In our study, we examine how the temporal window shift—the step between consecutive analysis windows—affects EEG-based cognitive fatigue detection while keeping the window length fixed. Using a reference workload dataset and a pipeline th...
As a pioneering work that directly applies deep learning methods to raw point cloud data, PointNet has the advantages of fast convergence speed and high computational efficiency. However, its feature learning in local areas has a certain defect, whic...
Blood cells play an important role in the metabolism of the human body, and the status of blood cells can be used for clinical diagnoses, such as the ratio of different blood cells. Therefore, blood cell classification is a primary task, which requir...
Accurate photovoltaic (PV) power forecasting is essential to mitigating the security and stability challenges associated with PV integration into power grids. Ground-based sky images can quickly reveal cloud changes, and the spatiotemporal feature in...
Scene text detection has become a popular topic in computer vision research. Most of the current research is based on deep learning, using Convolutional Neural Networks (CNNs) to extract the visual features of images. However, due to the limitations...
The increasing water temperature due to climate change has led to more frequent algae blooms and deteriorating water quality in coastal areas and rivers worldwide. To address this, we developed a deep learning-based model for identifying floating alg...
This study examined whether the temporal patterns of energy and macronutrient intake in early and late eating windows were associated with metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) among non-shift workers. A total...
Lightweight Single-Image Super-Resolution (SISR) faces the core challenge of balancing computational efficiency with reconstruction quality, particularly in preserving both high-frequency details and global structures under constrained resources. To...
Accurate traffic prediction is significant in intelligent cities’ safe and stable development. However, due to the complex spatiotemporal correlation of traffic flow data, establishing an accurate traffic prediction model is still challenging....
In recent years, Transformer has shown great performance in speech enhancement by applying multi-head self-attention to capture long-term dependencies effectively. However, the computation of Transformer is quadratic with the input speech spectrogram...
In this work, we have followed ethanol evaporation at two different concentrations using a fiber optic spectrometer and a screen capture application with a resolving capacity of 10 ms. The transmission spectra are measured in the visible-near-infrare...
Micro-expressions, which are spontaneous and difficult to suppress, reveal a person’s true emotions. They are characterized by short duration and low intensity, making the task of micro-expression recognition challenging in the field of emotion...
Hyperspectral image classification (HSI) has rich applications in several fields. In the past few years, convolutional neural network (CNN)-based models have demonstrated great performance in HSI classification. However, CNNs are inadequate in captur...
Single-image super-resolution (SR) has long been a research hotspot in computer vision, playing a crucial role in practical applications such as medical imaging, public security and remote sensing imagery. However, all currently available methods foc...
To facilitate the realization of automated tea picking and enhance the speed and accuracy of tea leaf grading detection, this study proposes an improved YOLOv8 network for fresh tea leaf grading recognition. This approach integrates a Hierarchical Vi...
Precision rolling bearings serve as critical components in a range of diverse industrial applications, where their continuous health monitoring is essential for preventing costly downtime and catastrophic failures. Early-stage bearing defects present...
Cameras, especially those carried by drones, are the main tools used to detect wildfires in forests because cameras have much longer detection ranges than smoke sensors. Currently, deep learning is main method used for fire detection in images, and T...
We discuss the spread of epidemics caused by two viruses which cannot infect the same individual at the same time. The mathematical modeling of this epidemic leads to a kind of SIIRR model with two groups of infected individuals and two groups of rec...
We propose a novel continual self-supervised learning (CSSL) framework for simultaneously learning diverse features from multi-window-obtained chest computed tomography (CT) images and ensuring data privacy. Achieving a robust and highly generalizabl...
As low-temperature plasma plays an important role in semiconductor manufacturing, plasma diagnostics have been widely employed to understand changes in plasma according to external control parameters, which has led to the achievement of appropriate p...
Electromyography (EMG) signals have diverse applications, ranging from prosthetic hands and assistive suits to rehabilitation devices. Nonetheless, their performance suffers from cross-subject generalization issues, electrode shifts, and daily variab...
Deep learning models have demonstrated potential in Condition-Based Monitoring (CBM) for rotating machinery, such as induction motors (IMs). However, their performance is significantly influenced by the size of the training dataset and the way signal...
For the significant distortion problem caused by the special projection method of equi-rectangular projection (ERP) images, this paper proposes an omnidirectional image super-resolution algorithm model based on position information transformation, ta...
Artificial intelligence, with its remarkable adaptability, has gradually integrated into daily life. The emergence of the self-attention mechanism has propelled the Transformer architecture into diverse fields, including a role as an efficient and pr...
Data classification in streams where the underlying distribution changes over time is known to be difficult. This problem—known as concept drift detection—involves two aspects: (i) detecting the concept drift and (ii) adapting the classifier. Online...
Transformers have performed better than traditional convolutional neural networks (CNNs) for image super-resolution (SR) reconstruction in recent years. Currently, shifted window multi-head self-attention based on the swin transformer is a typical me...
Change point detection is widely used in signal detection, industrial engineering, economy, finance, biomedicine and many other fields. The widely used parametric methods require prior knowledge of the noise signal distribution, which are seldom real...
Universal, predictive attractor patterns configured by Lyapunov exponents (LEs) as a function of the control parameter are shown to characterize periodic windows in chaos just as in attractors, using a coherent model of the laser with injected signal...
In wavelength-tuning interferometry, the surface profile of the optical component is a key evaluation index. However, the systematic errors caused by the coupling error between the higher harmonics and phase shift error are considerable. In this rese...
Direct Position Determination (DPD) of coherent pulse trains using a single moving sensor is considered in this paper. Note that when a large observation window and relative maneuvering course between emitter and receiver both exist, the localization...
Time-gating of single-photon avalanche diodes (SPADs) was commonly used as a method to reduce dark noise in biomedical imaging applications where photon events are correlated with a reference clock. Time-gating was also used to obtain timing informat...
In this study, we examine the electrical characteristics of triple-gate feedback field-effect transistors (TG FBFETs) over a temperature range of −200 °C to 280 °C. With increasing temperature from 25 °C to 280 °C, the thermally...
Tailoring electromagnetic properties by meta-devices has aroused great interest with respect to manipulating light. However, the uncertainty of angular dispersion introduced by the incident waves prevents their further applications. Here, we propose...
The synchronization of time between devices is one of the more important and challenging problems in wireless networks. We discuss the problem of maximization of the probability of receiving a message from a device using a limited listening time wind...
The trend across the whole of society is to focus on natural and/or biodegradable materials such as cellulose (Cell) over synthetic polymers. Among other usage scenarios, Cell can be combined with electroactive components such as multiwall carbon nan...
This paper examines how the size of the rolling window, and the frequency used in moving average (MA) trading strategies, affects financial performance when risk is measured. We use the MA rule for market timing, that is, for when to buy stocks and w...
Climate variability poses great challenges to food security in West Africa, a region heavily dependent on rainfall for farming. Identifying sowing strategies that minimize yield losses for farmers in the region is crucial to securing their livelihood...
Solar-induced chlorophyll fluorescence (SIF) is highly correlated with photosynthesis and can be used for estimating gross primary productivity (GPP) and monitoring vegetation stress. The far-red band of the solar Fraunhofer lines (FLs) is close to t...
In the successive cancellation (SC) list decoding, the tree pruning operation retains the L best paths with respect to a metric at every decoding step. However, the correct path might be among the L worst paths due to the imposed penalties. In this c...
This article deals with the implementation of the P-Class PMU compliant with IEC/IEEE Standard 60255-118-1:2018 by usage of a multiple-resonator (MR)-based approach for harmonic analysis having been proposed recently. In previously published articles...
Shift work has been associated with an increased risk of developing chronic non-communicable diseases, such as obesity. The reduction in overnight fasting and its physiological consequences seem to affect the metabolic health of shift workers, but li...
Phase-measuring profilometry (PMP) is increasingly applied in high-accuracy three-dimensional shape measurement. However, various factors may result in the uncertainty of phase shift values in the PMP system, and phase errors induced by actual phase...
We demonstrate an ultrafast displaying Spectral Domain Optical Doppler Tomography system using Graphics Processing Unit (GPU) computing. The calculation of FFT and the Doppler frequency shift is accelerated by the GPU. Our system can display processe...
For the treatment of osteosarcoma, cisplatin (CDDP) can be substituted by carboplatin (CBDCA) to reduce toxicity. We report a single institution experience of CBDCA-based regimen. Two to three cycles of CBDCA + ifosfamide (IFO) therapy (window therap...
Within the field of Automatic Speech Recognition (ASR) systems, facing impaired speech is a big challenge because standard approaches are ineffective in the presence of dysarthria. The first aim of our work is to confirm the effectiveness of a new sp...
18 November 2022
Electroencephalography (EEG) signals can be analyzed in the temporal, spatial, or frequency domains. Noise and artifacts during the data acquisition phase contaminate these signals adding difficulties in their analysis. Techniques such as Independent...
Background: Exchangeable item repair systems are inventory systems. A nonfunctional item is exchanged for a functional item and returns to the system after being repaired. In our periodic review setting, repair is performed either in-house or outsour...
A bifunctional tunable metamaterial composed of pattern metal structure, graphene, and strontium titanate (STO) film is proposed and studied numerically and theoretically. The dual plasmon-induced transparency (PIT) window is obtained by coupling the...
This paper addresses the implications on the business model of district heating companies of the technology shift targeting lower temperatures in the distribution network. Lower temperatures are valuable, since heat supply to low-energy buildings wit...
Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) nighttime light data has become a key tool of the environmental and social scientific fields, but suffers from several validity problems. We highlight one such problem&md...
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