Jinping Liu

Hunan Normal University · College of Information Science and Engineering

Water is a vital resource essential to the survival and development of all creatures. With the rapid growth of industry and agriculture, people face a severe threat of ecological destruction and environmental pollution while living earthly lives. Water pollution, in particular, harms people’s health the most. As a result, water supply security has...

While deep learning has advanced significantly in machinery diagnosis, models trained on source domain data struggle with real-world applications due to varying operating conditions in the target domain. To address this, we propose a novel solution, the Global Receptive Field-based Graph Attention Network (GRF-GAT), for the fault diagnosis of varyi...

Accurate segmentation of coronavirus disease 2019 (COVID-19)-infected lung areas from chest CT scans is critical for COVID-19 diagnosis and prognosis evaluations. However, current mainstream 2D slice-wise segmentation models fail to fully utilize 3D volumetric context across slices, leading to inaccurate segmentation results. Although 3D segmentati...

The traditional domain adaptation method for fault diagnosis of axial fans faces two main problems: (1) source domain moves to target domain makes the source feature distribution changed; (2) the narrow decision boundary of source domain features leads to misclassification of target samples. Therefore, a multi-source subdomain adaption fault diagno...

The tailings grade is a crucial indicator for controlling and optimizing mineral flotation processes. However, detecting/predicting tailings grade online faces challenges due to intricate physicochemical reactions in threephase slurries with the strongly-coupled characteristics of the technical process. This paper introduces a novel multi-source fe...

Hail, an intense convective catastrophic weather, is seriously hazardous to people’s lives and properties. This article proposes a multi-step cyclone hail weather recognition model, called long short-term memory (LSTM)-C3D, based on radar images, integrating attention mechanism and network voting optimization characteristics to achieve intelligent...

Path‐tracking and lane‐keeping efficiency of driverless cars remain critical characteristics of the efficient and safe deployment of such vehicles in future intelligent transportation systems. This study introduces a robust type‐3 (T3) fuzzy controller implementation for the path‐tracking task of driverless cars during critical driving conditions a...

It is well known that the permanent magnet synchronous motor (PMSM) exhibits chaotic characteristics when its parameters fall within a certain range, which can lead to system instability. This article proposes an adaptive control strategy for achieving the fixed-time chaotic stabilization of PMSM, even in the presence of unknown parameters and pert...

Cardiovascular diseases are the leading cause of mortality, and accurate segmentation of ventricular regions in cardiac magnetic resonance images (MRIs) is crucial for diagnosing and treating these diseases. However, fully automated and accurate right ventricle (RV) segmentation remains challenging due to the irregular cavities with ambiguous bound...

To effectively improve the power dispatching, the prediction accuracy of wind power has been the concern of many scholars for many years. The wind power prediction problem is actually equivalent to the wind speed prediction problem. Based on linear regression (LR) and variational mode decomposition (VMD), in this paper, we proposed an efficient hyb...

Visual Question Answering (VQA) is a multimodal task, which requires understanding the information in the natural language questions and paying attention to the useful information in the images. So far, the solution of VQA tasks can be divided into grid-based methods and bottom-up-based methods. The grid-based method directly extracts the semantic...

The quality and ratio of clinker, the fineness of cement are key factors affecting the strength of cement. In order to realize the target tracking control of cement strength, a self-learning fuzzy predictive control algorithm is proposed to calculate the adjustment variables of cement grinding process Considering the serious hysteresis of cement st...

COVID-19 is a dangerous disease that directly damages human health, with the properties of severely contagious and highly variable. It is endangering the health and safety of people all around the world. Thus, it compels governments to seek rapid detection, diagnosis and treatment, and epidemic forecasting approaches under the consumption of consid...

Laminar cooling roller motor (LCRM) is the main driving equipment of laminar cooling section (LCS) in a steelmaking plant. To promote an intelligent upgrade of the safe management and operation of LCRMs, a novel fault diagnosis method based on the morphological recognition and combination pattern mining of LCRM’s multi-current signatures is propose...

In the field of cardiac magnetic resonance (MR) image analysis, the accurate segmentation of right ventricle (RV) regions plays an important role in the quantitative examination and medical diagnosis of various cardiovascular diseases. However, the automated RV segmentation in cardiac MR images is still challenging, due to its obscure and ill-defin...

Robust industrial process monitoring is crucial to ensure production safety and product quality stability. However, the process monitoring of high-dimensional, nonlinear, complex industrial processes is still challenging due to their inherent complexities, such as multi-phase, multi-field, and tight coupling of multiple sub-processes. In this artic...

Anecdotal experiences show that the human perception of time is subjective, and changes with one's emotional state. Over the past 25 years, increasing empirical evidence has demonstrated that emotions distort time perception and usually result in overestimation. Yet, some inconsistencies deserve clarification. Specifically, it remains controversial...

The chaotic systems have extensive applications in various branches of engineering problems such as financial problems, image processing, secure communications, and medical problems, among many others. In most applications, a synchronization needs to be made with another favorite chaotic system, or output trajectories track the desired signal. The...

The rise of artificial intelligence has revolutionized all aspects of today's life. Neural networks, which are a stepping stone in the search for artificial intelligence, considerably affect the pace of advances in this field. Therefore, developing trustable tools for their modeling and control is of crucial importance. Motivated by this, we propos...

The accurate segmentation of blood vessels plays a crucial role in screening, diagnosis and treatment of multiple diseases. However, current automated segmentation approaches do not pay enough attention to the vascular topology errors (such as mistaking vessel‐breakpoints), resulting in considerable scattered vessel‐fragments in segmentation result...

Fault monitoring plays a vital role in ensuring operating safety and product quality of industrial manufacturing processes. However, modern industrial processes are generally developing towards the direction of large scale, diversification, and individuation, complexity, and refinement, exhibiting strong non-linearity and dynamically time-varying c...

Flotation froth image deblurring is of great significance to research on zinc flotation working condition recognition and fault diagnosis. A blurry froth image includes not only the air–water fogs and dust produced in industrial sites, but also motion blur caused by camera vibrations. However, due to the redundancy and complexity of froth images, o...

This paper aims at analyzing the dynamical behavior of a SIR hepatitis B epidemic stochastic model via a novel approach by incorporating the effect of information interventions and random perturbations. Initially, we demonstrate the positivity and global existence of the solutions. Afterward, we derive the stochastic threshold parameter Rs, followe...

Novelty detection (ND) is a crucial task in machine learning to identify anomalies in the test data in some respects different from the training data. As an anomaly detection method, novelty detection only uses normal samples for model learning, which can well fit most of the natural scenes that the amount of abnormal samples is in fact strongly in...

Due to technical or economic limitations, timely measuring quality-relevant key performance indicators (KPIs) of complex industrial processes (CIPs), especially the chemical composition-related indexes, is intractable. Process monitoring image sequences (PMISs) usually involve significant information about the operation states and KPIs. Thus, soft...

The Selkov system, which is typically employed to model glycolysis phenomena, unveils some rich dynamics and some other complex formations in biochemical reactions. In the present work, the synchronization problem of the glycolysis reaction-diffusion model is handled and examined. In addition, a novel convenient control law is designed in a linear...

Identifying parameters of financial and economic models with chaotic dynamics is an important, yet daunting challenge because of the complexities there exist in these chaotic systems. Although several studies have been devoted to understanding the mechanism of financial systems, the application of most state-of-the-art methods to these systems is c...

This article proposes a robust end-to-end deep learning-induced fault recognition scheme by stacking multiple sparse-denoising autoencoders with a Softmax classifier, called stacked spare-denoising autoencoder (SSDAE)-Softmax, for the fault identification of complex industrial processes (CIPs). Specifically, sparse denoising autoencoder (SDAE) is e...

The role of brain regions in the relationship between psychological stress and sleep quality is unclear. This study investigates the neuroanatomical basis of the association between psychological stress and sleep quality. Data were collected using the Pittsburgh Sleep Quality Index, the Psychosomatic Tension Relaxation Inventory, and voxel-based mo...

Machine-vision-based defect detection, instead of manual visual inspection, is becoming increasingly popular. In practice, images of the upper surface of cableway load sealing steel wire ropes are seriously affected by complex environments, including factors such as lubricants, adhering dust, natural light, reflections from metal or oil stains, and...

Little is known about the electrophysiological basis of the effect of threat-related emotional stimuli with different motivational direction on duration perception. Thus, event-related potentials were employed to examine the effects of angry expressions and fearful expressions on perception of different duration (490–910 ms). Behavioral results sho...

Accurate cardiac segmentation of multimodal images, e.g., magnetic resonance (MR), computed tomography (CT) images, plays a pivot role in auxiliary diagnoses, treatments and postoperative assessments of cardiovascular diseases. However, training a well-behaved segmentation model for the cross-modal cardiac image analysis is challenging, due to thei...

Although most of the early research studies on fractional-order systems were based on the Caputo or Riemann–Liouville fractional-order derivatives, it has recently been proven that these methods have some drawbacks. For instance, kernels of these methods have a singularity that occurs at the endpoint of an interval of definition. Thus, to overcome...

This paper proposes a moving window recursive sparse principal component analysis (MWRSPCA)-based online fault monitoring scheme, aim at providing an online fault monitoring solution for large-scale complex industrial processes (e.g., chemical industry processes) with time-varying and dynamically changing characteristics. It establishes a sparse pr...

This paper presents a simple yet powerful online flotation process working condition (FPWC) discrimination approach based on the sparse representation of froth images. It learns a local Gabor pattern-based discriminative dictionary with a linear classification model simultaneously for the FPWC identification by solving a sparsity-constrained optimi...

This paper proposes an online bubble size distribution (BSD) monitoring scheme by incorporating a multiscale deblurring full convolutional network (MsD) and a multistage jumping feature-fused full convolutional network (MsJ), having the potential of online identification of the health state of flotation process operations. MsD can restore blurry fr...

In complex industrial processes (CIPs), due to technical and economic limitations, key performance indicators (KPIs), especially the chemical content-related KPIs, are often difficult to measure in real time, which hinders the propagation of advanced process control technologies. This paper presents a soft sensor-based online KPI inference scheme b...

Industrial Cyber-physical systems (ICPSs), integrating communication, computation and control of industrial processes are referred to as a core technology to approach the Industry 4.0. Ensuring the ICPS security is of paramount importance in smart manufacturing. Considering the characteristics of large-scale, geographically-dispersed and multi-dime...

It is well known that the change of the reagent dosage during the flotation process will cause the froth image to change continuously with time. Therefore, an intelligent setting method based on the time series froth image in the zinc flotation process is proposed. Firstly, the sigmoid kernel function is used to estimate the cumulative distribution...

Accurate segmentation of brain tumors from magnetic resonance (MR) images play a pivot role in assisting diagnoses, treatments and postoperative evaluations. However, due to its structural complexities, e.g., fuzzy tumor boundaries with irregular shapes, accurate 3D brain tumor delineation is challenging. In this paper, an intersection over union (...

Froth color can be referred to as a direct and instant indicator to the key flotation production index, for example, concentrate grade. However, it is intractable to measure the froth color robustly due to the adverse interference of time-varying and uncontrollable multisource illuminations in the flotation process monitoring. In this article, we p...

Edge-relevant structure features (ERSFs), e.g., object edges, boundaries and contours, junctions, etc. play an important role in low and middle level image processing tasks, such as image segmentation, as well as in higher-level computer vision tasks, such as scene analysis and content understanding. Commonly-used ERSF detection methods employ the...

Automatic texture pattern classification (ATPC) has long been an essential issue in computer vision. However, ATPC is still a challenging task since texture is a subjective conception, which is difficult to be expressed concisely by the existing computational models. The visual appearance of the imaged texture pattern (TP) visually depends on the r...

This paper presents a froth image statistical modeling-based online flotation process operation-state identification method by introducing a biologically inspired Gabor wavelet transform in accordance with the physiological findings in the biological vision system. It derived the latent probabilistic density models of these biologically inspired Ga...

This paper presents an adaptive network intrusion detection (ANID) method based on the selective ensemble of kernel extreme learning machines (KELMs) with random features (termed ANID-SEoKELM), aiming at identifying various unauthorized uses, misuses and abuses of computer systems in real time. To generate a lightweight intrusion detector, multiple...

With the increasing diversity and rapid variability of network intrusion, the development of real-time network security monitoring systems with high flexibility and strong adaptability still faces severe challenges. Therefore adaptive network intrusion detection (ANID) method based on fuzzy rough set attribute reduction (FRS-AR) and Gaussian mixtur...

h i g h l i g h t s • A selective ensemble of KELMs-based intrusion detection method is proposed. • The KELM is introduced for the lightweight base classifier learning. • Random projection is adopted for the feature representation of network instances. • An incremental-learning-based online KELM updating approach is derived. • A margin distance min...

Texture pattern classification has long been an essential issue in computer vision (CV). However, texture is a kind of perceptual concept of human beings in scene observation or content understanding, which cannot be defined or described clearly in CV. Visually, the visual appearance of the complex spatial structure (CSS) of texture pattern (TP) ge...

This paper presents an image statistical modeling-based texture classification (TC) approach via Bayesian-driven B-splines probability density estimation of the image textural surface appearance (ITSA), termed TCvBsISM. It approximates the probability density functions (PDFs) of the marginal distribution and joint distribution, involving the global...

The surface texture of mineral flotation froth is well acknowledged as an important index of the flotation process. The surface texture feature closely relates to the flotation working conditions and hence can be used as a visual indicator for the zinc fast roughing working condition. A novel working condition identification method based on the dua...

A B-spline probability density function (PDF) estimation-based texture image identification method is presented in this work, which can be categorized into three processing phases, including PDF feature dictionary learning phase, PDF feature representation phase and texture identification phase.In the PDF feature dictionary learning and feature rep...

Automated visual inspection (AVI) attracts increasing interest in product quality control both academic and industrial communities, particularly on mass production processes, because product qualities of most types can be characterized with their corresponding surface visual attributes. However, many product images in AVI systems are comprised of s...

A kind of interactive image segmentation method based on ensemble multi-classifiers is put forward to solve the problem of unsatisfactory segmentation results based on scarce or unbalanced labelling labels on different object areas by single learner. The first classifier is established based on multivariate adaptive regression splines (MARS) method...

The topic of online product quality inspection (OPQI) with smart visual sensors is attracting increasing interest in both the academic and industrial communities on account of the natural connection between the visual appearance of products with their underlying qualities. Visual images captured from granulated products (GPs), e.g., cereal products...

Computer vision as a fast, low-cost, noncontact, and online monitoring technology has been an important tool to inspect product quality, particularly on a large-scale assembly production line. However, the current industrial vision system is far from satisfactory in the intelligent perception of complex grain images, comprising a large number of lo...

Grain image I for image statistical modeling by WD model. (PPTX)

Image statistical modeling resultsof Grain image I by WD model. (XLSX)

A combined fuzzy based feedforward (FBF) and bubble size distribution (BSD) based feedback reagent dosage control strategy is proposed to implement the product indices in copper roughing process. A fuzzy theory based feedforward compensator will be used to calculated the reagent dosage in advance to eliminate the influence of large disturbances acc...