Deep neural networks are successful learning tools for building nonlinear models. However, a robust deep learning-based classification model needs a large dataset. Indeed, these models are often unstable when they use small datasets. To solve this is...
Surface roughness is one of the main bases for measuring the surface quality of machined parts. A large amount of training data can effectively improve model prediction accuracy. However, obtaining a large and complete surface roughness sample datase...
Orbit uncertainty propagation plays an important role in the analysis of a space mission. The accuracy and computation expense are two critical essences of uncertainty propagation. Repeated evaluations of the objective model are required to improve t...
Surface roughness is a critical indicator for assessing the quality and characteristics of workpieces, the accurate prediction of which can significantly enhance production efficiency and product performance. Data-driven methods are efficient ways fo...
Finger vein recognition is considered to be a very promising biometric identification technology due to its excellent recognition performance. However, in the real world, the finger vein recognition system inevitably suffers from the single-sample pr...
Corrosion is the predominant failure mechanism in marine steel, and accurate corrosion prediction is essential for effective maintenance and protection strategies. However, the limited availability of corrosion datasets poses significant challenges t...
Generative adversarial networks are known as being capable of outputting data that can imitate the input well. This characteristic has led the previous research to propose the WGAN_MTD model, which joins the common version of Generative Adversarial N...
In recent years, generative adversarial networks (GANs) have been proposed to generate simulated images, and some works of literature have applied GAN to the analysis of numerical data in many fields, such as the prediction of building energy consump...
Chloride diffusivity of concrete is essentially determined by its microstructural parameters. Establishing a reliable and accurate prediction model for chloride diffusion has become a research hotspot. In this study, a database containing 144 sets of...
Determining the appropriate sample size is crucial in clinical studies due to the potential limitations of small sample sizes in detecting true effects. This work introduces the use of Wasserstein Generative Adversarial Networks (WGANs) to create vir...
Because of the high cost of experimental data acquisition, the limited size of the sample set available when conducting tissue structure ultrasound evaluation can cause the evaluation model to have low accuracy. To address such a small-sample problem...
The prediction of the ablation rate of silicone rubber-based composites is of great significance to accelerate the development of flexible thermal protection materials. Herein, a method which combines uniform design experimentation, active learning,...
The bioequivalence (BE) of highly variable drugs is a complex issue in the pharmaceutical industry. The impact of this variability can significantly affect the required sample size and statistical power. In order to address this issue, the EMA and FD...
This study introduces artificial intelligence as a powerful tool to transform bioequivalence (BE) trials. We apply advanced generative models, specifically Wasserstein Generative Adversarial Networks (WGANs), to create virtual subjects and reduce the...
Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs) have been widely used in hyperspectral image classification (HSIC) tasks. However, the generated HSI virtual samples by VAEs are often ambiguous, and GANs are prone to the mod...
Sample size estimation is critical in clinical trials. A sample of adequate size can provide insights into a given population, but the collection of substantial amounts of data is costly and time-intensive. The aim of this study was to introduce a no...
The effectiveness of in virtuo exposure-based treatment of performance-only social anxiety disorder (SAD) has been demonstrated in several studies. However, few studies have validated virtual environments with participants suffering from generalized...
Recent research has shown that spatial-spectral information can help to improve the classification of hyperspectral images (HSIs). Therefore, three-dimensional convolutional neural networks (3D-CNNs) have been applied to HSI classification. However,...
In today’s digital era, rumors spreading on social media threaten societal stability and individuals’ daily lives, especially multimodal rumors. Hence, there is an urgent need for effective multimodal rumor detection methods. However, exi...
This review article is the continuation of a previous publication, by the same author, on one dimensional theory of space charge effect and virtual cathode. The virtual cathode is known to be unstable. However, the process of virtual cathode oscillat...
This study aimed to assess third-year student pharmacists’ perspectives regarding a virtually delivered research proposal course. A 23-item questionnaire was distributed to third-year student pharmacists enrolled in a research proposal course o...
Hyperspectral classification is an important technique for remote sensing image analysis. For the current classification methods, limited training data affect the classification results. Recently, Conditional Variational Autoencoder Generative Advers...
In this paper, we propose a method for the generation of simulated test scenarios for autonomous driving. Based on the requirements of standard regulatory test scenarios, we can generate virtually simulated scenarios and functional scenario libraries...
In the context of the “Carbon peak, Carbon neutral” target, the introduction of carbon trading and the connection of new energy generation such as wind power and photovoltaics to the power grid have become important means to achieve a red...
Until the outbreak of the COVID-19 pandemic, virtual tourism was not as popular as during its duration in 2021, when traveling in the real world was not possible due to social isolation and forced quarantine. In response to the lockdown and the lack...
Satellite-derived bathymetry (SDB) using Ice, Cloud, and Land Elevation satellite-2 (ICESat-2) LiDAR data and remote sensing images faces challenges in the difficulty of uniform coverage of the inversion area by the bathymetric control points due to...
Nowadays, technological teaching tools, such as virtual labs, have become essential, especially in nursing degrees. These resources help implement practical learning based on self-regulation and it is important to know how satisfied students are with...
In spite of the tremendous success in artificial intelligence technology and a high level of automation in geospatial data obtaining processes, there is still a need for topographical field data collection by professional surveyors. Understanding ter...
This paper proposes a framework that enables the online generation of virtual point clouds relying only on previous camera and point clouds and current camera measurements. The continuous usage of the pipeline generating virtual LIDAR measurements ma...
The objective of the study was to put forth an interpolation method (the LZ method) for refining the GNSS-derived precipitable water vapor (PWV) map. We established a regional weighted mean temperature (Tm) model for this experiment, which introduced...
8 March 2023
Background: The onset of the coronavirus disease in 2019 necessitated a rapid transition to virtual care for chronic pain treatment. Methods: A mixed methods design was implemented using qualitative interviews and quantitative satisfaction surveys. I...
To better control eutrophication, reliable and accurate information on phosphorus and nitrogen loading is desired. However, the high-frequency monitoring of these variables is economically impractical. This necessitates using virtual sensing to predi...
We deal with the problem of characterizing a source or scatterer from electromagnetic radiated or scattered field measurements. The problem refers to the amplitude and phase measurements which has applications also to interferometric approaches at op...
Evidence suggests that moderate to vigorous physical activity (MVPA) is necessary for health benefits. Immersive virtual reality is a technology that uses images, sounds, and tactile sensations from a simulated world to encourage healthy behaviours a...
Interrupted-sampling repeater modulation (ISRM) can generate multiple virtual target images by sampling and forwarding radar signals to confront the inverse synthetic aperture radar (ISAR). However, the repeating delay is unavoidable and the system i...
In this paper, an improved two-dimensional (2-D) direction of arrival (DOA) estimation algorithm for L-shaped nested arrays is proposed. Unlike the approach for a classical nested array, which use the auto-correlation matrix (ACM) to increase the deg...
The study is dedicated to the accuracy of engineering analyses of virtual prototypes. In particular, it aims to quantify the importance of material models and data consistent with physical tests. The focus is set on the stress–strain material c...
Accessible palaeontological sites conform highly adequate out-of-school environments for meaningful learning experiences regarding formal and non-formal teaching of geosciences. With a perspective of international cooperation, two correlative Cenoman...
In this paper, we present a novel microfluidic mixer with staggered virtual electrode based on light-actuated AC electroosmosis (LACE). We solve the coupled system of the flow field described by Navier–Stokes equations, the described electric field b...
The choice of furniture in a retail store is usually based on a product catalog and simplistic product renderings with different configurations. We present a preliminary field study that tests a Multi-Sensory In-Store Virtual Reality Customer Journey...
Virtual experiments are a digital representation of a real measurement and play a crucial role in modern measurement sciences and metrology. Beyond their common usage as a modeling and validation tool, a virtual experiment may also be employed to per...
In coastal water monitoring, abrupt pH changes might indicate different pollution sources. Existing sensors for pH monitoring in coastal waters at low cost are mainly based on a glass membrane and a reference electrode. Virtual sensors are elements c...
The automated detection of distress such as cracks or potholes is a key basis for assessing the condition of pavements and deciding on their maintenance. A fine-grained pavement distress-detection algorithm based on integrated data using a digital tw...
Because of the occurrence of severe and large magnitude earthquakes each year, earthquake-prone countries suffer considerable financial damages and loss of life. Teaching essential safety measures will lead to a generation that can perform basic proc...
There have been decades of research on face recognition, and the performance of many state-of-the-art face recognition algorithms under well-conditioned environments has become saturated. Accordingly, recent research efforts have focused on difficult...
This study investigated the effectiveness of a five-session virtual professional development program designed to increase the knowledge of inclusive education practices among school-based professionals from 26 schools on a topic of their choice. Part...
There have been no nationwide studies of patient opinions regarding telehealth in Saudi Arabia to identify the factors that might influence patients’ perceptions and satisfaction. This was a prospective cross-sectional study of adults in the ge...
Small series production with a high level of variability is not suitable for full automation. So, a manual assembly process must be used, which can be improved by cooperative robots and assisted by augmented reality devices. The assisted assembly pro...
Background/Objectives: Non-specific low back pain represents a high number of primary care consultations, generating a great social and economic cost. There is a higher prevalence in women, and it may be associated with multiple factors. One of the m...
Increasingly, robotic systems require a level of perception of the scenario to interact in real-time, but they also require specialized equipment such as sensors to reach high performance standards adequately. Therefore, it is essential to explore al...
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