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Search results for: FEATURE-BASED MODELING
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Cost-Efficient Two-Level Modeling of Microwave Passives Using Feature-Based Surrogates and Domain Confinement
PublicationA variety of surrogate modelling techniques has been utilized in high-frequency design over the last two decades. Yet, the curse of dimensionality still poses a serious challenge in setting up re-liable design-ready surrogates of modern microwave components. The difficulty of the model-ing task is only aggravated by nonlinearity of circuit responses. Consequently, constructing a practically usable surrogate model, valid across...
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OmicSelector: automatic feature selection and deep learning modeling for omic experiments
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Response Feature Technology for High-Frequency Electronics. Optimization, Modeling, and Design Automation
PublicationThis book discusses response feature technology and its applications to modeling, optimization, and computer-aided design of high-frequency structures including antenna and microwave components. By exploring the specific structure of the system outputs, feature-based approaches facilitate simulation-driven design procedures, both in terms of improving their computational efficiency and reliability. These benefits are associated...
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Auditory-model based robust feature selection for speech recognition
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Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition
Publicationconvolutional neural network (CNN) which is a class of deep, feed-forward artificial neural network. We decided to analyze audio signal feature maps, namely spectrograms, linear and Mel-scale cepstrograms, and chromagrams. The choice was made upon the fact that CNN performs well in 2D data-oriented processing contexts. Feature maps were employed in the Lithuanian word recognition task. The spectral analysis led to the highest word...
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Modeling Volunteer Based Systems
PublicationThere are two main approaches to processing tasks requiring high amounts of computational power. One approach is using clusters of mostly identical hardware, placed in dedicated locations [1, 2, 3]. The other approach is outsourcing computing resources from large numbers of volunteers connected to the Internet [7]. This chapter presents an application of a mathematical model of the volunteer computing presented in Volume 1 of this...
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Agent-Based RBF Network Classifier with Feature Selection in a Kernel Space
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Cluster-dependent rotation-based feature selection for the RBF networks initialization
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Feature-based generation of machining process plans for optimised parts manufacture
PublicationPrzedstawiono aktualne zagadnienia związane z integracją systemów CAD/CAM/CAPP. Opracowano model informacyjny danych dla systemu CAPP w postaci zapisu macierzowego. Zawarto algorytm tworzenia rozwiązań wariantowych i wyboru optymalnego procesu technologicznego obróbki. Proponowany algorytm działania zweryfikowano na rzeczywistym przykładzie z praktyki przemysłu.
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Data Sampling-Based Feature Selection Framework for Software Defect Prediction
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Prediction based on integration of Decisional DNA and a feature selection algorithm Relief-F
PublicationThe paper presents prediction model based on Decisional DNA and Set of experienced integrated with Relief_F algorithm for feature selection
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A Study of Cross-Linguistic Speech Emotion Recognition Based on 2D Feature Spaces
PublicationIn this research, a study of cross-linguistic speech emotion recognition is performed. For this purpose, emotional data of different languages (English, Lithuanian, German, Spanish, Serbian, and Polish) are collected, resulting in a cross-linguistic speech emotion dataset with the size of more than 10.000 emotional utterances. Despite the bi-modal character of the databases gathered, our focus is on the acoustic representation...
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Rapid Yield Estimation and Optimization of Microwave Structures Exploiting Feature-Based Statistical Analysis
PublicationIn this paper, we propose a simple, yet reliable methodology to expediteyield estimation and optimization of microwave structures. In our approach,the analysis of the entire response of the structure at hand (e.g., $S$-parameters asa function of frequency) is replaced by response surface modeling of suitablyselected feature points. On the one hand, this is sufficient to determinewhether a design satisfies given performance specifications....
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Current based Normalized Triple Covariance as a bearings diagnostic feature in induction motor
PublicationDiagnosis of induction motors, conducted remotely by measuring and analyzing the supply current is attractive with the lack of access to the engine. So far there is no solution, based on analysis of current, the credibility of which allow use in industry. Statistics of IM bearing failures of induction motors indicate, that they constitute more than 40% of IM damage, therefore bearing diagnosis is so important. The article provides...
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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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Multidimensional Feature Selection and Interaction Mining with Decision Tree Based Ensemble Methods
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Tree-based homogeneous ensemble model with feature selection for diabetic retinopathy prediction
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Fundamentals of Physics-Based Surrogate Modeling
PublicationChapter 1 was focused on data-driven (or approximation-based) modeling methods. The second major class of surrogates are physics-based models outlined in this chapter. Although they are not as popular, their importance is growing because of the challenges related to construction and handling of approximation surrogates for many real-world problems. The high cost of evaluating computational models, nonlinearity of system responses,...
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Alternative Modeling of Volunteer Based Systems
PublicationThe canonical approach to model a flow of a voluntary based computing, as presented in Chapter 7 may tax the capacity of the simulator, especially when a more complex model of Voluntary Computing, proposed in [1], is used which would imply that, for typical heterogeneous groups of volunteers, several thousands of threads would have to be run inside the simulator, to mimic closely the behaviour of every volunteer. This chapter presents...
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Computationally-Efficient Statistical Design and Yield Optimization of Resonator-Based Notch Filters Using Feature-Based Surrogates
PublicationModern microwave devices are designed to fulfill stringent requirements pertaining to electrical performance, which requires, among others, a meticulous tuning of their geometry parameters. When moving up in frequency, physical dimensions of passive microwave circuits become smaller, making the system performance increasingly susceptible to manufacturing tolerances. In particular, inherent inaccuracy of fabrication processes affect...
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Rapid design closure of microwave components by means of feature-based optimization and adjoint sensitivities
PublicationIn this article, fast design closure of microwave components using feature-based optimization (FBO) and adjoint sensitivities is discussed. FBO is one of the most recent optimization techniques that exploits a particular structure of the system response to “flatten” the functional landscape handled during the optimization process, which leads to reducing its computational complexity. When combined with gradient-based search involving...
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Tolerance-Aware Multi-Objective Optimization of Antennas by Means of Feature-Based Regression Surrogates
PublicationAssessing the immunity of antenna design to fabrication tolerances is an important consideration, especially when the manufacturing process has not been predetermined. At the same time, the antenna parameter tuning should be oriented toward improving the performance figures pertinent to both electrical (e.g., input matching) and field properties (e.g., axial ratio bandwidth) as much as possible. Identification of available trade-offs...
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Current-based higher-order spectral covariance as a bearing diagnostic feature for induction motors
PublicationConducting the diagnosis of induction motors remotely by analyzing the supply current is an attractive prospect with the lack of access to the engine. Currently, there is no solution, based on analysis of the current, the credibility of which would allow its use in industry. The statistics of bearing failures in induction motors indicate that they constitute more than 40% of induction motor damage, therefore, bearing diagnosis...
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A cortex-like model for animal recognition based on texture using feature-selective hashing
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Feature-Based Characterisation of Turned Surface Topography with Suppression of High-Frequency Measurement Errors
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Triangulation-based Constrained Surrogate Modeling of Antennas
PublicationDesign of contemporary antenna structures is heavily based on full-wave electromagnetic (EM) simulation tools. They provide accuracy but are CPU-intensive. Reduction of EM-driven design procedure cost can be achieved by using fast replacement models (surrogates). Unfortunately, standard modeling techniques are unable to ensure sufficient predictive power for real-world antenna structures (multiple parameters, wide parameter ranges,...
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Traffic Modeling in IMS-based NGN Networks
PublicationIn the modern world the need for accurate and quickly delivered information is becoming more and more essential. In order to fulfill these requirements, next generation telecommunication networks should be fast introduced and correctly dimensioned. For this reason proper traffic models must be identified, which is the subject of this paper. In the paper standardization of IMS (IP Multimedia Subsystem) concept and IMS-based NGN...
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Machining process sequencing and machine assignment in generative feature-based CAPP for mill-turn parts
PublicationProcess selection and sequencing, as one of the most complex issues when evaluated from a mathematical point of view and crucial in CAPP, still attract research attention. For the current trend of intelligent manufacturing, machining features (MFs) are the information carriers for workpiece geometry and topology representation. They are basically derived from CAD models and are used by downstream engineering applications. A feature-based...
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Optimization-Based Robustness Enhancement of Compact Microwave Component Designs with Response Feature Regression Surrogates
PublicationThe ability to evaluate the effects of fabrication tolerances and other types of uncertainties is a critical part of microwave design process. Improving the immunity of the device to parameter deviations is equally important, especially when the performance specifications are stringent and can barely be met even assuming a perfect manufacturing process. In the case of modern miniaturized microwave components of complex topologies,...
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Pupil detection supported by Haar feature based cascade classifier for two-photon vision examinations
PublicationThe aim of this paper is to present a novel method, called Adaptive Edge Detection (AED), of extraction of precise pupil edge coordinates from eye image characterized by reflections of external illuminators and laser beams. The method is used for monitoring of pupil size and position during psychophysical tests of two-photon vision performed by dedicated optical set-up. Two-photon vision is a new phenomenon of perception of short-pulsed...
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Pupil detection supported by Haar feature based cascade classifier for two-photon vision examinations
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Knowledge-based performance-driven modeling of antenna structures
PublicationThe importance of surrogate modeling techniques in the design of modern antenna systems has been continuously growing over the recent years. This phenomenon is a matter of practical necessity rather than simply a fashion. On the one hand, antenna design procedures rely on full-wave electromagnetic (EM) simulation tools. On the other hand, the computational costs incurred by repetitive EM analyses involved in solving common tasks...
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Physics-Based Coarse-Grained Modeling in Bio- and Nanochemistry
PublicationCoarse-grained approaches, in which groups of atoms are represented by single interaction sites, are very important in biological and materials sciences because they enable us to cover the size- and time-scales by several orders of magnitude larger than those available all-atom simulations, while largely keeping the details of the systems studied. The coarse-grained approaches differ by the scheme of reduction and by the origin...
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Design-oriented computationally-efficient feature-based surrogate modelling of multi-band antennas with nested kriging
PublicationDesign of modern antenna structures heavily depends on electromagnetic (EM) simulation tools. EM analysis provides reliable evaluation of increasingly complex designs but tends to be CPU intensive. When multiple simulations are needed (e.g., for parameters tuning), the aggregated simulation cost may become a serious bottleneck. As one possible way of mitigating the issue, the recent literature fosters utilization of faster representations,...
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Global EM-Driven Optimization of Multi-Band Antennas Using Knowledge-Based Inverse Response-Feature Surrogates
PublicationElectromagnetic simulation tools have been playing an increasing role in the design of contemporary antenna structures. The employment of electromagnetic analysis ensures reliability of evaluating antenna characteristics but also incurs considerable computational expenses whenever massive simulations are involved (e.g., parametric optimization, uncertainty quantification). This high cost is the most serious bottleneck of simulation-driven...
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Expedited Feature-Based Quasi-Global Optimization of Multi-Band Antenna Input Characteristics with Jacobian Variability Tracking
PublicationDesign of modern antennas relies—for reliability reasons—on full-wave electromagnetic simulation tools. In addition, increasingly stringent specifications pertaining to electrical and field performance, growing complexity of antenna topologies, along with the necessity for handling multiple objectives, make numerical optimization of antenna geometry parameters a highly recommended design procedure. Conventional algorithms, particularly...
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Global Surrogate Modeling by Neural Network-Based Model Uncertainty
PublicationThis work proposes a novel adaptive global surrogate modeling algorithm which uses two neural networks, one for prediction and the other for the model uncertainty. Specifically, the algorithm proceeds in cycles and adaptively enhances the neural network-based surrogate model by selecting the next sampling points guided by an auxiliary neural network approximation of the spatial error. The proposed algorithm is tested numerically...
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Performance-Based Nested Surrogate Modeling of Antenna Input Characteristics
PublicationUtilization of electromagnetic (EM) simulation tools is mandatory in the design of contemporary antenna structures. At the same time, conducting designs procedures that require multiple evaluations of the antenna at hand, such as parametric optimization or yield-driven design, is hindered by a high cost of accurate EM analysis. To certain extent, this issue can be addressed by utilization of fast replacement models (also referred...
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Design and modeling of the piezoelectric motor based on three resonance actuators
PublicationThis paper describes a piezoelectric motor which combines advantages from two existing piezoelectric motors topologies. The research work presents the design, simulations and measurements of the piezoelectric motor with three rotation-mode actuators. The aim of the project was to obtain the high speed piezoelectric motor. Other advantages of this conception are blocking torque, short response times, the ability to work in a hostile...
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FEM modeling of structures based on close range digital photogrammetry
PublicationPraca dotyczy metodologii przygotowania modelu konstrukcji istniejącej do analizy mechanicznej metodą element ow skończonych. MOdelowanie geometrii budowli jest oparte na danych pozyskanych z pomiarów fotogrametrycznych. Praca wskazuje na możliwości oraz efektywność zastosowania metod optometrycznych w rewitalizacji budowli zabytkowych, an przykładzie modelu dachu drewnianego.
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Soft modeling support for managing knowledge-based information technology (IT)
PublicationW pracy omówiono metody miękkiego modelowania. Wskazano na możliwości zastosowania tych metod do wspomagania tworzenia systemów opartych na wiedzy. Omówiono także metody oparte na teorii zbiorów rozmytych.
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Performance Modeling and Prediction of Real Application Workload in a Volunteer-based System
PublicationThe goal of this paper is to present a model that predicts the real workload placed on a volunteer based system by an application, with incorporation of not only performance but also availability of volunteers. The application consists of multiple data packets that need to be processed. Knowing the computational workload demand of a single data packet we show how to estimate the application workload in a volunteer based system. Furthermore,...
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Knowledge-Based Virtual Modeling and Simulation of Manufacturing Processes for Industry 4.0
PublicationABSTRACT Industry 4.0 aims at providing a digital representation of a production landscape, but the challenges in building, maintaining, optimizing, and evolving digital models in inter-organizational production chains have not been identified yet in a systematic manner. In this paper, various Industry 4.0 research and technical challenges are addressed, and their present scenario is discussed. Moreover, in this article, the novel...
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Inverse Modeling and Optimization of CSRR-based Microwave Sensors for Industrial Applications
PublicationDesign optimization of multivariable resonators is a challenging topic in the area of microwave sensors for industrial applications. This paper proposes a novel methodology for rapid re-design and parameter tuning of complementary split-ring resonators (CSRRs). Our approach involves inverse surrogate models established using pre-optimized resonator data as well as analytical correction techniques to enable rapid adjustment of geometry...
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Modeling the Customer’s Contextual Expectations Based on Latent Semantic Analysis Algorithms
PublicationNowadays, in the age of Internet, access to open data detects the huge possibilities for information retrieval. More and more often we hear about the concept of open data which is unrestricted access, in addition to reuse and analysis by external institutions, organizations and people. It’s such information that can be freely processed, add another data (so-called remix) and then published. More and more data are available in text...
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Modeling of Heat Source Based on Parameters of Electron Beam Welding Process
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Mathematical Modeling of Hydrodynamics in Bioreactor by Means of CFD-Based Compartment Model
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Accidental wow evaluation based on sinusoidal modeling and neural nets prediction
PublicationReferat przedstawia opis algorytmu do określenia charakterystyki zniekształcenia kołysania dźwięku. Prezentowane podejście wykorzystuje sinusoidalną analizę dźwięku bazującą zarówno na amplitudowym jak i fazowym widmie sygnału fonicznego. Trajektorie poszczególnych składowych tonalnych, obrazujące zniekształcenie kołysania, określane są na podstawie analizy ich chwilowych amplitud, częstotliwości i faz. Dodatkowo referat przedstawia...
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Improved Procedures for Feature-Based Suppression of Surface Texture High-Frequency Measurement Errors in the Wear Analysis of Cylinder Liner Topographies
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Prediction of Protein Structure by Template-Based Modeling Combined with the UNRES Force Field
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