Multimodal medical image registration has an important role in monitoring tumor growth, radiotherapy, and disease diagnosis. Deep-learning-based methods have made great progress in the past few years. However, its success depends on large training da...
Metamaterials and their related research have had a profound impact on many fields, including optics, but designing metamaterial structures on demand is still a challenging task. In recent years, deep learning has been widely used to guide the design...
Reverse logistics (RL) plays a crucial role in promoting circularity and sustainability in supply chains, particularly in the face of increasing waste generation and growing environmental demands. In recent years, machine learning (ML) has emerged as...
Complex engineering optimization problems often exhibit high-dimensional, multi-constraint, and nonlinear characteristics. Traditional deterministic optimization methods rely on gradient information and have limited optimization ranges, making it dif...
With the widespread adoption of 3D scanners, reverse engineering methods for obtaining CAD drawings from physical objects have become increasingly utilized. When converting point data obtained from a 3D scanner into a mesh structure, a smoothing proc...
Reverse osmosis membranes have been predominantly made from aromatic polyamide composite thin-films, although significant research efforts have been dedicated to discovering new materials and synthesis technologies to enhance the water–salt selectivi...
As a distributed machine learning paradigm, federated learning (FL) enables participating clients to share only model gradients instead of local data and achieves the secure sharing of private data. However, the lack of clients’ willingness to...
Machine learning algorithms for reverse image search (a subset of open source intelligence or OSINT) provide a free, useful tool for determining the content of an image, where and when it was captured, and, in some cases, whether it has been digitall...
Reverse vaccinology (RV) is a bioinformatics approach that can predict antigens with protective potential from the protein coding genomes of bacterial pathogens for subunit vaccine design. RV has become firmly established following the development of...
In recent years, the explosion of big data has presented unparalleled opportunities for the advancement of machine learning (ML). However, the vast size and sensitive nature of these datasets present significant challenges in terms of privacy and sec...
Reverse image search has been a vital and emerging research area of information retrieval. One of the primary research foci of information retrieval is to increase the space and computational efficiency by converting a large image database into an ef...
Federated learning (FL) can break the problem of data silos and allow multiple data owners to collaboratively train shared machine learning models without disclosing local data in mobile edge computing. However, how to incentivize these clients to ac...
The security of industrial control systems relies on the communication and data exchange capabilities provided by industrial control protocols, which can be complex, and may even use encryption. Reverse engineering these protocols has become an impor...
Classifying and segmenting skin cancer represent pivotal objectives for automated diagnostic systems that utilize dermoscopy images. However, these tasks present significant challenges due to the diverse shape variations of skin lesions and the inher...
Computational thinking (CT) is important for students because it is one of the 21st century’s skills. Reverse engineering pedagogy (REP) can improve students’ CT due to its ability to develop students’ cooperativity, algorithmic thi...
The fashion industry is facing increasing pressure to move toward sustainable development, especially with concern to cost and environmental sustainability. Innovative digital technologies are regarded as a promising solution for fashion companies to...
Aircraft maintenance scheduling is a critical task in air transportation and national defense security, characterized by complex multi-step procedures, strict precedence dependencies, and multi-resource constraints involving personnel skills and equi...
Reverse vaccinology (RV) is a computer-aided approach for vaccine development that identifies a subset of pathogen proteins as protective antigens (PAgs) or potential vaccine candidates. Machine learning (ML)-based RV is promising, but requires a dat...
Tuberculosis (TB) is the leading cause of death of any single infectious agent, having led to 1.4 million deaths in 2019 alone. Moreover, an estimated one-quarter of the global population is latently infected with Mycobacterium tuberculosis (MTB), pr...
The management of the abundant amount of used plastic bottle waste is a major concern nowadays, because it is a major contributor to landfills and overburdens waste processing facilities. Once disposed of, plastic can take centuries to break down, he...
Momentum and reversal effects are important phenomena in stock markets. In academia, relevant studies have been conducted for years. Researchers have attempted to analyze these phenomena using statistical methods and to give some plausible explanatio...
Despite the increasing application of machine learning and computational intelligence algorithms in medicine and physiotherapy, accurate classification and prognosis algorithms for postoperative patients in the rehabilitation phase are still lacking....
Reversal learning tasks are used to model flexible decision-making in laboratory animals, and exposure to drugs of abuse can cause long-term impairments in reversal learning. However, the long-term effects of alcohol on reversal learning have varied....
Cognitive flexibility refers to the ability to modify learned behavior in response to changes in the environment. In laboratory rodents, cognitive flexibility can be assessed in reversal learning, i.e., the change of contingencies, for example in T-m...
Background: Despite the importance of the deltoid to shoulder biomechanics, very few studies have quantified the three-dimensional shape, size, or quality of the deltoid muscle, and no studies have correlated these measurements to clinical outcomes a...
Cognitive flexibility is essential to modify our behavior in a non-stationary environment and is often explored by reversal learning tasks. The basal ganglia (BG) dopaminergic system, under a top-down control of the pre-frontal cortex, is known to be...
The rapid growth of electric vehicles (EVs) has created an urgent need for sustainable end-of-life battery management systems. This paper presents a novel AI-driven framework for designing resilient reverse logistics networks that optimize the collec...
Federated learning is a promising technique in cloud computing and edge computing environments, and designing a reasonable resource allocation scheme for federated learning is particularly important. In this paper, we propose an auction mechanism for...
Calcium sulfate scaling remains a major barrier to stable reverse osmosis (RO) operation. This study introduces an interpretable, stage-oriented framework that analyzes three complementary scaling endpoints rather than treating scaling as a single re...
Adverse early life experiences are associated with an enhanced risk for mental and physical health problems, including substance abuse. Despite clinical evidence, the mechanisms underlying these relationships are not fully understood. Maternal separa...
The reversed gender achievement gap in the Kingdom of Saudi Arabia (KSA) in favor of girls developed in a societal environment that still predominantly favors men. The finding illustrates how equity gaps at higher systemic levels may not translate se...
Steel pipes play a vital role in energy and industrial transportation systems, where undetected defects such as cracks and wall thinning may lead to severe safety hazards. Although ultrasonic guided waves enable long-range inspection, their defect im...
Human immunodeficiency virus (HIV) is one of the viruses that has co-evolved within human populations for a considerable time. With the evolution of new drug-resistant HIV strains, the necessity to discover novel drugs has become an issue of great co...
Reverse osmosis (RO) digital twins require predictive models whose accuracy remains credible as plant operating conditions change. We evaluated the readiness of predictive models for a full-scale, two-stage RO plant using operational spreadsheets and...
One concern in the yearly re-formulation of influenza vaccines is the time-consuming manufacturing of vaccine potency reagents, particularly for emergency responses. The continuous evaluation of modern techniques such as reversed-phase (RP) chromatog...
We present a supervised learning method to estimate two local descriptors of time-series dynamics, the mean-reversion rate
Knitting, a cornerstone of textile manufacturing, is uniquely challenging to automate, particularly in terms of converting fabric designs into precise, machine-readable instructions. This research bridges the gap between textile production and roboti...
This paper proposes the Quantum-behaved Loser Reverse-learning Differential Evolution (QLRDE) algorithm to address the inherent limitations of the standard Differential Evolution (DE) algorithm, including slow convergence speed and the premature stag...
Point-of-care ultrasound (POCUS), realized by recent developments in portable ultrasound imaging systems for prompt diagnosis and treatment, has become a major tool in accidents or emergencies. Concomitantly, the number of untrained/unskilled staff n...
In this paper, we present our work on developing a Smart Pricing Policies module specifically designed for individual users and Mobile Network Operators (MNOs). Our framework will operate in a multi-MNO blockchain radio access network (B-RAN) and is...
The abnormality in N6-methyladenosine (m6A) methylation is involved in the course of Alzheimer’s disease (AD), while the intervention of 27-Hydroxycholesterol (27-OHC) can affect the m6A methylation modification in the brain cortex. Disordered...
The load-penetration depth (P–h) curves of different metallic coating materials can be determined by nanoindentation experiments, and it is a challenge to obtain stress–strain response and elastoplastic properties directly using P–h...
In developed countries such as Spain, where the population is increasingly aging, retirement planning and longevity risk represent major societal challenges. In Spain, in particular, a significant proportion of household wealth is concentrated in rea...
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Chronic alcoholism has profound effects on the brain, including volume reductions in regions critical for eyeblink classical conditioning (EBCC). The current study challenged abstinent alcoholics using delay (n = 20) and trace (n = 17) discrimination...
Fused Deposition Modeling (FDM) components require accurate identification of printing parameters to ensure reliable quality assessment and support scalable reverse-engineering workflows. The objective of this study is to evaluate whether mechanical...
PDF has become a major attack vector for delivering malware and compromising systems and networks, due to its popularity and widespread usage across platforms. PDF provides a flexible file structure that facilitates the embedding of different types o...
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The family dog is a valid model for studying complex human functions and psychological disorders such as Attention-Deficit/Hyperactivity Disorder (ADHD). Based on prior human research indicating impairments in cognitive flexibility related to ADHD, t...
Sleep supports brain development and adaptability, yet its relationship with cognitive performance in farm animals remains unclear. This study examined the association between a behavioral indicator of rapid eye movement (REM) sleep, the REM sleep-li...
Q-compensated reverse time migration (Q-RTM) is a crucial technique in seismic imaging. However, stability is a prominent concern due to the exponential increase in high-frequency ambient noise during seismic wavefield propagation. The two primary st...
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