Transformer has recently become widely adopted in point cloud registration. Nevertheless, Transformer is unsuitable for handling dense point clouds due to resource constraints and the sheer volume of data. We propose a method for directly regressing...
The increase in cybersecurity threats has made attack detection systems critically important. Traditional deep learning methods often require large amounts of data and struggle to understand relationships between features effectively. With their self...
Oral cancer, a pervasive and rapidly growing malignant disease, poses a significant global health concern. Early and accurate diagnosis is pivotal for improving patient outcomes. Automatic diagnosis methods based on artificial intelligence have shown...
This paper focuses on the study of the high frequency transformer incorporated in solid- state transformers, specifically on the development of the steps that enable the design of an optimized high frequency transformer and its equivalent model based...
Transformer load is a key factor influencing its aging and service life. Accurately predicting load trends is crucial for assisting load redistribution. This study proposes a hybrid model called RIME-VMD-TCN-iTransformer to forecast the trend of tran...
There were many promising superconducting materials discovered in the last decades that can significantly increase the efficiency of large power transformers. However, these large machines are generally custom-made and tailored to the given applicati...
The aim of this paper is to show that the developed inductive current transformer may ensure the required wideband transformation accuracy and it may be applied, as the reference source, in the measuring system for the evaluation of the transformatio...
Epilepsy is a chronic neurological disease associated with abnormal neuronal activity in the brain. Seizure detection algorithms are essential in reducing the workload of medical staff reviewing electroencephalogram (EEG) records. In this work, we pr...
Recently, Transformer-based models have shown promising results in automatic speech recognition (ASR), outperforming models based on recurrent neural networks (RNNs) and convolutional neural networks (CNNs). However, directly applying a Transformer t...
This study investigates the vibration and noise characteristics of oil-immersed power transformers, with a particular focus on the influence of transformer oil on structural dynamics and acoustic emission. The research integrates multi-physics modell...
Sentiment analysis is essential for understanding consumer opinions, yet selecting the optimal models and embedding methods remains challenging, especially when handling ambiguous expressions, slang, or mismatched sentiment–rating pairs. This s...
This paper addresses the multi-trajectory prediction problem and a so-called Embedded-TCN-Transformer (EmbTCN-Transformer) model is designed by using the real-time historical trajectories in a formation. A temporal convolutional network (TCN) is util...
The increased use of electrical energy will encourage the installation of more power transformers in residential areas as well as in industrial areas. Each power transformer, in its operation, will generate noise that can interfere with comfort and,...
21 October 2021
In the recent pandemic, accurate and rapid testing of patients remained a critical task in the diagnosis and control of COVID-19 disease spread in the healthcare industry. Because of the sudden increase in cases, most countries have faced scarcity an...
Renewable energy resources and new loads—such as electric vehicles—challenge grid management. Among several scenarios, the smart transformer represents a solution for simultaneously managing low- and medium-voltage grids, providing ancillary services...
Defect detection is crucial for quality control in industrial products. The defects in industrial products are typically subtle, leading to reduced accuracy in detection. Furthermore, industrial defect detection often necessitates high efficiency in...
The performance and efficiency of high-frequency transformers (HFTs) are significantly influenced by leakage inductance. To improve the efficiency of HFTs, it is crucial to consider the effects of leakage inductance during the design and analysis pro...
Semantic segmentation for remote sensing images (RSIs) is widely applied in geological surveys, urban resources management, and disaster monitoring. Recent solutions on remote sensing segmentation tasks are generally addressed by CNN-based models and...
With the introduction of numerous technologies and equipment, the volume of data in smart substations has undergone exponential growth. In order to enhance the intelligent management level of substations and promote their efficient and sustainable de...
This paper presents a new model for multi-object tracking (MOT) with a transformer. MOT is a spatiotemporal correlation task among interest objects and one of the crucial technologies of multi-unmanned aerial vehicles (Multi-UAV). The transformer is...
The effect of catalysts in the form of a transformer copper winding with Kraft paper insulation on the lifetime of transformer oil was studied via ultraviolet-visible (UV-Vis) spectroscopy and Fourier transform infrared (FT-IR) spectroscopy. The test...
The tracker based on the Siamese network describes the object-tracking task as a similarity-matching problem. The Siamese network is the current mainstream model. It achieves similarity learning by applying correlation filters to the target and searc...
The quality of remote sensing images has been greatly improved by the rapid improvement of unmanned aerial vehicles (UAVs), which has made it possible to detect small objects in the most complex scenes. Recently, learning-based object detection has b...
Multi-person pose forecasting involves predicting the future body poses of multiple individuals over time, involving complex movement dynamics and interaction dependencies. Its relevance spans various fields, including computer vision, robotics, huma...
Instrument current transformers (CTs) measure AC currents. The DC component in the measured current can saturate the transformer and cause gross error. We use fluxgate detection and digital feedback compensation of the DC flux to suppress the overall...
An on-chip transformer with a ferrofluid magnetic core has been developed and tested. The transformer consists of solenoid-type coil and a magnetic core of ferrofluid, with the former fabricated by MEMS technology and the latter by a chemical co-prec...
Weed control is among the most challenging issues for crop cultivation and turf grass management. In addition to hosting various insects and plant pathogens, weeds compete with crop for nutrients, water and sunlight. This results in problems such as...
In recent times, transformer-based deep learning models have risen in prominence in the field of machine learning for a variety of tasks such as computer vision and text generation. Given this increased interest, a historical outlook at the developme...
A voltage transformer employing the magnetoelectric effect in a composite ceramic heterostructure with layers of a magnetostrictive nickel–cobalt ferrite and a piezoelectric lead zirconate–titanate is described. In contrast to electromagn...
Deep convolutional neural networks (CNNs) can achieve good performance in image denoising due to their superiority in the extraction of structural information. However, they may ignore the relationships between pixels to limit effects for image denoi...
This paper presents a hybrid electromechanical transformer that passively transfers electrical power between galvanically isolated ports by coupling electrodynamic and piezoelectric transducers. The use of these two complementary electromechanical tr...
In recent years, remote sensing technology has been extensively used in detecting and managing natural disasters, playing a vital role in the early identification of events like landslides. The integration of deep learning models has considerably enh...
In urban public transportation systems, the accuracy of bus arrival time prediction is crucial to reduce passenger waiting time, increase satisfaction, and ensure efficient transportation operations. However, traditional bus information systems (BISs...
A power transformer is one of the most critical and expensive assets in electric power systems. Failure of a power transformer would not only result in a downtime to the entire transmission and distribution networks but may also cause personnel and e...
Capturing complex temporal dependencies across multiple scales remains a fundamental challenge in time series forecasting. Transformer-based models have achieved impressive performance on sequence tasks, but vanilla designs often struggle to integrat...
Identifying an individual based on their physical/behavioral characteristics is known as biometric recognition. Gait is one of the most reliable biometrics due to its advantages, such as being perceivable at a long distance and difficult to replicate...
Transformer efficiency is a key concern for both transformer operators and regulators, particularly with regards to new transformers. Cooling is a critical factor in preventing overheating and controlling the ageing of transformer insulation. This pa...
This paper presents for the first time a quad-core oscillator based on a very compact interstacked transformer that tightly couples the four cores without oscillation mode ambiguity thanks to its strong magnetic coupling factor. As a proof of concept...
The authors review the techniques applied to diagnose oil aging. Further, the authors put forward a new diagnostic method. It stipulates for an additional high-frequency measuring loop formed in an operating transformer. This dielcometric measuring c...
In recent years, the use of biodegradable fluids as liquid insulation for distribution and power transformers is spreading. The main biodegradable fluids used are natural and synthetic esters, although biodegradable hydrocarbons have been recently pr...
As is well known, the high installation and operational costs of the unified power flow controller (UPFC) restrict its widespread applications in power grid. An economical “Sen” transformer (ST) that is composed of a three-phase four-wind...
Human–object interaction (HOI) is a human-centered object detection task that aims to identify the interactions between persons and objects in an image. Previous end-to-end methods have used the attention mechanism of a transformer to spontaneo...
In this paper, a bearing- and transformer-integrated electric excitation synchronous motor excitation system (bearing-integrated rotary transformer) is proposed to support the motor rotor and energy transmission of excitation systems. Firstly, the wo...
The article presents a method of determining dielectric losses that occur in insulating materials in a power transformer. These losses depend mainly on the electric field stress, pulsation, dielectric loss coefficient, and electrical permittivity of...
Artificial intelligence as an approach to visual inspection in industrial applications has been considered for decades. Recent successes, driven by advances in deep learning, present a potential paradigm shift and have the potential to facilitate an...
Researchers tackled the challenge of finding the right parameters for a transformer-equivalent circuit. They achieved this by minimizing the difference between actual measurements (currents, powers, secondary voltage) during a transformer load test a...
The resolution of feature maps is a critical factor for accurate medical image segmentation. Most of the existing Transformer-based networks for medical image segmentation adopt a U-Net-like architecture, which contains an encoder that converts the h...
This paper presents a novel Arduino-based fault detection and protection system for power transformers. Power transformers are an integral component of the power system infrastructure. Power transformers are present in such a significant number in th...
Following the significant success of the transformer in NLP and computer vision, this paper attempts to extend it to 3D triangle mesh. The aim is to determine the shape’s global representation using the transformer and capture the inherent mani...
Electricity companies around the world are constantly seeking ways to provide electricity more safely and efficiently while reducing the negative impact on the environment. Mineral oils have been the most popular transformer insulation, having excell...
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