Yudong Zhang

University of Leicester | LE · School of Computing and Mathematical Sciences

According to the World Health Organization statistics, as of 25 October 2022, there have been 625,248,843 confirmed cases of COVID-19, including 65,622,281 deaths worldwide. The spread and severity of COVID-19 are alarming. The economy and life of countries worldwide have been greatly affected. The rapid and accurate diagnosis of COVID-19 directly...

Problems: For people all over the world, cancer is one of the most feared diseases. Cancer is one of the major obstacles to improving life expectancy in countries around the world and one of the biggest causes of death before the age of 70 in 112 countries. Among all kinds of cancers, breast cancer is the most common cancer for women. The data sho...

This paper proposes applying a novel deep‐learning model, TBDLNet, to recognize CT images to classify multidrug‐resistant and drug‐sensitive tuberculosis automatically. The pre‐trained ResNet50 is selected to extract features. Three randomized neural networks are used to alleviate the overfitting problem. The ensemble of three RNNs is applied to bo...

The widespread presence of explicit content on social media platforms has far-reaching consequences for individuals, relationships, and society as a whole. It is crucial to tackle this problem by implementing efficient content moderation, educating users, and creating technologies and policies that foster a more secure and wholesome online atmosphe...

Mathematical modeling, geared towards describing different aspects of the real world, reciprocal interactions and dynamics thereof through mathematics, must be able to address universal concepts, which makes mathematical models unique as they, on their own, allow for the mechanization and automation of intellectual activity. The mathematical model b...

Since 2019, the coronavirus disease-19 (COVID-19) has been spreading rapidly worldwide, posing an unignorable threat to the global economy and human health. It is a disease caused by severe acute respiratory syndrome coronavirus 2, a single-stranded RNA virus of the genus Betacoronavirus. This virus is highly infectious and relies on its angiotensi...

Real-time monitoring of rock stability during the mining process is critical. This paper first proposed a RIME algorithm (CCRIME) based on vertical and horizontal crossover search strategies to improve the quality of the solutions obtained by the RIME algorithm and further enhance its search capabilities. Then, by constructing a binary version of C...

Supply chain collaboration is acknowledged for its benefits, but realizing these advantages can be challenging. The role of government subsidies in supply chain collaboration, collaborative advantage, and firm performance remains unclear. In this study, we explored how supply chain collaboration can enhance firm performance and the roles of collabo...

Covid-19 is a kind of fast-spreading pneumonia and has dramatically impacted human life and the economy. As early diagnosis is the most effective method to treat patients and block virus transmission, an accurate, automatic, and effective diagnosis method is needed. Our research proposes a machine learning model (WE-BA) using wavelet entropy for fe...

This paper studies the performance for the proactive eavesdropping-based legitimate surveillance for the integrated satellite-terrestrial relay networks in the presence of several monitors. To investigate the proactive eavesdropping performance, we propose three different presentative proactive eavesdropping cases/modes. In these cases, the monitor...

Complex and nonlinear dynamic models are characterized by intricate attributes like high dimensionality and heterogeneity, having fractional-order derivatives and constituting fractional calculus, which brings forth a thorough comprehension, control and optimization of the related dynamics and structure. This requirement, posing a daunting challeng...

Image segmentation methods have received widespread attention in face image recognition, which can divide each pixel in the image into different regions and effectively distinguish the face region from the background for further recognition. Threshold segmentation, a common image segmentation method, suffers from the problem that the computational...

The purpose of this study is to investigate whether there are differences in handwritten Chinese signatures on different media including paper and electronic devices. Participants were asked to sign specified names on various types of media and the signatures were scanned or saved digitally for subsequent analysis. In this study, using convolutiona...

RBEBT: A ResNet-Based BA-ELM for Brain Tumor Classification

The Hunger Games Search (HGS) is an innovative optimizer that operates without relying on gradients and utilizes a population-based approach. It draws inspiration from the collaborative foraging activities observed in social animals in their natural habitats. However, despite its notable strengths, HGS is subject to limitations, including inadequat...

Artificial intelligence (AI) allows computers to think and behave like humans, so it is now becoming more and more influential in almost every field. Hence, users in businesses, industries, hospitals, etc., need to understand how these AI models work and the potential impact of using them

In recent times, DFU (diabetic foot ulcer) has become a universal health problem that affects many diabetes patients severely. DFU requires immediate proper treatment to avert amputation. Clinical examination of DFU is a tedious process and complex in nature. Concurrently, DL (deep learning) methodologies can show prominent outcomes in the classifi...

For multi-focus image fusion, the existing deep learning based methods cannot effectively learn the texture features and semantic information of the source image to generate high-quality fused images. Thus, we develop a new adaptive feature concatenate attention network named AFCANet, which adaptively learns cross-layer features and retains the tex...

Facial expression recognition has become a hot issue in the field of artificial intelligence. So, we collect literature on facial expression recognition. First, methods based on machine learning are introduced in detail, which include image preprocessing, feature extraction, and image classification. Then, we review deep learning methods in detail:...

Cutting-edge developments in machine learning and deep learning are improving all aspects of cancer research and treatment. Nowadays, the applications of artificial intelligence, machine learning, and deep learning to clinical aspects of cancer research have received more attention from scholars, with particular emphasis on diagnosis, prognosis, de...

Cell counting and segmentation are critical tasks in biology and medicine. The traditional methods for cell counting are labor‐intensive, time‐consuming, and prone to human errors. Recently, deep learning‐based cell counting methods have become a trend, including point‐based counting methods, such as cell detection and cell density prediction, and...

Deep ensemble learning, where we combine knowledge learned from multiple individual neural networks, has been widely adopted to improve the performance of neural networks in deep learning. This field can be encompassed by committee learning, which includes the construction of neural network cascades. This study focuses on the high-dimensional low-s...

The slime mould algorithm (SMA) is a population-based swarm intelligence optimization algorithm that simulates the oscillatory foraging behavior of slime moulds. To overcome its drawbacks of slow convergence speed and premature convergence, this paper proposes an improved algorithm named PSMADE, which integrates the differential evolution algorithm...

In the global epidemic, distance learning occupies an increasingly important place in teaching and learning because of its great potential. This paper proposes a web-based app that includes a proposed 8-layered lightweight, customized convolutional neural network (LCCNN) for COVID-19 recognition. Five-channel data augmentation is proposed and used...

Due to buildings blocking GPS and Wi-Fi signals, traditional techniques can’t offer the user’s required positioning accuracy in resource-constrained underground parking, but the cooperation of agent nodes can provide the exact localization information to improve the positioning accuracy. However, some well-localized agents may not be willing to sac...

Deep learning has shown a huge interest in computer vision in the last few years, especially for the application of medical imaging. In medical imaging, deep learning is employed for detecting and classifying cancers such as skin cancer, stomach cancer, brain tumor, and a few more. Dermoscopy, wireless capsule endoscopy, and MRI imaging technologie...

In recent years, cellular communication systems have continued to develop in the direction of intelligence. The demand for cellular networks is increasing as they meet the public’s pursuit of a better life. Accurate prediction of cellular network traffic can help operators avoid wasting resources and improve management efficiency. Traditional predi...

Artificial intelligence (AI) refers to the field of computer science theory and technology [1] that is focused on creating intelligent machines capable of simulating human intelligence [2]. AI systems [3] are designed to perform tasks that typically require human intelligence [4], such as perception, learning, reasoning [5], problem-solving [6], de...

Background: Medical data mining is an important research direction in the data mining field and has always been a research hotspot in the computer and medical fields for many years. Data mining algorithms usually assume that the sample distribution of data is balanced and the misclassification cost is equal. However, due to the characteristics of m...

COVID-19 has caused over 6.35 million deaths and over 555 million confirmed cases till 11/July/2022. It has caused a serious impact on individual health, social and economic activities, and other aspects. Based on the gray-level co-occurrence matrix (GLCM), a four-direction varying-distance GLCM (FDVD-GLCM) is presented. Afterward, a five-property...

(1) Background: The application of deep learning technology to realize cancer diagnosis based on medical images is one of the research hotspots in the field of artificial intelligence and computer vision. Due to the rapid development of deep learning methods, cancer diagnosis requires very high accuracy and timeliness as well as the inherent partic...

Aim) COVID-19 has triggered 6.42 million death tolls, and more than 586 million confirmed positive cases until 10/Aug/2022. CT-based diagnosis methods need special expert knowledge, and the labeling procedure is tedious. (Methods) We first propose a 12-layer CNN-based backbone network. Then, we utilize the Swish activation function to replace tradi...

Amongst all types of cancer, breast cancer has become one of the most common cancers in the UK threatening millions of people’s health. Early detection of breast cancer plays a key role in timely treatment for morbidity reduction. Compared to biopsy, which takes tissues from the lesion for further analysis, image-based methods are less time-consumi...

According to the World Health Organisation, falling is a major health problem with potentially fatal implications. Each year, thousands of people die as a result of falls, with seniors making up 80% of these fatalities. The automatic detection of falls may reduce the severity of the consequences. Our study focuses on developing a vision-based fall...

Automatic brain tumour segmentation in MRI scans aims to separate the brain tumour's endoscopic core, edema, non‐enhancing tumour core, peritumoral edema, and enhancing tumour core from three‐dimensional MR voxels. Due to the wide range of brain tumour intensity, shape, location, and size, it is challenging to segment these regions automatically. U...

This editorial presents the recent advances and challenges of deep learning. We reviewed four main challenges: heterogeneity, copious size, reproducibility crisis, and explainability. Finally, we present the prospect of deep learning in industrial applications.

Since the COVID-19 pandemic outbreak, over 760 million confirmed cases and over 6.8 million deaths have been reported globally, according to the World Health Organization. While the SARS-CoV-2 virus carried by COVID-19 patients can be identified though the reverse transcription–polymerase chain reaction (RT-PCR) test with high accuracy, clinical mi...

INTRODUCTION: In scalable information systems, edge computing can help to overcome the challenges of latency, bandwidth, and connectivity in large-scale networks by reducing the amount of data that needs to be transmitted over the network. OBJECTIVES: The edge devices, such as sensors, cameras, gateways, routers, switches, multiplexers, integrated...

Recently, swarm intelligence algorithms have received much attention because of their flexibility for solving complex problems in the real world. Recently, a new algorithm called the colony predation algorithm (CPA) has been proposed, taking inspiration from the predatory habits of groups in nature. However, CPA suffers from poor exploratory abilit...

This message is from the Editorial Office of the journal BIOCELL. We would like to bring your attention to an article that was published in 2023 and has been included in the list of highly cited papers and hot papers. We kindly request you to take a moment to read it. Abstract Since 2019, the coronavirus disease-19 (COVID-19) has been spreading rap...

The rapidly spreading COVID-19 disease had already infected more than 190 countries. As a result of this scenario, nations everywhere monitored confirmed cases of infection, cures, and fatalities and made predictions about what the future would hold. In the event of a pandemic, governments had set limit rules for the spread of the virus and save li...

As a hearing disorder, sensorineural hearing loss (SNHL) can be effectively detected by magnetic resonance imaging (MRI). However, the manual detection of MRI scanning is subjective, time‐consuming, and unpredictable. An accurate and automatic computer‐aided diagnosis system is proposed for SNHL detection, providing reliable references for professi...

Counting high-density objects quickly and accurately is a popular area of research. Crowd counting has significant social and economic value and is a major focus in artificial intelligence. Despite many advancements in this field, many of them are not widely known, especially in terms of research data. The authors proposed a three-tier standardised...

The outbreak of the corona virus disease (COVID-19) has changed the lives of most people on Earth. Given the high prevalence of this disease, its correct diagnosis in order to quarantine patients is of the utmost importance in the steps of fighting this pandemic. Among the various modalities used for diagnosis, medical imaging, especially computed...

In this paper, the novelty of scalable coding of encrypted images (S.C.E.I) using Block Truncation Code (BTC) for different non-overlapping block sizes is investigated. Initially, the original content of the image of size 512 × 512 is split into different non-overlapping block (N.O.B.) sizes of 2 × 2, 4 × 4, 8 × 8 and 16 × 16. Then each N.O.B. size...

The emerging field of the Internet of Vehicles (IoV) has garnered significant attention due to its potential to revolutionize transportation and mobility. IoV enables the development of innovative services and applications that can enhance the efficiency, safety, and sustainability of transportation systems. However, ensuring secure and reliable co...

Alzheimer’s and related diseases are significant health issues of this era. The interdisciplinary use of deep learning in this field has shown great promise and gathered considerable interest. This paper surveys deep learning literature related to Alzheimer’s disease, mild cognitive impairment, and related diseases from 2010 to early 2023. We ident...

COVID-19 is a vastly infectious disease caused by the new coronavirus, officially recognized as severe acute respiratory syndrome coronavirus 2. This virus has multiplied fast worldwide, causing a global pandemic. It has caused 6.87 million death tolls until 20/March/2023.

In this paper, a new sparsity‐optimised Farrow structure variable fractional delay (SFS‐VFD) filter is proposed to address the aperture effect in wideband array. Our method is based on coefficient (anti‐)symmetry and optimises the number and orders of its sub‐filters, greatly reducing the non‐zero coefficients. The established cost function is form...

The field of position tracking control and communication engineering has been increasingly interested in time-varying quadratic minimization (TVQM). While traditional zeroing neural network (ZNN) models have been effective in solving TVQM problems, they have limitations in adapting their convergence rate to the commonly used convex activation funct...

Alzheimer's disease (AD) is a terrible and degenerative disease commonly occurring in the elderly. Early detection can prevent patients from further damage, which is crucial in treating AD. Over the past few decades, it has been demonstrated that neuroimaging can be a critical diagnostic tool for AD, and the feature fusion of different neuroimaging...

We propose a two-stage deep residual attention generative adversarial network (TSDRAGAN) for inpainting iris textures obscured by eyelids. This two-stage generation approach ensures that the semantic and texture information of the generated images is preserved. In the second stage of the fine network, a modified residual block (MRB) is used to furt...

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 requires much time for manual analysis. The recent advances in computer vision can be beneficial to free d...

Speech emotion recognition (SER) is an important research problem in human‐computer interaction systems. The representation and extraction of features are significant challenges in SER systems. Despite the promising results of recent studies, they generally do not leverage progressive fusion techniques for effective feature representation and incre...

In recent years, optical imaging techniques have gained wide recognition for the measurement of vital signals, such as heart rate, respiratory rate, oxygen saturation, and blood pressure, which are crucial indicators for evaluating human health conditions in clinical examinations. There is a wide range of optical imaging methods for remote physiolo...

Bionic artificial neural networks (BANNs) are a type of artificial neural network (ANN) that draw inspiration from the biological neural networks in living organisms, such as the brain and the nervous system.

With the Internet of Vehicles (IOV), a lot of self-driving vehicles (SDVs) need to handle a variety of tasks but have very seriously limited computing and storage resources, meaning they cannot complete intensive tasks timely. In this paper, a joint edge computing and caching based on a Dueling Double Deep Q Network (D3QN) is proposed to solve the...

Effective connectivity can describe the causal patterns among brain regions. These patterns have the potential to reveal the pathological mechanism and promote early diagnosis and effective drug development for cognitive disease. However, the current studies mainly focus on using empirical functional time series to calculate effective connections,...