2023 October-1 - 200 articles
Digital Twins, which are virtual representations of physical systems mirroring their behavior, enable real-time monitoring, analysis, and optimization. Understanding and identifying the temporal dependencies included in the multivariate time series d...
This paper proposes a weakly supervised cross-domain person re-identification (Re-ID) method based on small sample data. In order to reduce the cost of data collection and annotation, the model design focuses on extracting and abstracting the informa...
Japanese adverbs are difficult to classify, with little progress made since the 1930s. Now in the age of large language models, linguists need a framework for lexical grouping that incorporates quantitative, evidence-based relationships rather than p...
This article presents the classification of optoelectronics encoder faults in a permanent magnet synchronous motor (PMSM) drive system. This paper proposes the deep neural networks (DNNs) speed sensor faults classification application in the vector-c...
The concept of spectrum sensing has emerged as a fundamental solution to address the growing demand for accessing the limited resources of wireless communications networks. This paper introduces a straightforward yet efficient approach that incorpora...
The Fourth Industrial Revolution, also known as Industrial 4.0, has greatly accelerated inter-connectivity and smart automation in industrial control systems (ICSs), which has introduced new challenges to their security. With the fast growth of the I...
The space radiation environment has a radiation effect on electronic devices, especially the total ionizing dose effect, which seriously affects the service life of spacecraft on-orbit electronic devices and electronic equipment. Therefore, it is par...
A CNN object detection method based on the structural reparameterisation technique using branch matching is proposed to address the problem of balancing accuracy and speed in object detection techniques. By the structural reparameterisation of the co...
In power semiconductor systems such as inverters, managing losses is critical for optimizing performance. Inverters, which convert DC to AC for applications such as renewable energy systems, motor drives, and power supplies, are significantly affecte...
Nowadays, in contemporary building and energy management systems (BEMSs), the predominant approach involves rule-based methodologies, typically employing supervised or unsupervised learning, to deliver energy-saving recommendations to building occupa...
To ensure lateral stability during the cruising of a differential steering vehicle (DSV), this paper presents a curving adaptive cruise control (ACC) system coordinated with a differential steering control (DSC) system, which considers both longitudi...
Traditional backward recursion methods face a fundamental challenge in solving Markov Decision Processes (MDP), where there exists a contradiction between the need for knowledge of optimal expected payoffs and the inability to acquire such knowledge...
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Cinematic Shot Attribute Analysis aims to analyze the intrinsic attributes of movie shots, such as movement and scale. In previous methods, specialized architectures were designed for each specific task and relied on the use of optical flow maps. In...
Counterfactual reasoning explores what could have happened if the circumstances were different from what actually occurred. As a crucial subtask, counterfactual story generation integrates counterfactual reasoning into the generative narrative chain,...
In this study, a novel intelligent inverter fault diagnosis approach based on a stacked denoising autoencoder–generative adversarial network–long short-term memory (SDAE-GAN-LSTM) under an imbalanced sample is proposed for a three-phase p...
A network intrusion detection tool can identify and detect potential malicious activities or attacks by monitoring network traffic and system logs. The data within intrusion detection networks possesses characteristics that include a high degree of f...
Knowledge tracing (KT) aims to trace a learner’s understanding or achievement of knowledge based on learning history. The surge in online learning systems has intensified the necessity for automated measurement of students’ knowledge stat...
Road instance segmentation is vital for autonomous driving, yet the current algorithms struggle in complex city environments, with issues like poor small object segmentation, low-quality mask edge contours, slow processing, and limited model adaptabi...
This paper provides a clear demonstration that a coplanar stripline (CPS) as a balanced line can act to re-establish the phase balance in the presence of phase deviation from a 180° distance between two input signal lines connected to the CPS. A...
The vehicle routing problem (VRP) is a common problem in logistics and transportation with high application value. In the past, many methods have been proposed to solve the vehicle routing problem and achieved good results, but with the development o...
Water electrolysis is a clean, non-polluting way of producing hydrogen that has seen rapid development in recent years. It offers the possibility of resolving the issue of excessive carbon emissions in conventional hydrogen production methods. In add...
The technologies of undersea detection and communication, seabed sensor networks, and geophysical detection using electromagnetic waves have emerged as research focal points within the field of marine science and engineering. However, most studies ha...
This paper presents the design and performance analysis of a wideband charge-pump phase-locked loop (CPPLL) characterized by low reference spur and low phase noise. The proposed CPPLL, operating as a wideband phase-locked loop (PLL) with a reference...
A one-dimensional mono-pulse microstrip antenna plays an important role in target detection, tracking, recognition and imaging. However, feeding and coupling are the main reasons for the large size of the mono-pulse antenna, which is not conducive to...
In this study, we propose a hybrid model for Perspective-n-Point (PnP)-based 6D object pose estimation called FusionNet that takes advantage of convolutional neural networks (CNN) and Transformers. CNN is an effective and potential tool for feature e...
The fast and accurate detection of steel surface defects has become an important goal of research in various fields. As one of the most important and effective methods of detecting steel surface defects, the successive generations of YOLO algorithms...
Studies have shown that in today’s urban areas, drivers lose a significant amount of time searching for available on-street parking spaces. Cruising drivers cause numerous problems, such as wasting gasoline and emitting gasses that lead to air...
The Frangi neuron proposed in this work is a complex element that allows high-level Hessian-based image processing. Its adaptive parameters (weights) can be trained using a minimum number of training data. In our experiment, we showed that just one i...
Anomaly-based intrusion detection systems identify the computer network behavior which deviates from the statistical model of typical network behavior. Binary classifiers based on supervised machine learning are very accurate at classifying network d...
The aim of this paper is to introduce the public to the virtual depot of the Gallery of Matica Srpska (GMS), which showcases a collection of sculptures that have been digitized using a Structure-from-Motion photogrammetry and presented by the use of...
We propose a single-pole double-throw (SPDT) switch with low insertion loss (IL), high isolation, and high linearity for a 28 GHz 5G new radio. The transmit (TX) path is a π-network consisting of a parallel dynamic-threshold metal–oxide&ndas...
The subject of this study is steganographic systems that are able to hide not only the content of the transmitted information but also the fact of its transmission. In this paper, we present a novel data transmission model within such systems, combin...
Topologically associated domains (TADs) represent essential units constituting chromatin’s intricate three-dimensional spatial organization. TADs are stably present across cell types and species, and their influence on vital biological processe...
This research addresses the issue of evaluating CPU rendering performance by introducing the innovative benchmark test suite construction method RenderBench. This method combines CPU microarchitecture features with rendering task characteristics to c...
Frequency deviations and the capability to cope with demand are two of the main problems in isolated or interconnected microgrids, especially with the increase in the penetration level of renewable energy sources. Those two problems call for new impr...
Automation and robotics are destined to play a critical role in the Industry 4.0 revolution, as illustrated by the emergence of autonomous machinery in earthwork operations. Despite rapid progress, autonomous agents will always require human supervis...
Indoor positioning is a core enabler for various 5G identity and context-aware applications requiring precise and real-time simultaneous localisation and mapping (SLAM). In this work, we propose a K-nearest neighbours and deep neural network (K-DNN)...
The importance of electric vehicle charging stations (EVCS) is increasing as electric vehicles (EV) become more widely used. EVCS with multiple low-carbon energy sources can promote sustainable energy development. This paper presents an optimization...
Obstructive Sleep Apnea–Hypopnea Syndrome (OSAHS), a severe respiratory sleep disorder, presents a significant threat to human health and even endangers life. As snoring is the most noticeable symptom of OSAHS, identifying OSAHS via snoring sou...
The development of brain-inspired spiking neural networks (SNNs) has great potential for neuromorphic edge computing applications, while challenges remain in optimizing power-efficiency and silicon utilization. Neurons, synapses and spike-based learn...
Recent technological advances have enabled the development of sophisticated robotic and sensor systems monitored and controlled by algorithms based on computational intelligence. The deeply intertwined and cooperating devices connected to the Interne...
Induction heating (IH) technology is widely recognized and utilized in residential applications due to its high efficiency and safe operating characteristics. Resonant inverter circuits are widely used in IH systems because of their high efficiency a...
The use of artificial intelligence has shown good performance in the medical imaging area, in particular the deep learning methods based on convolutional neural networks for classification, detection, and/or segmentation tasks. The task addressed in...
Systems for sustainable development are built on three pillars: economic development, environmental stewardship, and social value [...]
The rapid growth of the Internet of Things (IoT) in smart buildings necessitates the continuous evaluation of potential threats and their implications. Conventional methods are increasingly inadequate in measuring risk and mitigating associated hazar...
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Visual object tracking poses challenges due to deformation of target object appearance, fast motion, brightness change, blocking due to obstacles, etc. In this paper, a Siamese network that is configured using a convolutional neural network is propos...
A recent development in marketing tools aimed at boosting sales involves the use of three-dimensional pattern films. These films are designed to captivate customers’ interest by applying 3D patterns to the surface of products. However, ensuring...
Utilizing neural network models to inverse time-domain electromagnetic signals enables rapid acquisition of electrical structures, a non-intrusive method widely applied in geological and environmental surveys. However, traditional multi-layer percept...
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