Precise segmentation of cardiac substructures in magnetic resonance imaging is pivotal for diagnosis and treatment planning but remains impeded by anatomical scale heterogeneity and the scarcity of high-quality pixel-level annotations. Existing deep...
The rapidly aging global population is placing immense pressure on healthcare systems, which are struggling to meet the needs of older adults. Information and communication technologies (ICTs) are considered a key driver in supporting the development...
Drawing on the emerging scarcity, abundance, and sufficiency (SAS) framework, this study explores how various consumer behaviors with potential environmental impacts relate to subjective evaluations of psychological resources such as economic resourc...
This study introduces a novel fusion deep learning framework that integrates a convolutional neural network (CNN), a bidirectional gated recurrent unit (BiGRU), and a self-attention (SA) mechanism to address the shortcomings of conventional linear mo...
Accurate water body segmentation in aerial imagery is a fundamental component of intelligent systems for flood monitoring, urban planning, and environmental management. However, the presence of shadows and surface variations often leads to significan...
The increasing connectivity of Internet of Things (IoT)-oriented environments has made them more vulnerable to cyberattacks, requiring intrusion-detection systems (IDSs) to ensure their secure and reliable operation. The feature selection (FS) proces...
Light field angular super-resolution (LFASR) aims to reconstruct densely sampled views from sparse inputs by exploiting spatial–angular correlations, thereby producing rich spatial–angular representations and enabling applications such as...
Mesoscale eddies play a critical role in sea navigation and route planning, yet traditional prediction methods have often overlooked their spatial relationships, relying on indirect approaches to capture their distribution across extensive maps. To a...
Precise short-term forecasting of wind power generation is indispensable for ensuring the security and economic efficiency of power grid operations. Nevertheless, the inherent non-stationarity and stochastic nature of wind power series present signif...
In this study, a hybrid heading control framework for unmanned surface vehicles (USVs) is proposed, combining variable domain fuzzy Proportional–Integral–Derivative (VUF-PID) with an improved algorithmic Beetle Antennae Search–Parti...
21 September 2022
Background: Somatic acupoint stimulation (SAS) has been frequently utilised as a promising intervention for individual cancer-related symptom management, such as fatigue, sleep disturbance and depression. However, research evidence regarding the role...
Software-defined networking (SDN) is a transformative approach for managing modern network architectures, particularly in Internet-of-Things (IoT) applications. However, ensuring the optimal SDN performance and security often needs a robust sensitivi...
Salicylideneaniline (SA) sorbed in cation-exchanged M-ZSM-5 (M = H+, Li+, Na+, K+, Rb+, Cs+ and Zn2+) zeolites was studied by spectroscopic techniques assisted by quantum-chemical calculations. The nature of extra-framework cations present in the zeo...
A Machine Learning (ML)-based surrogate modeling framework is presented for mapping structure–property relationships in architected Ti6Al4V cylindrical TPMS metamaterials subjected to quasi-static compression. A Python–nTop pipeline autom...
In recent years, the involvement of synthetic strongly labeled data, weakly labeled data, and unlabeled data has drawn much research attention in semi-supervised acoustic event detection (SAED). The classic self-training method carries out prediction...
16 March 2021
Situation awareness (SA) of pilots’ unsafe behavior can ensure safety onboard. Thus, the cognitive mechanism that controls the SA leading to unsafe behavior must be articulated. This study employs the SA model and theory of planned behavior (TPB) to...
Virtual power plants (VPPs) integrate distributed energy sources and demand-side resources, but their efficient intelligent resource decision-making faces challenges such as high-dimensional constraints, output volatility of renewable energy, and ins...
In order to meet the requirements of high-tech enterprises for high power quality, high-quality operation and maintenance (O&M) in smart distribution networks (SDN) is becoming increasingly important. As a significant element in enhancing the hig...
Sustainable agriculture (SA) has emerged as an alternative to feeding an increasing global population. Several frameworks have been used in SA research. This study proposes understanding SA under five components: environment, economy, society, resili...
Dimensionality Reduction (DR) models are of significance to extract low-dimensional features for Hyperspectral Images (HSIs) data analysis where there exist lots of noisy and redundant spectral features. Among many DR techniques, the Graph-Embedding...
The use of unmanned aerial aircrafts (UAVs) is governed by strict regulatory frameworks that prioritize safety. To guarantee safety, it is necessary to acquire and maintain situational awareness (SA) throughout the operation. Existing Canadian regula...
Background/Objectives: Secondary victimization (SV) following sexual assault (SA) is known to compound negative health outcomes for survivors seeking help within formal systems, such as healthcare. While there have been advances in preventing SV and...
Given the increasing momentum globally towards sustainable transportation, the remanufacturing of used electric vehicle lithium-ion batteries (EV LIBs) emerges as a critical opportunity to promote the principles of the circular economy. Existing rese...
As the most direct indicator of drought, the dynamic assessment and prediction of actual evapotranspiration (AET) is crucial to regional water resources management. This research aims to develop a framework for the regional AET evaluation and predict...
Background: In safety-critical environments, human error is a leading cause of accidents, with the loss of situation awareness (SA) being a key contributing factor. Accurate SA assessment is essential for minimizing such risks and ensuring operationa...
The arbitrary placement of sensors in concrete structures measures a considerable amount of unnecessary data. Optimal sensor placement methods are used to provide informative data with the least cost and maximum efficiency. In this study, a robust op...
IoT-integrated supply chains play an important role in managing the movement of products and distribution, which relies on the processing of real-time data gathered using sensors and IoT-connected vehicles to make informed decisions that reduce logis...
For indoor multi-task planning problems of small unmanned aerial vehicles (UAVs) with different abilities, task assignment and path planning play a crucial role. The multi-dimensional requirements of reconnaissance tasks bring great difficulties to t...
Multimodal sentiment analysis (MSA) has emerged as a prominent research frontier, enabling a comprehensive understanding of complex human emotions through the synergistic integration of heterogeneous multimodal signals. However, most existing approac...
Currently, practically no modeling study is expected to be carried out without some form of Sensitivity Analysis (SA). At the same time, there is a large number of various methods and it is not always easy for practitioners to choose one. The aim of...
Aerial situational awareness (SA) faces significant challenges due to inherent complexity involving large-scale dynamic entities and intricate spatio-temporal relationships. While deep learning advances SA for specific data modalities (static or time...
Electromagnetic imaging of anisotropic objects is investigated using a deep learning-based framework combined with a Self-Attention (SA) mechanism. In this work, anisotropic scatterers are excited using both TM (Transverse Magnetic)- and TE (Transver...
Adaptive Large Neighborhood Search (ALNS) represents a versatile and highly efficient optimization methodology that has demonstrated significant effectiveness in practical applications. This study introduces an enhanced ALNS approach integrated with...
Land use significantly influences mobility dynamics, affecting both travel behavior and mode choice. Traditional indicators such as the Floor Area Ratio, Land-Use Mix Index, and Built-up Area Ratio are widely used to describe settlement patterns; yet...
Background/Objectives: Artificial intelligence-based software as a medical device (AI-SaMD) refers to AI-powered software used for medical purposes without being embedded in physical devices. Despite increasing approvals over the past decade, researc...
Trajectory prediction is a key component in the development of applications such as mixed urban traffic management and public safety. Traditional models have struggled with the complexity of modeling dynamic crowd interactions, the intricacies of spa...
On the basis of a previously developed elliptic blending turbulence model (SST–k–ω–φ–α model), a scale-adaptive simulation (SAS) model is developed by following Menter and Egorov’s SAS concept. An SAS sou...
A new satellite-based experiment in the field of gravitation, SaToR-G, is presented. It aims to compare the predictions of different theories of gravitation in the limit of weak-field and slow-motion. The ultimate goal of SaToR-G is searching for pos...
Processes for evaluating software architecture (SA) help to investigate problems and potential risks in SA. It is derived from many studies that proposed a plethora of systematic SA evaluation methods, while industrial practitioners currently refrain...
This study aims to investigate how sustainable innovation (SI) influences the relationship between internal audit effectiveness (IAE) and sustainability auditing (SA) practices in Libya’s public sector, providing valuable insights into its impl...
This study proposes a method for designing spatial light modulator (SLM) projection phases in digital lasers using a simulated annealing (SA) approach combined with an initialized pre-designed phase to generate structured laser beams. SLM projection...
Unmanned aerial vehicles (UAVs), equipped with a variety of sensors, are being used to provide actionable information to augment first responders’ situational awareness in disaster areas for urban search and rescue (SaR) operations. However, ex...
Semantic segmentation assigns a semantic label to every pixel in an image, which is a fundamental task in computer vision with applications such as autonomous driving and medical imaging. Existing segmentation methods, whether CNN-based or transforme...
The conceptual framework for assessing the situational awareness (SA) of drivers consists of three hierarchical levels: perception of the elements of the environment, comprehension of the elements, and decision-making in the near future. A common cha...
Rapid functional soft tissue restoration has shown considerable promise as a framework for stability and coordination in the human body. Inspired by the anisotropic arrangement of structures with soft and hard phases in biological tissues, such as te...
Water limitations in the Brazilian semi-arid region require saline water utilization. Hydroponic cultivation combined with salicylic acid (SA) elicitation represents a strategy to manage salt stress in cherry tomatoes. This study evaluated the effect...
Image segmentation is extensively used in remote sensing spectral image processing. Most of the existing region merging methods assess the heterogeneity or homogeneity using global or pre-defined parameters, which lack the flexibility to further impr...
In this paper, we present a sustainable approach for the creation of superhydrophobic (SP) coating on a stainless-steel substrate based on a biological metal–organic framework (MOF). The MOF was synthesized using aspartic acid as a linker and c...
This research examines the proposition that enhancing sustainable innovation can be particularly effective when the focus is on strategy, machine learning, and digitalization. The study specifically targets the complex interactions among strategic al...
Background: Self-amplifying mRNA (saRNA) holds promising application prospects. However, due to the inclusion of a replicase sequence, its extended length leads to premature termination during in vitro transcription (IVT), resulting in poor product i...
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