The development of regression models for composite distributions has received insufficient attention in the literature. The purpose of this research is to provide maximum likelihood (ML) and approximate Bayesian computation (ABC) estimators for the p...
Mechanical ventilation is required for many patients who cannot breathe normally as a result of lung disease and other factors that result in reduced lung function. In this study, we investigated the effects of mechanical ventilation and normal breat...
Memristive logic-in-memory circuits can provide energy- and cost-efficient computing, which is essential for artificial intelligence-based applications in the coming Internet-of-things era. Although memristive logic-in-memory circuits have been previ...
Purpose: To study the effect of the infusion of normal saline on hemodynamic changes in healthy volunteers using computational fluid dynamics (CFD) simulation. Methods: Eight healthy subjects participated and 16 carotid arteries were used for the CFD...
Background: Oxaliplatin-based hyperthermic intraperitoneal chemotherapy (HIPEC) using the original 30 min protocol has shown limited benefits in patients with peritoneal metastasis of colorectal cancer (PMCRC), likely due to the short duration, which...
Normalization as a layer within neural networks has over the years demonstrated its effectiveness in neural network optimization across a wide range of different tasks, with one of the most successful approaches being that of batch normalization. The...
Stochastic computing (SC) has the characteristics of low complexity and is expected to solve the bottleneck problem of conventional binary computing. Stochastic normalization units are widely used in stochastic decoding and stochastic signal detectio...
The equivalent source method (ESM) is a core algorithm in integrated radiation-propagation acoustic field modeling. However, in challenging marine environments, including deep-sea and polar regions, where sound speed profiles exhibit strong vertical...
Ultra-high dose rate radiotherapy known as Flash radiotherapy (FLASH-RT) offers tremendous opportunities to improve the therapeutic ratio of radiotherapy by sparing the normal tissue while maintaining similar tumoricidal efficacy. However, the underl...
Acoustic waves are essential tools for guiding underwater activities. For many years, numerical modeling of ocean acoustic propagation has been a major research focus in underwater acoustics. Normal mode theory, one of the earliest and most extensive...
Accurate classification of cancer images plays a crucial role in diagnosis and treatment planning. Deep learning (DL) models have shown promise in achieving high accuracy, but their performance can be influenced by variations in Hematoxylin and Eosin...
Modeling loss data is a crucial aspect of actuarial science. In the insurance industry, small claims occur frequently, while large claims are rare. Traditional heavy-tail distributions, such as Weibull, Log-Normal, and Inverse Gaussian distributions,...
The normal mode model is important in computational atmospheric acoustics. It is often used to compute the atmospheric acoustic field under a time-independent single-frequency sound source. Its solution consists of a set of discrete modes radiating i...
The development of deep neural networks, although demonstrating astounding capabilities, leads to more complex models, high energy consumption, and expensive hardware costs. While network quantization is a widely used method to address this problem,...
Prevalence of atrial fibrillation (AF) is high in heart failure patients supported by a continuous flow left ventricular assist device (CF-LVAD); however, the long term effects remain unclear. In this study, a computational model simulating effects o...
An efficient parallel computation using graphics processing units (GPUs) is developed for studying the electromagnetic (EM) backscattering characteristics from a large three-dimensional sea surface. A slope-deterministic composite scattering model (S...
During image segmentation tasks in computer vision, achieving high accuracy performance while requiring fewer computations and faster inference is a big challenge. This is especially important in medical imaging tasks but one metric is usually compro...
Objectives: The aim of this study was to assess the 5-year prognostic value of multidetector coronary computed tomography angiography (CCTA) in patients with normal coronary arteries. Background: Use of CCTA is increasing in patients with suspected c...
Nowadays, large-aperture optical components are increasingly used in high-power laser systems, remote-sensing satellites, and space-based astronomical telescopes. Fabricating these surfaces with submicron-scale shape accuracy and a nanoscale surface...
Spatiotemporal deep learning models, like Graph Neural Networks (GNNs), Transformers, and selective State Space Models (Mamba), have achieved impressive performance in electroencephalogram (EEG) decoding and affective computing. However, their genera...
Due to low activity in Internet of Things (IoT) applications, systems tend to leverage low power modes in order to reduce their power consumption. Normally-off computing thus arose, consisting in having turned off most part of a system’s power...
Background: Lung cancer remains a major cause of cancer-related mortality, and accurate analysis of pulmonary abnormalities on computed tomography (CT) images is important for supporting timely diagnosis. However, automated lung cancer classification...
MRI is an influential diagnostic imaging technology specifically worn to detect pathological changes in tissues with organs early. It is also a non-invasive imaging method. Medical image segmentation is a complex and challenging process due to the in...
Many population-based surveys have binary responses from a large number of individuals in each household within small areas. One example is the Nepal Living Standards Survey (NLSS II), in which health status binary data (good versus poor) for each in...
We use the HHL algorithm to retrieve a quantum state holding the algebraic normal form (ANF) of a Boolean function. Unlike the standard HHL applications, we do not describe the cipher as an exponentially big system of equations. Rather, we perform a...
The brain–computer interface (BCI) has many applications in various fields. In EEG-based research, an essential step is signal denoising. In this paper, a generative adversarial network (GAN)-based denoising method is proposed to denoise the mu...
As the core power element of a centrifugal fan, the impeller’s structural parameters are important factors affecting the aerodynamic performance of the fan. Therefore, to improve the aerodynamic performance of centrifugal fans, in this study, w...
Accurate evaluation of the standard normal cumulative distribution function is fundamental in many areas of mathematics, statistics, and applied computation, yet no closed-form expression in elementary functions exists. We present a simple analytic a...
Normal-flow, low-gradient aortic stenosis is one of the most deceptive presentations of aortic stenosis. It leaves clinicians uncertain whether they are facing true severe disease or a measurement artefact. This often reflects a discordant grading pa...
The aim of this study was to determine the factors that affect esthetic preference regarding the perceived facial attractiveness of young Korean female adults with a normal skeletal pattern using cone-beam computed tomography (CBCT). After reorientin...
This article proposes a normalization multi-layer perception (NMLP) geometry classifier to autonomously determine the optimal four femtocell evolved Node Bs (FeNBs), which can use time difference of arrival (TDOA) to measure the location of the macro...
In this paper, a novel soft computing technique is designed to analyze the mathematical model of the steady thin film flow of Johnson–Segalman fluid on the surface of an infinitely long vertical cylinder used in the drainage system by using art...
Single-molecule force spectroscopy experiments allow protein folding and unfolding to be explored using mechanical force. Probably the most informative technique for interpreting the results of these experiments at the structural level makes use of s...
This study presents a custom-built, portable multispectral imaging (MSI) system integrated with computer vision for sodium nitrite detection via the Griess reaction on paper-based substrates. The MSI system was used to investigate the absorption char...
The registration of point clouds in a three-dimensional space is an important task in many areas of computer vision, including robotics and autonomous driving. The purpose of registration is to find a rigid geometric transformation to align two point...
The Olympic Games are a sporting event and a catalyst for urban development in their host city. In this study, we utilized remote sensing and GIS techniques to examine the impact of the Olympic infrastructure on the surface temperature of urban areas...
This study presents a novel methodology for the detection and monitoring of changes in surface water bodies, with a particular emphasis on the near-eastern region of Antioquia, Colombia. The proposed approach integrates remote sensing and artificial...
Coronary computed tomography angiography (CCTA) is an effective imaging modality, increasingly accepted as a first-line test to diagnose coronary artery disease (CAD). The accurate segmentation of the coronary artery lumen on CCTA is important for th...
Background/Objectives: Normal pressure hydrocephalus (NPH) is a treatable cause of gait impairment and fall risk in older adults, yet it remains frequently underdiagnosed. This study aimed to validate an automated measurement of the callosal angle, a...
This paper presents a novel computational integral imaging reconstruction (CIIR) method using elemental image blending to eliminate the normalization process in CIIR. Normalization is commonly used in CIIR to address uneven overlapping artifacts. By...
Mass spectrometry-based proteomics have become a valued tool for conducting comprehensive analyses in amniotic fluid samples with pathologies. Our research interest is the finding and characterization of proteins related to normal vs. polyhydramnios...
3D least-squares matching is an algorithm that allows to measure subvoxel-precise displacements between two data sets of computed tomography voxel data. The determination of precise displacement vector fields is an important tool for deformation anal...
In this article, we derive a closed-form expression for computing the probabilities of p-dimensional rectangles by means of a multivariate skew-normal distribution. We use a stochastic representation of the multivariate skew-normal/independent distri...
Vector normalization is an important process in several algorithms. It is used in classical physical calculations, mathematical techniques, and machine learning, which has witnessed significant advancements in recent years. Normalization and regulari...
The assessment of liver size is usually performed using radiography in dogs. However, due to wide variations in patients’ sizes and body conformations, accurate diagnosis of hepatomegaly or microhepatia is difficult. Computed tomographic (CT) v...
Background: Distal tibiofibular syndesmotic injuries, often misdiagnosed, can lead to substantial morbidity. This study utilized postmortem computed tomography (PMCT) to define normal syndesmotic relationships in 131 subjects. Methods: Three paramete...
Objective: The objective was to evaluate the normal value of left ventricular myocardial strain using the computed tomography feature-tracking technique and to explore the correlation between myocardial strains and cardiac function parameters. Method...
Cloud computing has emerged as a fundamental pillar of modern technology, enabling large-scale data management, computational efficiency, and operational flexibility. However, critical challenges persist, particularly concerning security and performa...
Objective: Computed tomography (CT) is superior to plain radiography for evaluating ankle syndesmosis, but anatomical variations can affect the measurements. This study aimed to assess the radiologic parameters of the incisura fibularis and the facto...
Computer simulations using a dynamic model of the skeletal muscle bioenergetic system, involving the Pi-double-threshold mechanism of muscle fatigue, demonstrate that the training-induced increase in
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