Structural hyperparameter selection (HPS) in neural network (NN) regression faces two critical, computationally expensive barriers: the mandatory splitting of datasets for validation, which significantly impairs sample efficiency, and the inability o...
Synthetic aperture radar (SAR) image change detection is one of the most important applications in remote sensing. Before performing change detection, the original SAR image is often cropped to extract the region of interest (ROI). However, the size...
The inevitable frequency errors owing to the frequency mismatch of a transmitter and receiver oscillators could seriously deteriorate the imaging performance in distributed inverse synthetic aperture radar (ISAR) system. In this paper, for this issue...
For clinical study and diagnosis, compression of Electro Cardio Gram (ECG) signal is a fundamental step for processing. However, the compression and reconstruction introduce errors in the signal. Therefore, error minimization is crucial before using...
Feature selection has been widely used in machine learning and data mining since it can alleviate the burden of the so-called curse of dimensionality of high-dimensional data. However, in previous works, researchers have designed feature selection me...
An intelligent vehicle must face a wide variety of situations ranging from safe and comfortable to more aggressive ones. Smooth maneuvers are adequately addressed by means of linear control, whereas more aggressive maneuvers are tackled by nonlinear...
This paper presents a method for lossless compression of images with fast decoding time and the option to select encoder parameters for individual image characteristics to increase compression efficiency. The data modeling stage was based on linear a...
The Direction of Arrival (DOA) estimations of systematic errors are caused by diffraction distortions of the measured spatial structure of a electromagnetic field. These distortions result from scattering of incident waves on the antenna system and n...
The phase angle master curve of the PU mixture is a new research field that is urgently needed to characterize the viscoelastic of the PU mixture under different conditions. In this paper, five master curve models, five shift factor equations, and fo...
The PU mixture considered here is a new kind of pavement material with excellent road performance, which lacks study into its dynamic mechanical and viscoelastic properties. In this study, the dynamic modulus of the polyurethane (PU) mixture was fitt...
A popular risk measure, conditional value-at-risk (CVaR), is called expected shortfall (ES) in financial applications. The research presented involved developing algorithms for the implementation of linear regression for estimating CVaR as a function...
In this paper, a nonlinear system is interpreted as an operator
In this paper, we consider a new design problem of optimizing a linear transceiver for correlated multiple-input multiple-output (MIMO) interference channels in the presence of channel state information (CSI) errors, which is a more realistic and pra...
This paper integrates
Bounding the best achievable error probability for binary classification problems is relevant to many applications including machine learning, signal processing, and information theory. Many bounds on the Bayes binary classification error rate depend...
A method for the approximate merging of disk Wang–Ball (DWB) curves based on the modified snake optimizer (BEESO) is proposed in this paper to address the problem of difficulties in the merging of DWB curves. By extending the approximate mergin...
Installing multi-camera systems and inertial measurement units (IMUs) in self-driving cars, micro aerial vehicles, and robots is becoming increasingly common. An IMU provides the vertical direction, allowing coordinate frames to be aligned in a commo...
The present paper treats a black-box estimation of the three independent parameters of a reciprocal lossy two-port network whose terminals are supposed to be accessible to an impedance measurement device. The discussed estimation method is based on t...
Inverse kinematics problems (IKP) are ubiquitous in robotics for improved robot control in widespread applications. However, the high non-linearity, complexity, and equation coupling of a general six-axis robotic manipulator pose substantial challeng...
The problem of parametric estimation in single-phase transformers is addressed in this research from the point of view of metaheuristic optimization. The parameters of interest are the series resistance and reactance as well as the magnetization resi...
In modern steel structures such as bridges and buildings, curved members are increasingly adopted. Current industry practices often approximate mildly curved surfaces with flat plates within tolerances, but optimizing this substitution to minimize fi...
This paper describes methods for optimal filtering of random signals that involve large matrices. We developed a procedure that allows us to significantly decrease the computational load associated with numerically implementing the associated filter...
12 October 2021
Air displacement plethysmography (ADP) is fast, accurate, and reliable. Nevertheless, in about 3% of the cases, standard ADP tests provide rogue results. To spot these outliers and improve precision, repeated trials protocols have been devised, but f...
In this research paper, a combinatorial optimization approach is proposed for parameter estimation in single-phase transformers considering voltage and current measurements at the transformer terminals. This problem is represented through a nonlinear...
Solar power forecasting is important for energy management and grid stability, yet many deep learning studies use a large set of meteorological and time-based variables because of the belief that more inputs improve model performance. In practice, a...
In the realm of 3D curve reconstruction, Non-Uniform Rational B-Splines (NURBSs) offer a versatile mathematical tool due to their ability to precisely represent complex geometries. However, achieving high fitting accuracy in stereo-based applications...
In recent years, image fusion has been a research hotspot. However, it is still a big challenge to balance the problems of noiseless image fusion and noisy image fusion. In order to improve the weak performance and low robustness of existing image fu...
Evaluating the performance of Bayesian classification in a high-dimensional random tensor is a fundamental problem, usually difficult and under-studied. In this work, we consider two Signal to Noise Ratio (SNR)-based binary classification problems of...
Global Ecosystem Dynamics Investigation (GEDI) is a relatively new technology for global forest research, acquiring LiDAR measurements of vertical vegetation structure across Earth’s tropical, sub-tropical, and temperate forests. Previous GEDI...
Background: Quantitative gait analysis is essential in both clinical and research contexts; however, traditional marker-based motion capture systems are costly and burdensome. Advances in three-dimensional markerless motion capture (3D-MMC) offer mor...
The wide spread usage of wearable sensors such as in smart watches has provided continuous access to valuable user generated data such as human motion that could be used to identify an individual based on his/her motion patterns such as, gait. Severa...
This paper discusses a method for taking into account rounding errors when constructing a stopping criterion for the iterative process in gradient minimization methods. The main aim of this work was to develop methods for improving the quality of the...
In modular distributed architectures, the adoption of a communication method that is at the same time robust and has a low and predictable latency is of utmost importance in order to support the required system dynamics. The aim of this paper is to e...
Medication errors represent a concern for healthcare organizations due to their negative consequences. In the nursing context, these errors represent a threat to the quality of care and patient safety. Many factors have been identified as potential c...
In complex electromagnetic environments, spatial coupling uncertainties—position errors and timing jitter—increase false target information entropy, reducing strategy effectiveness and posing challenges for robust UAV swarm track deceptio...
Hybrid RANS-LES methods are supposed to provide major contributions to future turbulent flow simulations, in particular for reliable flow predictions under conditions where validation data are unavailable. However, existing hybrid RANS-LES methods su...
As wireless sensor networks have become more prevalent, data from sensors in daily life are constantly being recorded. Due to cost or energy consumption considerations, optimization-based approaches are proposed to reduce deployed sensors and yield r...
Background/Objectives: Medication errors are the most frequent and critical issues in healthcare settings, often leading to worsened clinical outcomes, increased treatment costs, extended hospital stays, and heightened mortality and morbidity rates....
Kalman filtering is a linear quadratic estimation (LQE) algorithm that uses a time series of observed data to produce estimations of unknown variables. The Kalman filter (KF) concept is widely used in applied mathematics and signal processing. In thi...
Lack of standardization related to compounded drug preparations, especially in the transition of care situations, threatens patient safety by facilitating medication error. This paper outlines progress to-date from the United States Pharmacopeia (USP...
As IoT (Internet of Things) devices are diversified in the fields of use (manufacturing, health, medical, energy, home, automobile, transportation, etc.), it is becoming important to analyze and process data sent and received from IoT devices connect...
This paper delves into precisely measuring liquid levels using a specific methodology with diverse real-world applications such as process optimization, quality control, fault detection and diagnosis, etc. It demonstrates the process of liquid level...
In this paper, a partial transmit sequence (PTS) technique with a side information (SI) blind detector based on minimized error accumulation for PAPR reduction in the coded underwater acoustic (UWA) orthogonal frequency division multiplexing (OFDM) c...
In this paper, we compare the effects of forecasting demand using individual (disaggregated) components versus first aggregating the components either fully or into several clusters. Demand streams are assumed to follow autoregressive moving average...
Circulating tumor DNA (ctDNA) is a promising biomarker, reflecting the presence of tumor cells. Sequencing-based detection of ctDNA at low tumor fractions is challenging due to the crude error rate of sequencing. To mitigate this challenge, we develo...
Among female breast cancer survivors, there is a high prevalence of lymphedema subsequent to axillary lymph node dissection and axillary radiation therapy. There are many methodologies available for the screening, diagnosis and follow-up of breast ca...
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The paper presents the results of the investigations on the direction-dependent accuracy of the point identification during contact probe measurements with a coordinate measuring machine (CMM). Considering the contact point identified by an orthogona...
Pulse wave velocity (PWV), a direct measure of arterial stiffness, is a promising biomarker of cardiovascular risk and a cardiovascular surrogate outcome. The resolution for detecting its smallest clinically significant change is dependent on the exp...
Researchers tackled the challenge of finding the right parameters for a transformer-equivalent circuit. They achieved this by minimizing the difference between actual measurements (currents, powers, secondary voltage) during a transformer load test a...
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