In this paper, a novel approach to facial expression recognition based on the discrete separable shearlet transform (DSST) and normalized mutual information feature selection is proposed. The approach can be divided into five steps. First, all test a...
With the growth of nonlinear electrical equipment, power quality disturbances (PQDs) often appear in electrical systems. To solve this, a practical heuristic methodology for PQD detection and classification based on empirical wavelet transform has be...
Despite the fact that Versatile Video Coding (VVC) achieves a superior coding performance to High-Efficiency Video Coding (HEVC), it takes a lot of time to encode video sequences due to the high computational complexity of the tools. Among these tool...
Slowness extraction via Slowness Time Coherence (STC) serves as a fundamental technique for formation evaluation in oil and gas geophysics. Conventional amplitude-dependent peak selection methods often exhibit limitations in complex logging scenarios...
Accurate and reliable dam inflow prediction models are essential for effective reservoir operation and management. This study presents a data-driven model that couples a long short-term memory (LSTM) network with robust input predictor selection, inp...
In order to improve the recognition accuracy and efficiency of power quality disturbances (PQD) in microgrids, a novel PQD feature selection and recognition method based on optimal multi-resolution fast S-transform (OMFST) and classification and regr...
Tool wear is an important concern in the manufacturing sector that leads to quality loss, lower productivity, and increased downtime. In recent years, there has been a rise in the popularity of implementing TCM systems using various signal processing...
Traditional fault phase selection methods are not easily adaptable to large-scale wind farms. This paper proposes a fault phase selection method based on transient voltage S-transform energy relative entropy (SERE) to realize adaptive reclosing of th...
Under complex operating conditions, vibration signals from rotating machinery often exhibit non-stationary characteristics with non-proportional and closely spaced instantaneous frequency (IF) components. Traditional time–frequency analysis (TF...
Deep learning algorithms are pivotal in the identification and classification of microseismic signals in mines subjected to impact pressure. However, conventional machine learning techniques often struggle to balance interpretability, computational e...
Partial discharge (PD) testing based on IEC 60270 is widely employed for assessing the insulation integrity of power transformers. Although numerous statistical descriptors can be extracted from PD measurements, redundant and irrelevant features can...
The feature selection (FS) procedure is a critical preprocessing step in data mining and machine learning, aiming to enhance model performance by eliminating redundant features and reducing dimensionality. The Energy Valley Optimizer (EVO), inspired...
This research utilized the E. coli manA gene encoding phosphomannose isomerase (PMI) selection on sucrose/mannose medium to increase transformation efficiencies after biolistic transformation of two immature citrus rootstock cultivars. Plasmid DNA, c...
Transformer-based language models have been increasingly adopted to enhance semantic awareness in web service selection systems. However, the computational cost of large transformer encoders poses significant challenges for real-time and resource-con...
Background: Thymoma is a tumor that originates in the thymus gland, a part of the human body located behind the breastbone. It is a malignant disease that is rare in children but more common in adults and usually does not spread outside the thymus. T...
Two Citrus sinensis (L.) phosphomannose isomerase (PMI) genes, CsPMI1 and CsPMI2, were evaluated as novel selectable markers in mature citrus transformation. Transgenic shoots produced after transformation of Kuharske rootstock with each PMI construc...
To better understand and control the crystallization of different polymorphs, a comprehensive crystal structure analysis was conducted by using fluralaner as a model compound, and the thermodynamic stability, phase transformation, and selective nucle...
In the growing field of Natural Language Processing (NLP), transformers have become excessively large, pushing the boundaries of both training and inference compute. Given the size and widespread use of these models, there is now a strong emphasis on...
Dissolved gas in oil (DGA) is a common means of monitoring the condition of an oil-immersed transformer. The concentration of dissolved gas and the ratio of different gases are important indexes to judge the condition of power transformers. Monitorin...
Furfural is an intermediary and aldehyde compound degraded from paper insulation, which is used with liquid fluid in power transformers. It can be utilized as an important indicator to evaluate the degradation degree of the paper insulation and the c...
Lower-grade gliomas (LGGs) often follow a relatively protracted clinical course; however, a substantial proportion eventually undergo malignant transformation to high-grade, treatment-refractory disease. This process has traditionally been interprete...
We study an interacting particle system on the unit sphere
To address the challenge of accurately assessing transformer health under multi-source heterogeneous data conditions and to enable precise full-lifecycle lifetime prediction along with interpretable decision-making insights, we propose an ensemble le...
Background: Aspergilloma disease is a fungal mass found in organs such as the sinuses and lungs, caused by the fungus Aspergillus. This disease occurs due to the accumulation of mucus, inflamed cells, and altered blood elements. Various surgical meth...
This study determined the critical parameters for the morphological development of the electrode surface (the critical potential and the critical charge) during anodic selective dissolution of a Cu–Pd alloy with a volume concentration of 15 at....
Accurate fault diagnosis of power transformers is critical for maintaining grid reliability, yet conventional dissolved gas analysis (DGA) methods face challenges in feature representation and high-dimensional data processing. This paper presents an...
Accurately extracting deviation features in frequency response curves, which reflect winding deformation states, and selecting appropriate machine learning algorithms are critical for achieving a precise quantitative diagnosis of winding deformation...
Protoplast transformation for the introduction of recombinant DNA into Aspergillus nidulans is technically demanding and dependant on the availability and batch variability of commercial enzyme preparations. Given the success of Agrobacterium tumefac...
Purpose: The construction industry is now experiencing a thorough transformation through digital technologies, especially with building information modeling (BIM). Despite significant BIM advantages, most construction projects suffer from low BIM per...
The growing sophistication of malware and other cyber threats presents significant challenges for detection and prevention in modern cybersecurity systems. In this paper an efficient and novel malware classification model using the Hybrid Resnet-Tran...
In this study, we analyzed the coupling effect of laser scanning speed and wall thickness on the phase transformation behavior and tensile properties of selective laser melted NiTi thin-wall structures. It is demonstrated that either scanning speed o...
To address the challenges brought by the high penetration of renewable energy in power systems, such as multi-scale dynamic interactions, high feature dimensionality, and limited model generalization, this paper proposes a transient stability assessm...
This article investigated the microstructure of Ti6Al4V that was fabricated via selective laser melting; specifically, the mechanism of martensitic transformation and relationship among parent β phase, martensite (α’) and newly gener...
Due to unique functional and mechanical properties, NiTi shape memory alloys are one of the most promising metallic functional materials. However, the poor workability limits the extensive utilization of NiTi alloys as components of complex shapes. T...
Early and accurate detection of distributed bearing faults is essential to prevent equipment failures and reduce downtime in industrial environments. This study explores the optimal selection of input signal sources for high-accuracy distributed faul...
Artificial metalloenzymes (ArMs) comprise a synthetic metal complex in a protein scaffold. ArMs display performances combining those of both homogeneous catalysts and biocatalysts. Specifically, ArMs selectively catalyze non-natural reactions and rea...
In a neutral ungrounded system, the high voltage fuses used to protect voltage transformers (VTs) often abnormally blow out, causing unbalanced VT operation. Fuses also fail to blow out in time, resulting in further damage to the VT. This paper repor...
Hyperspectral images, characterized by rich spectral information, enable precise pixel-level classification and are thus widely employed in remote sensing applications. Although convolutional neural networks (CNNs) have demonstrated effectiveness in...
Gastrodin is one of the most important biologically active components of Gastrodia elata, which has many health benefits as a dietary and health food supplement. However, gastrodin measurement traditionally relies on laboratory and sophisticated inst...
This paper proposes a novel hybrid forecasting model with three main parts to accurately forecast daily electricity prices. In the first part, where data are divided into high- and low-frequency data using the fractional wavelet transform, the best d...
Attention is one of many human cognitive functions that are essential in everyday life. Given our limited processing capacity, attention helps us focus only on what matters. Focusing attention on one speaker in an environment with many speakers is a...
Transform-based tensor algebras induced by invertible linear transforms provide a unified framework for tensor operations and spectral analysis. This paper investigates how the choice of a unitary transform affects the quantitative tightness of class...
Parkinson’s disease (PD) is a clinically and biologically heterogeneous neurodegenerative disorder in which variable symptom profiles, progression rates, and treatment responses likely reflect distinct but partially convergent pathogenic mechan...
Historical measurements are usually used to build assimilation models in sequential data assimilation (S-DA) systems. However, they are always disturbed by local noises. Simultaneously, the accuracy of assimilation model construction and assimilation...
Recent advancements in the detection Transformer model have demonstrated remarkable accuracy in real-time object detection using an end-to-end approach. DETR leverages the concept of object queries, which act as “questions” to determine t...
Sugar beet, one of the most important natural sources of sugars in the world, is well known as a recalcitrant crop for genetic transformation. In the present study, several key components of Agrobacterium-mediated transformation of sugar beet have be...
Botrytis cinerea can infect almost all of the important horticultural crops and cause severe economic losses globally every year. Modifying candidate genes and studying the phenotypic changes are among the most effective ways to unravel the pathogeni...
Selectable marker genes are useful for recognizing which cells have integrated specific sequences in their genome after genetic transformation processes. They are especially important for fruit trees genetic transformation to individuate putatively g...
Speech emotion recognition (SER) tasks are conducted to extract emotional features from speech signals. The characteristic parameters are analyzed, and the speech emotional states are judged. At present, SER is an important aspect of artificial psych...
Background: Intestinal metaplasia (IM) is a precancerous gastric condition that requires accurate histopathological diagnosis to enable early intervention and cancer prevention. Traditional evaluation of H&E-stained tissue slides can be labor-int...
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