Features
PublicationAccounting for manufacturing tolerances as well as uncertainties concerning operating conditions and material parameters is one of the important yet often neglected aspects of antenna development. Appropriate quantification of uncertainties allows for estimating the fabrication yield but also to carry out robust design (e.g., yield maximization). For reliability reasons, statistical analysis should be executed at the accuracy level...
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Performance-Driven Surrogate Modeling of High-Frequency Structures
PublicationThe development of modern high-frequency structures, including microwave and antenna components, heavily relies on full-wave electromagnetic (EM) simulation models. Notwithstanding, EM-driven design entails considerable computational expenses. This is especially troublesome when solving tasks that require massive EM analyzes, parametric optimization and uncertainty quantification be-ing representative examples. The employment of...
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Inverse surrogate modeling for low-cost geometry scaling of microwave and antenna structures
PublicationPurpose–The purpose of this paper is to investigate strategies for expedited dimension scaling ofelectromagnetic (EM)-simulated microwave and antenna structures, exploiting the concept of variable-fidelity inverse surrogate modeling.Design/methodology/approach–A fast inverse surrogate modeling technique is described fordimension scaling of microwave and antenna structures. The model is established using referencedesigns obtained...
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Fast Design Closure of Compact Microwave Components by Means of Feature-Based Metamodels
PublicationPrecise tuning of geometry parameters is an important consideration in the design of modern microwave passive components. It is mandatory due to limitations of theoretical design methods unable to quantify certain phenomena that are important for the operation and performance of the devices (e.g., strong cross-coupling effects in miniaturized layouts). Consequently, the initial designs obtained using analytical or equivalent network...
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User-assisted methodology targeted for building structure interpretable QSPR models for boosting CO2 capture with ionic liquids
PublicationTask-specific ionic liquid (IL) is an emerging class of compounds that may be environmentally friendly. Properly selected, these compounds may be green alternative to amine solutions and can replace them in post-combustion carbon dioxide (CO2) capture processes on an industrial scale. However, owing to the vast diversity of ions and their possible combinations, laboratory research is time consuming and expensive. Therefore, computational...
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Electronic nose algorithm design using classical system identification for odour intensity detection
PublicationThe two elements considered crucial for constructing an efficient environmental odour intensity monitoring systems are sensors and algorithms typically addressed to as electronic nose sensor (e-nose). Due to operational complexity of biochemical sensors developed in human bodies algorithms based on computational methods of artificial intelligence are typically considered superior to classical model based approaches in development...
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Efficient Simulation-Based Global Antenna Optimization Using Characteristic Point Method and Nature-Inspired Metaheuristics
PublicationAntenna structures are designed nowadays to fulfil rigorous demands, including multi-band operation, where the center frequencies need to be precisely allocated at the assumed targets while improving other features, such as impedance matching. Achieving this requires simultaneous optimization of antenna geometry parameters. When considering multimodal problems or if a reasonable initial design is not at hand, one needs to rely...
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Explicit Size-Reduction-Oriented Design of a Compact Microstrip Rat-Race Coupler Using Surrogate-Based Optimization Methods
PublicationIn this paper, an explicit size reduction of a compact rat-race coupler implemented in a microstrip technology is considered. The coupler circuit features a simple topology with a densely arranged layout that exploits a combination of high- and low-impedance transmission line sections. All relevant dimensions of the structure are simultaneously optimized in order to explicitly reduce the coupler size while maintaining equal power...
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Low-Cost and Precise Automated Re-Design of Antenna Structures Using Interleaved Geometry Scaling and Gradient-Based Optimization
PublicationDesign of contemporary antennas is an intricate endeavor involving multiple stages, among others, tuning of geometry parameters. In particular, re-designing antennas to different operating frequencies, makes parametric optimization imperative to ensure the best achievable system performance. If the center frequency at the current design is distant from the target one, local tuning methods generally fail, whereas global algorithms...
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Application of the Msplitmethod for filtering airborne laser scanning data-sets to estimate digital terrain models
PublicationALS point cloud filtering involves the separation of observations representing the physical terrain surface from those representing terrain details. A digital terrain model (DTM) is created from a subset of points representing the ground surface. The accuracy of the generated DTM is influenced by several factors, including the survey method used, the accuracy of the source data, the applied DTM generation algorithm, and the survey...
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Application of Msplit method for filtering airborne laser scanning data sets to estimate digital terrain models
PublicationALS point cloud filtering involves the separation of observations representing the physical terrain surface from those representing terrain details. A digital terrain model (DTM) is created from a subset of points representing the ground surface. The accuracy of the generated DTM is influenced by several factors, including the survey method used, the accuracy of the source data, the applied DTM generation algorithm, and the survey...
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Surrogate modeling of impedance matching transformers by means of variable‐fidelity electromagnetic simulations and nested cokriging
PublicationAccurate performance evaluation of microwave components can be carried out using full‐wave electromagnetic (EM) simulation tools, routinely employed for circuit verification but also in the design process itself. Unfortunately, the computational cost of EM‐driven design may be high. This is especially pertinent to tasks entailing considerable number of simulations (eg, parametric optimization, statistical analysis). A possible...
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Cost-Efficient Surrogate Modeling of High-Frequency Structures Using Nested Kriging with Automated Adjustment of Model Domain Lateral Dimensions
PublicationSurrogate models are becoming popular tools of choice in mitigating issues related to the excessive cost of electromagnetic (EM)-driven design of high-frequency structures. Among available techniques, approximation modeling is by far the most popular due to its versatility. In particular, the surrogates are exclusively based on the sampled simulation data with no need to involve engineering insight or problem-specific knowledge....
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Cost-Efficient Bi-Layer Modeling of Antenna Input Characteristics Using Gradient Kriging Surrogates
PublicationOver the recent years, surrogate modeling has been playing an increasing role in the design of antenna structures. The main incentive is to mitigate the issues related to high cost of electromagnetic (EM)-based procedures. Among the various techniques, approximation surrogates are the most popular ones due to their flexibility and easy access. Notwithstanding, data-driven modeling of antenna characteristics is associated with serious...
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Optimum number of actuators to minimize the cross-sectional area of prestressable cable and truss structures
PublicationThis paper describes a new computational method for determining the optimum number of actuators to design the optimal and economic cross-sectional area of pin-jointed assemblies based on the conventional force method. The most active members are selected to be prestressed to redistribute stress in the whole structure, resulting in regulating the internal force of bars that face high stress. Reducing stress in critical members allows...
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Divulging the anti-acetylcholinesterase activity of Colletotrichum lentis strain KU1 extract as sustainable AChE active site inhibitors
PublicationAlzheimer’s disease (AD), also called senile dementia is a neurodegenerative disease seen commonly in the elderly and is characterised by the formation of β-amyloid plaques and neurofbrillary tangles (NFT). Though a complete understanding of the disease is lacking, recent studies showed the role of the enzyme acetylcholinesterase (AChE) in pathogenesis. Finding new lead compounds from natural sources has always been a quest for...
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Tolerance Optimization of Antenna Structures by Means of Response Feature Surrogates
PublicationFabrication tolerances and other types of uncertainties, e.g., the lack of precise knowledge of material parameters, have detrimental effects on electrical and field performance of antenna systems. In the case of input characteristics these are particularly noticeable for narrow- and multi-band antennas where deviations of geometry parameters from their nominal values lead to frequency shifts of the operating frequency bands. Improving...
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Compact High Efficiency and Zero-Emission Gas-Fired Power Plant with Oxy-Combustion and Carbon Capture
PublicationReduction of greenhouse gases emissions is a key challenge for the power generation industry, requiring the implementation of new designs and methods of electricity generation. This article presents a design solution for a novel thermodynamic cycle with two new devices—namely, a wet combustion chamber and a spray-ejector condenser. In the proposed cycle, high temperature occurs in the combustion chamber because of fuel combustion...
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Reduced-Cost Microwave Modeling Using Constrained Domains and Dimensionality Reduction
PublicationDevelopment of modern microwave devices largely exploits full-wave electromagnetic (EM) simulations. Yet, simulation-driven design may be problematic due to the incurred CPU expenses. Addressing the high-cost issues stimulated the development of surrogate modeling methods. Among them, data-driven techniques seem to be the most widespread owing to their flexibility and accessibility. Nonetheless, applicability of approximation-based...
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QUEUE II Winter School
e-Learning CoursesQUEUE = QUantum and molEcUlEsIt's a school organized for all those young scientists and students who wish to learn on the basics and advances in quantum ideas and methodologies and its practical applications for living problems in chemistry, electrochemistry and material sciences. The students will learn on how to perform the quantum-chemical computations, because we have planned a big block of laboratories, aside from lectures,...
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QUEUE I Summer School
e-Learning CoursesQUEUE = QUantum and molEcUlEsIt's a school organized for all those young scientists and students who wish to learn on the basics and advances in quantum ideas and methodologies and its practical applications for living problems in chemistry, electrochemistry and material sciences. The students will learn on how to perform the quantum-chemical computations, because we have planned a big block of laboratories, aside from lectures,...
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QUEUE III Summer School
e-Learning CoursesQUEUE = QUantum and molEcUlEsIt's a school organized for all those young scientists and students who wish to learn on the basics and advances in quantum ideas and methodologies and its practical applications for living problems in chemistry, electrochemistry and material sciences. The students will learn on how to perform the quantum-chemical computations, because we have planned a big block of laboratories, aside from lectures,...
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Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction
PublicationIn recent times, customer churn has become one of the most significant issues in business-oriented sectors with telecommunication being no exception. Maintaining current customers is particularly valuable due to the high degree of rivalry among telecommunication companies and the costs of acquiring new ones. The early prediction of churned customers may help telecommunication companies to identify the causes of churn and design...
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Synthesis, structural characterization and reactivity of new trisubstituted N1-acylamidrazones: solid state and solution studies
PublicationA series of new linear trisubstituted N1-acylamidrazones have been investigated using a variety of analytical techniques and theoretical calculations to check the influence of the type of N1-acyl substituent on the resonance forms and conformational behavior in the solid state and in solution. The 1D- and 2D-NMR experiments, supported by computational studies, revealed that in solution all amidrazones exhibit conformational syn/anti...
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Rapid Antenna Optimization with Restricted Sensitivity Updates by Automated Dominant Direction Identification
PublicationMeticulous tuning of geometry parameters turns pivotal in improving performance of antenna systems. It is more and more often realized using formal optimization methods, which is demonstrably the most efficient way of handling multiple design variables, objectives, and constraints. Although in some cases a need for launching global search arises, a typical design scenario only requires local optimization, especially when a decent...
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On Inadequacy of Sequential Design of Experiments for Performance-Driven Surrogate Modeling of Antenna Input Characteristics
PublicationDesign of contemporary antennas necessarily involves electromagnetic (EM) simulation tools. Their employment is imperative to ensure evaluation reliability but also to carry out the design process itself, especially, the adjustment of antenna dimensions. For the latter, traditionally used parameter sweeping is more and more often replaced by rigorous numerical optimization, which entails considerable computational expenses, sometimes...
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Tool Wear Monitoring Using Improved Dragonfly Optimization Algorithm and Deep Belief Network
PublicationIn recent decades, tool wear monitoring has played a crucial role in the improvement of industrial production quality and efficiency. In the machining process, it is important to predict both tool cost and life, and to reduce the equipment downtime. The conventional methods need enormous quantities of human resources and expert skills to achieve precise tool wear information. To automatically identify the tool wear types, deep...
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Computer-Aided Detection of Hypertensive Retinopathy Using Depth-Wise Separable CNN
PublicationHypertensive retinopathy (HR) is a retinal disorder, linked to high blood pressure. The incidence of HR-eye illness is directly related to the severity and duration of hypertension. It is critical to identify and analyze HR at an early stage to avoid blindness. There are presently only a few computer-aided systems (CADx) designed to recognize HR. Instead, those systems concentrated on collecting features from many retinopathy-related...
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Three-dimensional numerical investigation of hybrid nanofluids in chain microchannel under electrohydrodynamic actuator
PublicationEnergy efficiency enhancement methods have received considerable attentionwithin the industry and scientific community, owing to the rising concern ofglobal energy sustainability. The present article attempts to scrutinize the effectsof electrohydrodynamics and nanofluids on the rate of heat transfer and fluidflow in the 3-D chain microchannels. Improved heat exchangers (e.g., chainmicrochannel) would have a key role in increasing...
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Modeling of medium flow processes in transportation pipelines - the synthesis of their state-space models and the analysis of the mathematical properties of the models for leak detection purposes
PublicationThe dissertation concerns the issue of modeling the pipeline flow process under incompressible and isothermal conditions, with a target application to the leak detection and isolation systems. First, an introduction to the model-based process diagnostics is provided, where its basic terminology, tools, and methods are described. In the following chapter, a review of the state of the art in the field of leak detection and isolation...
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Techniki zwiększania efektywności metody elementów skończonych poprzez redukcję dziedziny obliczeniowej z wykorzystaniem własności geometrii struktur
PublicationWspółczesna elektronika ze względu na swój szybki rozwój wymaga od nas efektywnego modelowania zjawisk polowych. Celem rozprawy jest zwiększanie efektywności metody elementów skończonych poprzez redukcję dziedziny obliczeniowej z wykorzystaniem własności geometrii struktur oraz jej hybrydyzację z użyciem technik analitycznych. Rozprawa zawiera przegląd stanu wiedzy na temat dostępnych obecnie technik modelowania jak również opis...
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Solvent influence on the crystal structures of new cadmium tri-tert -butoxysilanethiolate complexes with 1,4-bis(3-aminopropyl)piperazine: luminescence and antifungal activity
PublicationMonocrystals of dinuclear -1,4-bis(3-aminopropyl)piperazine-4N1,N10:N4,N40-bis[bis(tri-tert-butoxysilanethiolato-S)cadmium(II)], [Cd2(C12H27O3SSi)4(C10-H24N4)] or [Cd2{SSi(OtBu)3}4(-BAPP)], 1, and polynuclear catena-poly[[bis-(tri-tert-butoxysilanethiolato-S)cadmium(II)]--1,4-bis(3-aminopropyl)piperazine-2N10:N40], [Cd(C12H27O3SSi)2(C10H24N4)]n or [Cd{SSi(OtBu)3}2(-BAPP)]n,2, with 1,4-bis(3-aminopropyl)piperazine (BAPP)...
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Molecular Recognition in Complexes of TRF Proteins with Telomeric DNA
PublicationTelomeres are specialized nucleoprotein assemblies that protect the ends of linear chromosomes. In humans and many other species, telomeres consist of tandem TTAGGG repeats bound by a protein complex known as shelterin that remodels telomeric DNA into a protective loop structure and regulates telomere homeostasis. Shelterin recognizes telomeric repeats through its two major components known as Telomere Repeat-Binding Factors, TRF1...
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Multi-objective optimization of expensive electromagnetic simulation models
PublicationVast majority of practical engineering design problems require simultaneous handling of several criteria. For the sake of simplicity and through a priori preference articulation one can turn many design tasks into single-objective problems that can be handled using conventional numerical optimization routines. However, in some situations, acquiring comprehensive knowledge about the system at hand, in particular, about possible...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublicationComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublicationSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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Rapid tolerance‐aware design of miniaturized microwave passives by means of confined‐domain surrogates
PublicationThe effects of uncertainties, primarily manufacturing tolerances but also incomplete information about operating conditions or material parameters, can be detrimental to the performance of microwave components. Quantification of such effects is essential to ensure a meaningful evaluation of the structure, in particular, its reliability under imperfect fabrication procedures. The improvement of the circuit robustness can be achieved...
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Daylight Appraisal Classes For Achitecture Students A Survey Combined With A Practical Assessment For Educational Training Recommendations
PublicationThe main objectives of this article are: (i) to present the relations between architecture students' subjective assessment of daylight in classrooms and the objective evaluation of daylit conditions using daylight simulations tools, (ii) to formulate guidelines and recommendations on daylight appraisal methods and tools which may be useful in architectural training. The methodology used includes an evaluation of the results of...
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Concrete mix design using machine learning
PublicationDesigning a concrete mix is a process of synthesizing many components, it is not a simple process and requires extensive technical knowledge. The design process itself focuses on obtaining the required strength of concrete. Very often designing a concrete mix takes into account the need to maintain the proper water-demand and frost-resistance features. The parameters that influence the concrete class most significantly are the...
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Proceedings of the fib Symposium 2019: Concrete - Innovations in Materials, Design and Structures 2019
PublicationDesigning a concrete mix is a process of synthesizing many components, it is not a simple process and requires extensive technical knowledge. The design process itself focuses on obtaining the required strength of concrete. Very often designing a concrete mix takes into account the need to maintain the proper water-demand and frost-resistance features. The parameters that influence the concrete class most significantly are the...
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Novel steroid sulfatase inhibitors based on N ‐thiophosphorylated 3‐(4‐aminophenyl)‐coumarin‐7‐O‐sulfamates
PublicationIn the present work, we described convenient methods for the synthesis ofN-thiophosphorylated 3-(4-aminophenyl)-coumarin-7-O-sulfamates as steroid sulfatase(STS) inhibitors. To design the structures of the potential STS inhibitors, molecularmodeling techniques were used. A computational docking method was used to deter-mine the binding modes of the synthesized inhibitors as well as to identify potentialinteractions between specified...
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Solvent influence on the crystal structures of new cadmium tri-tert -butoxysilanethiolate complexes with 1,4-bis(3-aminopropyl)piperazine: luminescence and antifungal activity
PublicationMonocrystals of dinuclear 1,4-bis(3-aminopropyl)piperazine-�4N1,N10:N4,N40-bis[bis(tri-tert-butoxysilanethiolato-�S)cadmium(II)], [Cd2(C12H27O3SSi)4(C10-H24N4)] or [Cd2{SSi(OtBu)3}4(�-BAPP)], 1, and polynuclear catena-poly[[bis- (tri-tert-butoxysilanethiolato-�S)cadmium(II)]-�-1,4-bis(3-aminopropyl)piperazine-�2N10:N40], [Cd(C12H27O3SSi)2(C10H24N4)]n or [Cd{SSi(OtBu)3}2(�-BAPP)]n, 2, with 1,4-bis(3-aminopropyl)piperazine (BAPP)...
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Concurrent Video Denoising and Deblurring for Dynamic Scenes
PublicationDynamic scene video deblurring is a challenging task due to the spatially variant blur inflicted by independently moving objects and camera shakes. Recent deep learning works bypass the ill-posedness of explicitly deriving the blur kernel by learning pixel-to-pixel mappings, which is commonly enhanced by larger region awareness. This is a difficult yet simplified scenario because noise is neglected when it is omnipresent in a wide...
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Algorithmic Human Resources Management - Perspectives and Challenges
PublicationTheoretical background: Technology – most notably processes of digitalisation, the use of artificial intelligence, machine learning, big data and prevalence of remote work due to pandemic – changes the way organizations manage human resources. One of the increasing trends is the use of so-called “algorithmic management”. It is notably different than previous e-HRM or HRIS (human resources information systems) applications, as it...
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Prediction of Overall In Vitro Microsomal Stability of Drug Candidates Based on Molecular Modeling and Support Vector Machines. Case Study of Novel Arylpiperazines Derivatives
PublicationOther than efficacy of interaction with the molecular target, metabolic stability is the primary factor responsible for the failure or success of a compound in the drug development pipeline. The ideal drug candidate should be stable enough to reach its therapeutic site of action. Despite many recent excellent achievements in the field of computational methods supporting drug metabolism studies, a well-recognized procedure to model...
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Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
PublicationThe importance of surrogate modeling techniques has been gradually increasing in the design of antenna structures over the recent years. Perhaps the most important reason is a high cost of full-wave electromagnetic (EM) analysis of antenna systems. Although imperative in ensuring evaluation reliability, it entails considerable computational expenses. These are especially pronounced when carrying out EM-driven design tasks such...
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Fast multi-objective optimization of antenna structures by means of data-driven surrogates and dimensionality reduction
PublicationDesign of contemporary antenna structures needs to account for several and often conflicting objectives. These are pertinent to both electrical and field properties of the antenna but also its geometry (e.g., footprint minimization). For practical reasons, especially to facilitate efficient optimization, single-objective formulations are most often employed, through either a priori preference articulation, objective aggregation,...
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublicationObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...