Lung and colon cancers are among the leading causes of human mortality and morbidity. Early diagnostic work up of these diseases include radiography, ultrasound, magnetic resonance imaging, and computed tomography. Certain blood tumor markers for car...
The “immersed boundary method (IBM)” is considered to be the most efficacious and versatile technique to solve flow problems associated with intricate geometries. The first part of this review examines recent advancements in IBM, essentia...
We extend a previously developed model for the Stark resonances of the water molecule. The method employs a partial-wave expansion of the single-particle orbitals using spherical harmonics. To find the resonance positions and decay rates, we use the...
Aiming at a critical gap in evaluating human-centered spatial quality during urban stock renewal, this study aimed to develop a quantitative methodology to evaluate emotional vitality in urban commercial complexes. Focusing on five representative Bei...
A model potential previously developed for the ammonia molecule is treated in a single-center partial-wave approximation in analogy with a self-consistent field method developed by Moccia. The latter was used in a number of collision studies. The mod...
After volume fracturing, shale reservoirs can be divided into nonlinear seepage areas controlled by micro- or nanoporous media and Darcy seepage areas controlled by complex fracture networks. In this paper, firstly, on the basis of calculating comple...
Cities are complex systems with socioeconomic activities exhibiting diverse spatial distributions, where selecting an appropriate observation scale is vital for understanding urban complexity. However, the traditional methods for this task are often...
This paper aims to study the difference of results in breakup state judgment, debris cloud and fragment characteristic parameter during hypervelocity impact (HVI) on large-scale complex spacecraft structures by various numerical simulation methods. W...
Modern retrieval systems tend to deteriorate because of their large output of useless and even misleading information, especially for complex search requests on a large scale. Complex information retrieval (IR) tasks requiring multi-hop reasoning nee...
The Conferences of the Middle European Cooperation in Statistical Physics (MECO) were created as an attempt to establish and maintain an exchange between scientists in the fields of statistical and condensed matter physics from Western and Eastern co...
Many studies have confirmed that the complexity of a time sequence is closely related to its predictability, but few studies have proposed methods to reduce the time sequence complexity, which is the key to improving its predictability. This study an...
In many complex systems observed in nature, properties such as scalability, adaptivity, or rapid information exchange are often accompanied by the presence of features that are scale-free, i.e., that have no characteristic scale. Following this obser...
Accurate segmentation of ship targets in high-resolution remote sensing images is crucial for maritime monitoring, traffic management and naval security. However, existing methods struggle to simultaneously address extreme scale variations in ships a...
The evaluation of rock porosity and the mercury injection capillary pressure (MICP) curve is fundamental for oil and gas exploration and production. Digital rock (DR) technology, incorporating 3D micro-CT imaging and numerical methods, has been widel...
Data augmentation (DA) is a widely used technique to improve generalization in Deep Learning. However, many existing mixing-based approaches apply uniform strategies or rely on computationally expensive saliency guidance. In this work, we propose Ada...
H. 265/HEVC still dominates the video encoding application market with its mature industrial ecosystem and excellent hardware support. However, its high computational complexity remains a major barrier to its wider application. To tackle this problem...
The accuracy of road damage detection models based on UAV remote sensing images is generally low, mainly due to the challenges posed by the complex background of road damage, diverse forms, and necessary computational requirements. To tackle the issu...
Slope units (SUs) are sub-watersheds bounded by ridge and valley lines. A slope unit reflects the physical relationship between landslides and geomorphological features and is especially useful for landslide sensitivity modeling. There have been sign...
In order to improve the uniformity of microwave heating, moving components are often added to the cavity. For higher uniformity or greater industrial processing capacity, samples often perform large-scale movements such as rotating and lifting motion...
For urban watersheds, the storm sewer network provides indispensable data for flood modeling but often needs to be simplified to balance the conflict between the large amount of data and current computing power. The sensitivity of a flood simulation...
Ship personnel detection is the core technology for building intelligent ship monitoring systems. It safeguards navigation safety and standardizes deck work management. Current human detection algorithms perform poorly in complex marine service envir...
In this paper, an improved antlion optimization algorithm (IALO) was proposed to search for promising solutions for optimal economic load dispatch (ELD) problems to minimize electrical generation fuel costs in power systems with thermal units and to...
Accurately perceiving changes in water level information is key to achieving the fine control of water and flooding; however, the existing technology cannot achieve water level recognition in complex and harsh environments, such as at night; in haze,...
This paper presents an iterative hybrid finite element boundary integral and physical optics (FEBI-PO) method for efficient electromagnetic scattering analysis of electrically large targets that contain locally complex structures. The key idea is to...
An innovative and efficient hybrid technique, which combines the Method of Moments (MoM) with Volume Meshed Shooting and Bouncing Ray (VSBR), is presented to analyze the scattering of metallic–dielectric mixed multi-scale structures in urban sc...
Accurate object detection is fundamental to computer vision, yet detecting small targets in complex backgrounds remains challenging due to feature loss and limited model efficiency. To address this, we propose LCW-YOLO, a lightweight detection framew...
Patterns of spatial heterogeneity in forests and other fire-prone ecosystems are increasingly recognized as critical for predicting fire behavior and subsequent fire effects. Given the difficulty in sampling continuous spatial patterns across scales,...
Whey protein pectin complexes can be applied to replace fat in food products, e.g., pudding and yogurt, contributing to creaminess while adding a source of protein and fiber. Production of these complexes is usually conducted on the laboratory scale...
The extension of sample entropy methodologies to multivariate signals has received considerable attention, with traditional univariate entropy methods, such as sample entropy (SampEn) and fuzzy entropy (FuzzyEn), introduced to measure the complexity...
Coral reef habitat structural complexity influences key ecological processes, ecosystem biodiversity, and resilience. Measuring structural complexity underwater is not trivial and researchers have been searching for accurate and cost-effective method...
To address the challenges of leaf–branch occlusion, fruit mutual occlusion, complex background interference, and scale variations in peach detection within complex orchard environments, this study proposes an improved YOLOv11n-based peach detec...
The health condition monitoring of rotating machinery can avoid the disastrous failure and guarantee the safe operation. The vibration-based fault diagnosis shows the most attractive character for fault diagnosis of rotating machinery (FDRM). Recentl...
In this paper, we primarily investigate the methodology for the hybrid complex projective synchronization (HCPS) scheme in non-identical complex fractional order chaotic systems via an active complex synchronization technique (ACST). Appropriate cont...
Compared to traditional real-valued neural networks, which process only amplitude information, complex-valued neural networks handle both amplitude and phase information, leading to superior performance in polarimetric synthetic aperture radar (PolSA...
To overcome the limitations of traditional methods in reverberant and noisy environments, a robust multi-scale fusion neural network with attention mask is designed to improve direction-of-arrival (DOA) estimation accuracy for acoustic sources. It co...
Structural analysis is a method for verifying equation-oriented models in the design of industrial systems. Existing structural analysis methods need flattening of the hierarchical models into an equation system for analysis. However, the large-scale...
Ship-radiated noise is one of the important signal types under the complex ocean background, which can well reflect physical properties of ships. As one of the valid measures to characterize the complexity of ship-radiated noise, permutation entropy...
Infrared small target detection, especially under low SCR conditions and complex backgrounds, is still a challenging research task. Considering the scale change caused by small targets rapidly moving, in this paper, a nonparametric regression-based m...
The use of convolutional neural networks (CNN) for crowd counting has made significant progress in recent years; however, effectively addressing the scale variation and complex backgrounds remain challenging tasks. To address these challenges, we pro...
Soil organic matter (SOM) scale effects are critical for crop growth and food security, especially in coal–grain complexes. However, few studies describe the spatial variation in SOM and its influencing factors at different sampling scales. Her...
In this paper, we consider one of the key problems in modular arithmetic. It is known that scaling in the residue number system (RNS) is a rather complicated non-modular procedure, which requires expensive and complex operations at each iteration. He...
Lightweight service identification models are very important for resource-constrained distribution grid systems. To address the increasingly larger deep learning models, we provide a method for the lightweight identification of complex power services...
Hyperspectral image (HSI) denoising is a crucial step in image preprocessing as its effectiveness has a direct impact on the accuracy of subsequent tasks such as land cover classification, target recognition, and change detection. However, existing m...
Engineering data, including product data-conversion networks and software dependency networks, are very important for the long-term preservation of product information. With the explosive growth of data in recent years, product information has become...
Background: In a patient-centred model of care, referral to early palliative care (EPC) depends on both the prognosis and the complexity of care needs. The PALCOM scale is a 5-domain multidimensional assessment tool developed to identify the level of...
Recently, deep neural network-based image compressed sensing methods have achieved impressive success in reconstruction quality. However, these methods (1) have limitations in sampling pattern and (2) usually have the disadvantage of high computation...
Assessing the dynamical complexity of biological time series represents an important topic with potential applications ranging from the characterization of physiological states and pathological conditions to the calculation of diagnostic parameters....
Farming systems are complex and include a variety of interacting biophysical and technical components. This complexity must be taken into account when designing farming systems to improve sustainability, but more methods are needed to be able to do s...
The manufacturing accuracy of large-scale complex components determines the performance and quality of aircraft, ships, high-speed rail, and other equipment. High-precision 3D measurement plays a crucial role in ensuring manufacturing accuracy. At pr...
A navigation method for a lunar rover based on large scale wireless sensornetworks is proposed. To obtain high navigation accuracy and large exploration area, highnode localization accuracy and large network scale are required. However, thecomputatio...
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