Evaluation Of Transfer Function Research Articles

Predicting Student Academic Performance Using Neural Networks: Analyzing the Impact of Transfer Functions, Momentum and Learning Rate

Artificial Neural Networks (ANN) demonstrate a compelling application of AI in predicting student performance, a critical aspect for both students and educators. Accurate forecasting of student achievements enables educators to monitor progress effectively, allowing educational institutions to optimize outcomes and improve student results. This study focuses on leveraging ANN for predictive analytics in student performance. Through a detailed evaluation of transfer functions, optimizers, learning rates, and momentum values, the model achieves an impressive 98% accuracy with specific configurations: a learning rate of 0.005, momentum of 0.7, Sigmoid transfer function, and SGD optimizer. Additionally, the study performs a comparative analysis of various Machine Learning Algorithms, including ANN, Support Vector Machines (SVM), K-Nearest Neighbors (KNN), Decision Trees (DT), Naive Bayes (NB), and Logistic Regression (LR). Using data from 689 B.Tech students at IP University, the analysis reveals that ANN outperforms other algorithms with an accuracy of 97%. This high accuracy demonstrates the potential of ANN in educational settings, providing a valuable tool for educators to enhance student performance and outcomes.

Absolute Evaluation of the Optical Transfer Function of the High Aperture Infrared Cryogenic Objective

Absolute Evaluation of the Optical Transfer Function of the High Aperture Infrared Cryogenic Objective

Derivation and Evaluation of Transfer Function of Output Voltage to Input Voltage Amplitude in Cockcroft-Walton Circuit

Derivation and Evaluation of Transfer Function of Output Voltage to Input Voltage Amplitude in Cockcroft-Walton Circuit

Experimental and numerical investigations of forced response of multi-element lean-premixed hydrogen flames

Understanding the distinctive thermoacoustic properties of multi-element lean-premixed hydrogen flames is crucial for the development of hydrogen-capable gas turbines. Extending our earlier investigations of the self-excited dynamics of a cluster of lean-premixed pure hydrogen-air flames, here we explore the dynamic response to harmonic velocity perturbations, using an integrative approach combining loudspeaker-forced direct measurements and LES-based numerical simulations. Electronically-excited OH intensity distribution, generally assumed to be equivalent to the flame's heat release rate, shows an anchored conical reaction zone. Numerical simulations of heat release rate contours, however, reveal the formation of a more concentrated thin annulus region resembling an inverted V shaped layer, created by preferential diffusion of hydrogen molecules. This difference between OH-intensity distribution and heat release rate contours suggests consequential uncertainties in surrogate-dependent flame transfer function evaluations; the transfer function gains from measured data are well defined by a fast-decaying low-pass filter behavior, but the simulation result exhibits slowly-decaying large gain with slight overshoot over the entire range of frequency. Because the systematic uncertainties associated with the estimation of the flame's heat release rate cannot be accurately quantified, we rely on a reduced-order network modeling framework combined with direct measurement to test the accuracy of the prediction of the growth of self-sustained pressure fluctuations. We demonstrate that LES-based transfer functions predict the system's stability more accurately, and this suggests that the calculated heat release rate data are closer to the hydrogen flame's true heat release response than the wavelength-specific light intensity measurement. This assessment enables us to identify structurally simple moderate transverse oscillations of local regions containing atypically concentrated energy as pivotal processes controlling high-frequency hydrogen combustion dynamics.

Initial validation of a closed loop filter and controller approach for active stabilization of thermomechanical distortions

Increasing technological progress in space technology is accompanied by an increased demand for accuracy. The alignment of optical instruments or antennas on the satellite platform requires structural stability that can no longer be achieved with traditional, passive methods, such as the use of materials with high stiffness or low coefficient of thermal expansion. Within the Infrared Astronomy Satellite Swarm Interferometry (IRASSI) project, an approach to actively stabilizing structures against low-frequency periodic heat induced deformations has been developed and simulated. In this study, the basic functionality of that thermomechanical FEM model is demonstrated by means of the thermal transfer functions between the changes in the applied heat and the resulting temperature changes, as well as a closed loop filter and controller approach consisting of a Linear Quadratic Regulator (LQR) and a Kalman filter. For this purpose, an experimental setup consisting of an aluminum plate with 14 temperature sensors, four heating elements for controlling the structure and one heating element for simulating the perturbation is used. The evaluation of the thermal transfer functions in the model compared to the experimental setup shows a deviation of the phase shift of less than 0.6% and an amplitude shift of less than 3.5% on average. A Kalman filter processes the temperature measurement in order to obtain an optimal estimate for the LQR controller, which then calculates the necessary change in the heating power of the four control heating elements to minimize the displacements at the desired two positions in x- and y-direction. The verification is performed by a camera system as an external validation tool, which is able to resolve micron-scale displacements by measuring the spatial displacement of a speckle pattern applied to the structure using sub-pixel accurate image correlation algorithms. While the range of values of the amplitudes of the displacements is 8.93 μ in the uncontrolled case, an improvement of more than 4.6dB could be achieved by applying the filter and controller system. Thus, it is demonstrated that this method has the potential to further improve already highly stable structures or to make lighter and cheaper materials with poorer passive stability values usable through active structural stabilization.

Combining monthly wind and inflow uncertainties in the stochastic dual dynamic programming

AbstractFollowing a global trend, intermittent sources, especially wind, have been experiencing accelerated growth in Brazil—in the last decade, wind power grew 13 times and became the second largest source in the electricity mix (12%), just behind hydropower (60%). Currently, although following regulatory guidelines, the representation of wind power in the long-term operation planning model is done in a simplified way, based on the monthly average of the last five years of aggregated generation, thus demanding improvements. The objective of this work is to describe an approach to be used by the Brazilian power industry to represent the uncertainties of monthly wind power production in the SDDP algorithm applied in the long-term operation planning model, keeping the large-scale stochastic problem still computationally viable, when applied to large interconnected systems, especially with hydroelectric predominance. The proposed methodology comprises statistical clustering of wind regimes and definition of equivalent wind farms; evaluation of monthly transfer functions between wind speed and power production; integrated generation of monthly multivariate synthetic scenarios of inflows and winds, considering associated cross-correlations; and representing monthly wind power in the SDDP algorithm. The application to real configurations of the Brazilian interconnected system, including case studies related to the monthly operation program and the calculation of the maximum amount of energy that can be traded in long-term power purchase agreements, points to its effectiveness and the relevance of modeling the wind uncertainties in the long-term operation planning of large hydro-dominated systems.

Modulation transfer function (MTF) evaluation for x-ray phase imaging system employing attenuation masks

Objective. Attenuation masks can be used in x-ray imaging systems to increase their inherent spatial resolution and/or make them sensitive to phase effects, a typical example being Edge Illumination x-ray phase contrast imaging (EI-XPCI). This work investigates the performance of a mask-based system such as EI-XPCI in terms of Modulation Transfer Function (MTF), in the absence of phase effects. Approach. Pre-sampled MTF measurements, using an edge, were performed on the same system implemented without masks, with non-skipped masks and finally with skipped masks (i.e. masks in which apertures illuminate every other pixel row/column). Results are compared to simulations and finally images of a resolution bar pattern acquired with all the above setups are presented. Main results. Compared to the detector’s inherent MTF, the non-skipped mask setup provides improved MTF results. In comparison to an ideal case where signal spill-out into neighbouring pixels is negligible, this improvement takes place only at specific frequencies of the MTF, dictated by the spatial repetition of the spill-out signal. This is limited with skipped masks, which indeed provide further MTF improvements over a larger frequency range. Experimental MTF measurements are supported through simulation and resolution bar pattern images. Significance. This work has quantified the improvement in MTF due to the use of attenuation masks and lays the foundation for how acceptance and routine quality control tests will have to be modified when systems using masks are introduced in clinical practice and how MTF results will compare to those of conventional imaging systems.

Training program for the metric specification of imaging sensors

Measurement systems in industrial practice are becoming increasingly complex and the system-technical integration levels are increasing. Nevertheless, the functionalities can in principle always be traced back to proven basic functions and basic technologies, which should, however, be understood and developed. For this very reason, the teaching of elementary basics in engineering education is unavoidable. The present paper presents a concept to implement a contemporary training program within the practical engineering education on university level in the special subject area of optical coordinate measuring technology. The students learn to deal with the subject area in a fundamentally oriented way and to understand the system-technical integration in detail from the basic idea to the actual solution, which represents the common practice in the industrial environment. The training program is designed in such a way that the basics have to be worked out at the beginning, gaps in knowledge are closed by the aspect of group work and the targeted intervention of a supervisor. After the technology has been fully developed theoretically, the system is put into operation and applied with regard to a characterizing measurement. The measurement data are then evaluated using standardized procedures. A special part of the training program, which is to promote the own creativity and the comprehensible understanding, represents the evaluation of the modulation transfer function (MTF) of the system by a self-developed algorithmic program section in the script-oriented development environment MALTAB, whereby students can supportively fall back on predefined functions for the evaluation, whose implementation however still must be accomplished.

Iliski, a software for robust calculation of transfer functions.

Understanding the relationships between biological processes is paramount to unravel pathophysiological mechanisms. These relationships can be modeled with Transfer Functions (TFs), with no need of a priori hypotheses as to the shape of the transfer function. Here we present Iliski, a software dedicated to TFs computation between two signals. It includes different pre-treatment routines and TF computation processes: deconvolution, deterministic and non-deterministic optimization algorithms that are adapted to disparate datasets. We apply Iliski to data on neurovascular coupling, an ensemble of cellular mechanisms that link neuronal activity to local changes of blood flow, highlighting the software benefits and caveats in the computation and evaluation of TFs. We also propose a workflow that will help users to choose the best computation according to the dataset. Iliski is available under the open-source license CC BY 4.0 on GitHub (https://github.com/alike-aydin/Iliski) and can be used on the most common operating systems, either within the MATLAB environment, or as a standalone application.

LCD-based method for evaluating modulation transfer function of optical lenses with poorly corrected distortion

Modulation transfer function (MTF) evaluation in the imaging of the optical lenses with poorly corrected geometric distortion involves sampling region of interest (ROI) images that are affected by geometric distortion, reducing its accuracy. A based liquid-crystal-device MTF (LMTF) method is proposed for this purpose by evaluating MTF of the medical rigid endoscope. This method establishes a mathematical model of geometric distortion and analyzes two sampling ROI image manners in MTF evaluation. Compared with the distortion factor (DF) manner, the distortion correction manner relaxes the value of the DF to twice the maximum non-distortion value, extends the sampling ROI image to twice the size, reduces the average RRMSE value to 6%, and improves average accuracy on MTF by 1.2%. The experimental results provide good agreement with the theoretical prediction. Therefore, the proposed LMTF method can be referential for the other optical lenses with poorly corrected distortion.

Construction and Evaluation of Transfer Function of Marginal Soil Temperature on the South Side of Greenhouse under Different Linings

The marginal soil temperature on the south side of a greenhouse remains at low temperatures in winter for long periods, which affects crop growth and land-use efficiency, it is of great significance to grasp the influencing factors of soil temperature change to improve the marginal soil temperature on the south side of the greenhouse. This study was conducted in at typical greenhouse in the cold and arid area of northern China and used the Grey Relational Analysis (GRA) method, the relational degree between the marginal soil temperature on the south side of the greenhouse and environmental factors under different lining structures was analyzed, and established the soil temperature transfer function. The results show that soil temperature had the greatest correlation with the soil humidity and air humidity inside and outside the greenhouse, and the second greatest correlation was the relation with the air temperature inside and outside the greenhouse and the outdoor soil temperature; the lining structure could effectively reduce the relation between soil temperature and humidity inside and outside the greenhouse. Polystyrene extruded board (PEB) had a greater degree of relational reduction than other lining materials in the test. Through verification analysis, the mean absolute error of soil temperature of 5 cm was less than 0.85 °C, the average absolute error of soil temperature at 15 cm was less than 0.57 °C, and the average absolute error of soil temperature at 25 and 55 cm was less than 0.2 °C. In conclusion, the constructed soil temperature transfer function could be used to predict the variation trend of soil temperature, and the PEB material lining structure had good thermal insulation.

An analysis of methods for aberrated spot diagram center evaluation

The paper considers spot diagram center evaluation methods and errors depending on aberration type and value. The authors present the modified center of mass method which provides higher accuracy of center evaluation for spot diagram with coma. Error estimation methods involved using simulated spot diagram with symmetrical and non-symmetrical aberrations of the third and fifth order and their combinations. The error of center evaluation by the maximum value method and center of mass method is analyzed. The proposed modified center of mass method gives higher weight for pixels with higher intensity that leads to better sensitivity of the method and it is compared with other methods. The center of mass method can evaluate accurate center position only for coma-free spot diagram. The maximum value method cannot evaluate accurate center position for spot diagram with coma either and for coma-free spot diagram it can also produce larger errors than the center of mass method. The modified center of mass method is more robust and evaluates center for spot diagram with coma and other aberrations more accurately. The modified center of mass method shows higher accuracy while evaluating center of spot diagram with aberration, and hence higher accuracy of modulation transfer function evaluation by spot diagram. The precise evaluation of spot diagram center will also increase the convergence of the phase retrieval method with parametric optimization techniques.

Data‐driven modeling from noisy measurements

AbstractThe scope of this contribution is to present some recent results on how interpolation‐based data‐driven methods such as The Loewner framework [1] The AAA algorithm [2] can handle noisy data sets. More precisely, it will be assumed that the input‐output measurements used in these methods, i.e., transfer function evaluations, are corrupted by additive Gaussian noise.The notion of “sensitivity to noise” is introduced and it is used to understand how the location of measurement points affects the “quality” of reduced order models. For example, models that have poles with high sensitivity are hence deemed prohibited since even small perturbations could cause an unwanted behavior (such as instability). Moreover, we show how different data splitting techniques can influence the sensitivity values. This is a crucial step in the Loewner framework; we present some illustrative examples that include the effects of splitting the data in the “wrong” or in the “right” way.Finally, some perspectives for the future: we would like to employ statistics and machine learning techniques in order to avoid “overfitting”. More precisely, it is said that a model that has learned the noise instead of the true signal is considered an “overfit” because it fits the given noisy dataset but has a poor fit with other new datasets. We present some possible ways to avoid “overfitting” for the methods under consideration.

Optimal Design of Microlens Aperture Size for Focused Plenoptic Camera

The aperture size of microlens is a key parameter of a plenoptic camera, which strongly influence the performance of the camera. Generally, the size of microlens aperture is submillimeter, which will introduce obvious diffraction effect with large f-number. Besides, optical distortions of plenoptic camera also bring degradation effect in raw plenoptic image. In this letter, based on wave optics, a more accurate imaging model with diffraction effect and optical distortion for focused plenoptic camera is proposed. The modulation transfer function (MTF) evaluation suggests that the proposed model is more close to the real one when compared to the previous models. Additionally, the raw images under different microlens aperture sizes are synthesized. Finally, a relatively optimal size of microlens aperture is obtained according the results of depth estimation.

WITHDRAWN: Practical methods for characterizing the optical performance of digital camera-based imaging systems: image processing application using ImageJ

Abstract In this paper, practical and simple methods for characterizing the optical performance of a digital CCD camera equipped with a zoom lens using test targets projected by a Newtonian collimator coupled to an integrating sphere and a halogen light source are presented. The presented methods include the evaluation of the CCD camera system modulation transfer function (MTF), uniformity, dynamic range, linearity and signal-to-noise ratio (S/N) properties in the visible region of the spectrum. Through out this work image processing for the recorded target images is performed using ImageJ. In addition, the paper presents a comparison between MTF measurements collected with a 1951-USAF resolution test target and a slanted edge test target. Finally, simple mathematical expressions for the measured optical system performance properties are provided. The presented optical system characterization methods can provide researchers with the needed data when a CCD or CMOS digital camera is integrated with a lens system.

Approximability models and optimal system identification

This article considers the problem of optimally recovering stable linear time-invariant systems observed via linear measurements made on their transfer functions. A common modeling assumption is replaced here by the related assumption that the transfer functions belong to a model set described by approximation capabilities. Capitalizing on recent optimal recovery results relative to such approximability models, we construct some optimal algorithms and characterize the optimal performance for the identification and evaluation of transfer functions in the framework of the Hardy Hilbert space and of the disk algebra. In particular, we determine explicitly the optimal recovery performance for frequency measurements taken at equispaced points on an inner circle or on the torus.

Practical Methods for Characterizing the Optical Performance of Digital Camera-Based Imaging Systems

In this paper, practical and simple methods for characterizing the optical performance of a digital CCD camera equipped with a zoom lens using test targets projected by a Newtonian collimator coupled to an integrating sphere and a halogen light source are presented. The presented methods include the evaluation of the CCD camera system modulation transfer function (MTF), uniformity, dynamic range, linearity, and signal-to-noise ratio (S/N) properties in the visible region of the spectrum. Through out this work image processing for the recorded target images is performed using ImageJ. In addition, the paper presents a comparison between MTF measurements collected with a 1951-USAF resolution test target and a slanted edge test target. Finally, simple mathematical expressions for the measured optical system performance properties are provided. The presented optical system characterization methods can provide researchers with the needed data when a CCD or CMOS digital camera is integrated with a lens system.

Kramers-Kronig relations for magnetoinductive waves

Kramers-Kronig relations for propagating modes are a fundamental property of many but not all structures supporting wave propagation. While Kramers-Kronig relations for a transfer function of a causal system are always satisfied, it was discovered in the past that Kramers-Kronig relations for individual modes of a system may fail, e.g., in leaky structures. Our aim in this paper is to scrutinize whether magnetoinductive waves propagating in discrete metamaterial structures by virtue of interelement coupling satisfy Kramers-Kronig relations. Starting with the dispersion relations of magnetoinductive waves in the nearest-neighbor approximation we investigated the real and imaginary parts of two complex functions: the propagation coefficient and the transfer function. In order to show that the real and imaginary parts of these functions are related to each other by the Kramers-Kronig relations we had to modify the functions by deducting from them the values of the functions at infinite frequencies. It was shown that these modified functions and their Kramers-Kronig pairs perfectly coincided. The much more complicated case of magnetoinductive wave propagation with long-range coupling assumed was also investigated. The mode structure was derived for interactions up to the third neighbor. It was shown that the Kramers-Kronig relations are not applicable to the individual modes, but are valid for the transfer functions of the waveguide after solving the excitation problem and taking all the modes into account. Our method can be applied to practically relevant cases enabling rapid evaluation of transfer functions, e.g., in metamaterials used for wireless power transfer.

Contrast transfer function of de-noising algorithms.

This paper presents a comprehensive study on the contrast transfer function of de-noising algorithms. In order to cover a broad variety of methods, 45 de-noising algorithms are chosen considering their recognized efficiency in the different application domains of image processing. Advanced methods are targeted: wavelet transform-based algorithms with Daubechies, symlets, curvelets, contourlets, patch-based methods such as BM3D, NL-means algorithms and deep learning approaches; in addition, classical spatial filtering methods are considered, such as Wiener, median, Gauss filtering, and adaptive filtering approaches such as anisotropic diffusion and synthetic aperture radar filtering. The contrast transfer function is provided for each algorithm. Ranking of the set of de-noising algorithms is established according to proposed metrics. The paper provides practical methodology and novel results dedicated to the evaluation of the contrast transfer function of de-noising approaches from literature.

Circuit-Parameter-Based Audiosusceptibility Model for Series Resonant Converter

Models that accurately predict the output voltage ripple magnitude are essential for applications with stringent performance target for it. Impact of the dc input ripple on the output ripple for a frequency-controlled series resonant converter (SRC) using a discrete-domain exact discretization modeling method is analyzed in this paper. A novel discrete state-space model along with a small-signal model for the SRC considering three state variables is presented. The audiosusceptibility (AS) transfer function that relates the input-to-output ripple is derived from the small-signal model. Analysis of the AS transfer function indicates a resonance peak and an expression is derived connecting the AS resonance frequency for the input ripple based on the SRC component values. Further analysis is done to show that a set of values for the SRC parameter exists, which forms a design space, for which the normalized gain offered by the SRC for the input ripple is less than unity at any input ripple frequency. A test setup to introduce the variable frequency ripple at the input of the SRC for the experimental evaluation of the AS transfer function is developed. Influence of stray parameters on the AS gain, AS resonance frequency, and on the SRC tank resonance frequency is evaluated. An SRC is designed at a power level of 10 kW. The analysis using the derived analytical model, simulations, and experimental results are found to be closely matching.