This study employs the FLACS code to analyze hydrogen leakage, vapor dispersion, and subsequent explosions. Utilizing pseudo-source models, a liquid pool model, and a hybrid model combining both, we investigate dispersion processes for varying leak m...
Partially coherent sources with non-conventional coherence properties present unusual behaviors during propagation, which have potential application in fields like optical trapping and microscopy. Recently, partially coherent sources exhibiting circu...
All pseudo-Schell model sources have been shown to possess the same continuous set of circularly symmetric modes, all of them presenting a conical wavefront. For keeping energy at a finite level, the mode amplitude along the radial coordinate is modu...
When segmenting massive amounts of remote sensing images collected from different satellites or geographic locations (cities), the pre-trained deep learning models cannot always output satisfactory predictions. To deal with this issue, domain adaptat...
Unsupervised domain adaptation (UDA) effectively transfers knowledge learned from a labeled source domain to an unlabeled target domain. The teacher–student framework, which generates pseudo-labels for target domain samples and uses them for ps...
In the fault diagnosis of complex industrial systems, labeled samples are expensive to obtain, which leads to insufficient training data for the belief rule base (BRB) model. Although unlabeled samples are abundant, the uncertainty of their pseudo-la...
Deep neural networks suffer performance drops when source and target domains differ in distribution, motivating research into domain adaptation (DA). Traditional DA approaches presume source samples come from a single domain and can be available duri...
Inverters are playing an increasingly important role in the electrical utility grid due to the proliferation of renewable energy sources. Obtaining inverter models with accurate parameters is, therefore, essential for grid studies and design. In this...
The automated detection of deep-sea polymetallic nodules is critical for processing large volumes of benthic imagery. However, its scalability faces challenges from cross-expedition covariate shifts, such as changes in lighting, altitude, and camera...
Multi-source domain adaptation (MSDA) plays an important role in industrial model generalization. Recent efforts regarding MSDA focus on enhancing multi-domain distributional alignment while omitting three issues, e.g., the class-level discrepancy qu...
Accurate retinal vessel segmentation supports quantitative vascular analysis in assessing ocular and systemic diseases. Yet, its clinical scalability is constrained by limited pixel-level annotations and domain shift across heterogeneous fundus datas...
The teacher–student framework has been employed in unsupervised domain adaptation, which transfers knowledge learned from a labeled source domain to an unlabeled target domain. However, this framework suffers from two serious challenges: the do...
Cross-scene classification focuses on setting up an effective domain adaptation (DA) way to transfer the learnable knowledge from source to target domain, which can be reasonably achieved through the pseudo-label propagation procedure. However, it is...
Although plastic scintillation detectors possess poor spectroscopic characteristics, they are extensively used in various fields for radiation measurement. Several methods have been proposed to facilitate their application of plastic scintillation de...
This study proposes a hybrid computational model for diagnosing such biases using groundwater observation data across Kazakhstan. The analytical dataset included 2402 georeferenced observations, including 492 natural springs from OpenStreetMap (OSM),...
Radio-frequency (RF) fingerprint distributions vary across collection dates, and changes in propagation conditions and hardware states can degrade transmitter-identification performance. To address this issue, we propose Source-Free Class-Balanced Ps...
Graph pseudo-labeling is an effective semi-supervised learning (SSL) approach to improve graph neural networks (GNNs) by leveraging unlabeled data. However, its success heavily depends on the reliability of pseudo-labels, which can often result in co...
Many oil wells in closed reservoirs continue to produce in the pseudo-steady-state flow regime for a long time. The principal objective of this work is to investigate the characteristics of two key pseudo-steady-state parameters—pseudo-steady-s...
Vehicle Re-Identification (Re-ID) based on Unsupervised Domain Adaptation (UDA) has shown promising performance. However, two main issues still exist: (1) existing methods that use Generative Adversarial Networks (GANs) for domain gap alleviation com...
Wastes are the sustainable sources of raw materials for the synthesis of new adsorbent materials. This study has as objectives the advanced capitalization of fly ash, by sulphuric acid activation methods, and testing of synthesized materials for heav...
Facing the challenges of scarce annotations in forward-looking sonar image segmentation, this paper proposes a teacher–student network for unsupervised domain adaptation. The proposed model undergoes supervised learning with optical image data...
4 November 2013
The presence of heavy metals in the environment constitutes a potential source of both soil and groundwater pollution. This study has focused on the reactivity of lead (Pb), copper (Cu) and Cadmium (Cd) during their transfer in a calcareous soil of P...
Spoofing interference is one of the most emerging threats to the Global Navigation Satellite System (GNSS); therefore, the research on anti-spoofing technology is of great significance to improving the security of GNSS. For single spoofing source int...
Glaucoma is a serious eye condition that damages the optic nerve and affects the transmission of visual information to the brain. It is the second leading cause of blindness worldwide. With deep learning, CAD systems have shown promising results in d...
Recent years have witnessed outstanding success in supervised domain adaptive person re-identification (ReID). However, the model often suffers serious performance drops when transferring to another domain in real-world applications. To address the d...
Carbon dioxide (CO2) has been deemed a significant contributor to the climate crisis and has an impact on environmental systems. Adsorption is widely used among other technologies for carbon capture because of its many benefits. As a starting materia...
Conventional machine learning relies on two presumptions: (1) the training and testing datasets follow the same independent distribution, and (2) an adequate quantity of samples is essential for achieving optimal model performance during training. Ne...
The task of tracking weak targets in low-altitude UAV scenarios requires high robustness and generalization ability of the model. Against this backdrop, this paper proposes a novel annotation and training mechanism based on SwinTrack. To improve the...
Deep learning has been widely used in various tasks such as computer vision, natural language processing, predictive analysis, and recommendation systems in the past decade. However, practical scenarios often lack labeled data, posing challenges for...
10 November 2015
On-site soils are increasingly used in the treatment and restoration of ecosystems to harmonize with the local landscape and minimize costs. Eight natural soils from diverse ecological zones in the source area of a drinking-water reservoir in central...
Unsupervised domain adaptation (UDA) is essential since manually labeling pixel-level annotations is consuming and expensive. Since the domain discrepancies have not been well solved, existing UDA approaches yield poor performance compared with super...
Source-free domain adaptation (SFDA) for cross-modality prostate MRI segmentation is challenging because source data are unavailable and pseudo-labels on target ADC images are often noisy. To address this problem, we propose Curriculum Anatomy-guided...
As a common brain-computer interface (BCI) paradigm, electroencephalogram (EEG)-based motor imagery provides a critical pathway for both assistive technology to (restoring communication and control) and active rehabilitation (promoting neural plastic...
The enzymatic hydrolysis of cellulose from biomass feedstock in the sugar-based biorefinery chain is penalized by enzyme cost and difficulty to approach the theoretical maximum cellulose conversion degree. As a consequence, the process is currently i...
This study investigated the root uptake and adsorption kinetics of Kiperin dihydrolyzed collagen (KDHC), an organic nitrogen source rich in amino acids and low-molecular-weight peptides, in radish (Raphanus sativus L.) seedlings grown in perlite. KDH...
With the increasing connectivity and automation on the Internet of Vehicles, safety, security, and privacy have become stringent challenges. In the last decade, several cryptography-based protocols have been proposed as intuitive solutions to protect...
We reported the second- and third-order temporal interference of two non-degenerate pseudo-thermal sources in a nitrogen-vacancy center (NV−). The relationship between the indistinguishability of source and path alternatives is analyzed at low temper...
Remote sensing building change detection is important for monitoring urban expansion, rural settlement dynamics, post-disaster reconstruction, and human-induced land transformation. However, most existing change detection models are optimized under i...
In this paper, we propose a new reduced-dynamic (RD) method by introducing the second-order time-difference position (STP) as additional pseudo-observations (named the RD_STP method) for the precise orbit determination (POD) of low Earth orbiters (LE...
Pseudo-satellite technology has excellent compatibility with the BDS satellite navigation system in terms of signal systems. It can serve as a stable and reliable positioning signal source in signal-blocking environments. User terminals can achieve c...
Computer-vision-based monitoring of aquatic organisms and benthic targets requires detectors that remain reliable across variable water bodies and acquisition conditions. Underwater imagery is affected by wavelength-dependent attenuation, scattering,...
Reliable state estimation is essential for the secure and efficient operation of sustainable energy systems, especially under the increasing integration of renewable energy, distributed resources, and heterogeneous sensing devices. However, in practi...
During natural disasters, social media platforms, such as X (formerly Twitter), become a valuable source of real-time information, with eyewitnesses and affected individuals posting messages about the produced damage and the victims. Although this in...
The comprehension of source code is very difficult, especially if the programmer is not familiar with the programming language. Pseudocode explains and describes code contents that are based on the semantic analysis and understanding of the source co...
Swift and accurate semantic segmentation of underwater images is key for precise object recognition in complex underwater environments. Nonetheless, the inherent complexity of these environments and the limited availability of labeled data pose signi...
The adsorption and desorption characteristics of cadmium (Cd) in uncontaminated soils have been investigated in numerous studies. However, similar studies on Cd-polluted soils from different sources, which exhibit complex physicochemical characterist...
The current work explores the adsorptive efficiency of carbon nanospheres (CNSs) derived from oil palm leaves (OPL) that are a source of biowaste. CNSs were synthesized at 400, 600, 800 and 1000 °C, and those obtained at 1000 °C demonstrated...
Graphene sheets are a highly radiation-resistant material for prospective nuclear applications and nanoscale defect engineering. However, the precise mechanism of graphene radiation hardness has remained elusive. In this paper, we study the origin an...
Accurate glaucoma diagnosis relies on precise segmentation of the optic disc (OD) and optic cup (OC) in retinal images. However, despite the development of numerous automatic segmentation models, the lack of annotations in the target domain and domai...
Given the diversity of medical images, traditional image segmentation models face the issue of domain shift. Unsupervised domain adaptation (UDA) methods have emerged as a pivotal strategy for cross modality analysis. These methods typically utilize...
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