Subsurface and groundwater flow characterization is of great importance for various environmental applications, such as the dispersion of contaminants and their remediation. For single-hole flowmeter measurements, key characteristics, such as wellbor...
Inefficiency of medical therapies used in order to cure patients with bacterial infections requires not only to actively look for new therapeutic strategies but also to carefully select antibiotics based on variety of parameters, including microbiolo...
In recent years, the most advanced pioneering techniques in the computing field have found application in assorted areas. Deep learning approaches, including artificial neural networks (ANNs), have become popular thanks to their ability to draw infer...
The growing use of deep neural networks in critical applications is making interpretability urgently to be solved. Local interpretation methods are the most prevalent and accepted approach for understanding and interpreting deep neural networks. How...
Outlier detection is a critical task in the intelligent operation and maintenance (O&M) of transportation equipment, as it helps ensure the safety and reliability of systems like high-speed trains, aircraft, and intelligent vehicles. Nearest neig...
Delirium in hospitalized patients is a worldwide problem, causing a burden on healthcare professionals and impacting patient prognosis. A machine learning interpretation method (ML interpretation method) presents the results of machine learning predi...
Technological improvements are crucial for achieving decarbonisation targets and addressing the impacts of climate change in the built environment via mitigation and adaptation measures. Data-driven methods for building performance prediction are par...
Steel fiber reinforced concrete (SFRC) exhibits excellent material enhancement and toughening properties. It is widely used in applications such as airport runways, highway pavements, and bridge deck overlays. In order to predict the compressive stre...
Fracture energy plays a pivotal role in ensuring the safe design of concrete structures. Currently, experimental testing remains the predominant methodology for exploring fracture energy in concrete. Nevertheless, this approach is hindered by protrac...
To address the technical challenge of real-time interpretation of sandstone reservoir porosity during drilling, a data-driven approach is employed by integrating logging data with machine learning algorithms to deeply mine existing logging data and p...
As the development of most domestic and international oilfields progresses, many fields have entered a mature phase characterized by high water cut and high recovery, with water cut levels often exceeding 90%. Carbon/oxygen ratio logging has proven t...
Coal mine goaf detection remains confronted with the lack of fast, effective and low-cost exploration means, especially for the accurate prediction of mining threats primarily caused by hydraulic infiltration. The rapid popularization of passive elec...
Many infectious diseases are transmitted via the air and are, therefore, particularly difficult to combat. These infections include various invasive mycoses caused by molds. The usual route of infection is the inhalation of conidia. In hospitals, inf...
Objects that possess mass (e.g., automobiles, manufactured items, etc.) translationally accelerate in direct proportion to the force applied scaled by the object’s mass in accordance with Newton’s Law, while the rotational companion is Eu...
Ground-penetrating radar processing and interpretation methods have been developed over time that usually follow a certain standard pathway, which leads from obtaining the raw reflection data to the production of amplitude slice-maps for three-dimens...
The current paper attempts to describe the methodology guiding researchers on how to use a combination of machine learning methods and cognitive-behavioral approaches to realize the automatic prediction of a learner’s preferences for the variou...
The paper completes the multi-parametrical fitting methods, which are based on metrics induced by the non-Euclidean Lq-norms, by deriving the errors of the optimal parameter values. This was achieved using the geometric representation of the residual...
The interpretation of well-testing data is a key means of decision-making support for oil and gas field development. However, conventional processing methods have many problems, such as the stochastic nature of the data, feature redundancies, the ran...
Studying paleoclimatic conditions across geological epochs is essential for understanding climate evolution and its influence on Earth’s biosphere. Leaf macrofossils serve as a crucial data source for reconstructing ancient climates due to thei...
The depositional environment of the Machów Formation in the central part of the Carpathian Foredeep is still relatively poorly understood. Although lithological variability, facies diversity, and depositional history have been described in man...
Background: Fosfomycin (FOS) is an older antimicrobial agent newly rediscovered as a possible treatment for infections with limited therapeutic options (e.g., Gram-negative bacteria with difficult-to-treat resistance, DTR), especially in intravenous...
Pre-crash injury risk (IR) assessment is essential for guiding efforts toward active vehicle safety. This work aims to conduct crash severity assessment using pre-crash information and establish the intrinsic mechanism of IR with proper interpretatio...
After obtaining the value of shear wave velocity (VS) from the bender elements test (BET), the shear modulus of soils at small strains (Gmax) can be estimated. Shear wave velocity is an important parameter in the design of geo-structures subjected to...
The heart of the differences between an Orthodox understanding and use of Scripture, and what has prevailed in most non-Orthodox scholarly circles since the time of Spinoza, is not primarily anything to do with methodologies, or techniques as such, b...
Little data exist on the levels of antimicrobial resistance from bacteria isolated from British sheep and beef cattle. The aim of this study was to investigate antimicrobial resistance patterns on sheep and beef farms in England and Wales using multi...
Introduction and objective: Rapid and efficient interpretation of echocardiographic findings is critical in clinical decision-making. This study aimed to design and validate a new graphical method, called CARDIOBOX, to represent echocardiographic fin...
This article provides an in-depth review of the concepts of interpretability and explainability in machine learning, which are two essential pillars for developing transparent, responsible, and trustworthy artificial intelligence (AI) systems. As alg...
Recently, in line with the increased attention paid to cultural tourism in general and to religious tourism in particular, researchers and practitioners have become increasingly interested in the analysis of various aspects related to cultural herita...
Salt interpretation using seismic data is essential for structural interpretation and oil and gas exploration. Although deep learning has made great progress in automatic salt image segmentation, it is often difficult to obtain satisfactory results i...
This paper discusses the principal sources of uncertainty in the execution and interpretation of Bender Element (BE) tests conducted on reconstituted sand samples. Based on the experience accumulated by the Geotechnical Laboratory of the University o...
In this study, series networks (AlexNet and VGG-19) and directed acyclic graph (DAG) networks (ResNet-18, ResNet-50, and ResNet-101) with transfer learning were employed to identify and classify 13 classes of apples from 7439 images. Two training dat...
Ultra-low permeability argillaceous sandstone reservoirs have become a significant focus for exploration and development. Saturation is a crucial parameter in evaluating such reservoirs. Due to the low porosity, low permeability, complex pore structu...
As global economic integration deepens, import and export trade plays an increasingly vital role in China’s economy. To enhance regulatory efficiency and achieve scientific, transparent credit supervision, this study proposes a trade credit ris...
This study presents the development of a discrete algorithm for interpreting ground-penetrating radar (GPR) data in vertically inhomogeneous media for the diagnostics of road structures. Experimental data were obtained using an OKO-2 GPR system, foll...
Non-destructive concrete strength prediction faces limitations in validation scope, methodological comparison, and interpretability that constrain deployment in safety-critical construction applications. This study presents a machine learning framewo...
Coal and gas outbursts pose significant threats to underground personnel, making the development of accurate prediction models crucial for reducing casualties. By addressing the challenges of highly nonlinear relationships among predictive parameters...
Although, existing methods have been successful in predicting phage (or bacteriophage) virion proteins (PVPs) using various types of protein features and complex classifiers, such as support vector machine and naïve Bayes, these two methods do n...
In order to study the deep mechanism of integrated power–gas system (IPGS) coupling, the influencing factors of IPGS coupling are investigated using the Decision Making Test and Evaluation Test–Interpretative Structural Modeling–Met...
Today, planning an urban–rural interface requires redefining the planner’s role and toolbox. Global challenges such as food security, climate change and population growth have become urgent issues to be addressed, especially for the implications in l...
Great progress has been made in the integration of Unmanned Aerial Vehicle (UAV) magnetic measurement systems, but the interpretation of UAV magnetic data is facing serious challenges. This paper presents a complete workflow for the detection of the...
Examples from the Polish clastic and carbonate reservoirs from the Central Polish Anticlinorium, Carpathians and Carpathian Foredeep are presented to illustrate possibilities of using well logging to geothermal resources recognition and characterizat...
Lifetime’s “Married at First Sight” (MAFS) aired its seventeenth season in 2024, averaging 2.58 million viewers per weekly episode. In this paper, we ask, how does MAFS reflect and intervene in contemporary marriage politics, partic...
SARS-CoV-2 is a novel virus that has been affecting the global population by spreading rapidly and causing severe complications, which require prompt and elaborate emergency treatment. Automatic tools to diagnose COVID-19 could potentially be an impo...
Machine-learning algorithms have made significant strides, achieving high accuracy in many applications. However, traditional models often need large datasets, as they typically peel substantial portions of the data in each iteration, complicating th...
Synthetic data, artificially generated by computer programs, has become more widely used in the financial domain to mitigate privacy concerns. Variational Autoencoder (VAE) is one of the most popular deep-learning models for generating synthetic data...
This paper develops a two-scale asymptotic homogenization method for periodic composite Kirchhoff plates. In this method, a three-dimensional (3D) periodic plate problem is simplified as a Kirchhoff plate problem, which is governed by a fourth-order...
Gains and losses of large segments of genomic DNA, known as copy number variants (CNVs) gained considerable interest in clinical diagnostics lately, as particular forms may lead to inherited genetic diseases. In recent decades, researchers developed...
Deep learning architectures like ResNet and Inception have produced accurate predictions for classifying benign and malignant tumors in the healthcare domain. This enables healthcare institutions to make data-driven decisions and potentially enable e...
Chronic pain leads to not only physical discomfort but also psychological challenges, such as depression and anxiety, which contribute to a substantial healthcare burden. Pain detection and assessment remains a challenge due to its subjective nature....
Science, technology, engineering, and mathematics (STEM) education has become a new trend in international education curriculum reform. This study analyzed the teaching of seven subjects and performance indicators by collecting data from literature o...
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