# Jing He's research while affiliated with University of Oxford and other places

## Publications (186)

Article
Traditional privacy-preserving technologies have been unable to provide adequate protection and are vulnerable to background knowledge. MapReduce is parallel distributed computing model which has the advantages of good scalability and high fault tolerance. In this paper, we design a differential privacy protection based on MapReduce for the securit...
Article
Graph distance is also named approximate graph isomorphism, error-tolerant graph matching, it is a measure of similarity (or dissimilarity) between two graphs. The graph distance function is an elusive question remaining a pressing problem in a wide range of fields. In general, graphs are usually enriched with node and edge attributes, namely, hete...
Article
Compared with relatively easy feature creation or generation in data analysis, manual data labelling needs a lot of time and effort in most cases. Even if automated data labelling seems to make it better in some cases, the labelling results still need to be checked and verified by manual. The High Dimension and Low Sample Size (HDLSS) data are ther...
Article
Mitochondrial dysfunction has been regarded as a hallmark of diabetic cardiomyopathy. In addition to their canonical metabolic actions, mitochondria influence various other aspects of cardiomyocyte function, including oxidative stress, iron regulation, metabolic reprogramming, intracellular signaling transduction and cell death. These effects depen...
Article
In diabetic cardiomyopathy (DCM), a major diabetic complication, the myocardium is structurally and functionally altered without evidence of coronary artery disease, hypertension or valvular disease. Although numerous anti-diabetic drugs have been applied clinically, specific medicines to prevent DCM progression are unavailable, so the prognosis of...
Article
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Objectives Dual specificity phosphatase 1 (DUSP1) is regarded as an anti-inflammatory factor in cardiovascular disorders. Mitophagy removes damaged mitochondria and thus promotes mitochondrial regeneration. We investigated whether DUSP1 could attenuate inflammation-induced cardiomyopathy by improving mitophagy. Methods Lipopolysaccharide was used...
Article
When dealing with complex and redundant data classification problems, many classifiers cannot provide high predictive accuracy and interpretability. We also find that the least-squares support vector classifiers (LSSVCs) hardly identify important instances and features from data, so they cannot give an interpretable prediction. Although the LSSVC h...
Article
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Fuzzy association rule mining (FARM) is a mainstream method to discover hidden patterns and association rules in quantitative data. It is essential to improve performance metrics, including quantity performance (e.g., the number of rules, the number of frequent itemsets) and quality performance (e.g., fuzzy support and confidence). The current appr...
Article
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Data intelligence is the core task of the information revolution entering the Internet era. It brings opportunities, but also makes human civilization face risks. Data drowns the idea and data is supreme. People regard manufacturing data as the goal of digital economy, stook data up hoarding and turn data into an immortal holy thing, which is very...
Article
QoS‐aware based web service recommendation is one of the crucial solutions to help users find high‐quality web services. To accurately predict the QoS values of candidate services, it is usually required to collect historical QoS data of users (QoS data for short). If these collected QoS data are improperly processed, QoS data privacy may be threat...
Article
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Convex optimization techniques are extensively applied to various models, algorithms, and applications of machine learning and data mining. For optimization-based classification methods, the sparsity principle can greatly help to select simple classifier models, while the single- and multi-kernel methods can effectively address nonlinearly separabl...
Chapter
With the increasing information load brought by the accelerated growth of research papers, the automatic discovery of a field’s emerging scientific topics becomes vital. It enables broad applications, such as optimizing resource allocations for promising research areas, predicting future technology trends, finding knowledge gaps and new concepts, a...
Article
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Mitophagy preserves microvascular structure and function during myocardial ischemia/reperfusion (I/R) injury. Empagliflozin, an anti-diabetes drug, may also protect mitochondria. We explored whether empagliflozin could reduce cardiac microvascular I/R injury by enhancing mitophagy. In mice, I/R injury induced luminal stenosis, microvessel wall dama...
Article
Credit cardholder behavior analysis is a very important issue for credit risk control. And classification method, which is an important topic in data mining, is usually used here for "Bad" credit detection. Data pre-processing may affect classification accuracy. In this paper, an information-based fuzzy partition approach is proposed for bad credit...
Article
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Cross-platform difficulties, data privacy, and authentication security are common problems in the Internet of Things (IoT) environment. Despite the fact that blockchain technology has brought new opportunities to the development of the IoT by enhancing interoperability, improving privacy and security, there are still problems such as diversity, lac...
Article
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In the present study, we used lipopolysaccharide- (LPS-) stimulated H9C2 cardiomyocytes to investigate whether irisin treatment attenuates septic cardiomyopathy via Fundc1-related mitophagy. Fundc1 levels and mitophagy were significantly reduced in LPS-stimulated H9C2 cardiomyocytes but were significantly increased by irisin treatment. Irisin signi...
Article
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The Internet of vehicles (IoV) has a typical Internet of things architecture, which is the specific application of Internet of things (IoT) technology in the field of intelligent transportation. Virtual network embedding (VNE) is the effective allocation of physical network resources to the virtual network, and is a virtualization technology widely...
Article
In recent years, money laundering has become much easier to be achieved but more challenging to be detected than before, which has enormous adversary effects on finance, military, and other related fields. In the real-time scenario, every money laundering case has a unique structure in terms of transactions. It is not sufficient to detect suspiciou...
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Pyroptosis is a recently discovered aspartic aspart-specific cysteine protease (Caspase-1/4/5/11) dependent mode of gene-regulated cell death cell death, which is represented by the rupture of cell membrane perforations and the production of proinflammatory mediaters like interleukin-18(IL-18) and interleukin-1β (IL-1β). Mitochondria also play an i...
Article
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Given the increasing amounts of data and high feature dimensionalities in forecasting problems, it is challenging to build regression models that are both computationally efficient and highly accurate. Moreover, regression models commonly suffer from low interpretability when using a single kernel function or a composite of multi-kernel functions t...
Chapter
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Transfer learning is an emerging technique in machine learning, by which we can solve a new task with the knowledge obtained from an old task in order to address the lack of labeled data. In particular deep domain adaptation (a branch of transfer learning) gets the most attention in recently published articles. The intuition behind this is that dee...
Preprint
The definition of factor space and a unified optimization based classification model were developed for linear programming. Intelligent behaviour appeared in a decision process can be treated as a point y, the dynamic state observed and controlled by the agent, moving in a factor space impelled by the goal factor and blocked by the constraint facto...
Chapter
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Deep Learning, also known as deep representation learning, has dramatically improved the performances on a variety of learning tasks and achieved tremendous successes in the past few years. Specifically, artificial neural networks are mainly studied, which mainly include Multilayer Perceptrons (MLPs), Convolutional Neural Networks (CNNs) and Recurr...
Article
Cloud computing is developing rapidly and playing an increasingly important role in many fields. Resource management of data center networks (DCNs) is critical to the performance of cloud computing. Due to the large-scale, distributed, and cross-regional characteristics of DCNs, there is insufficient resource utilization. In this article, we discus...
Chapter
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Studying on EEG (Electroencephalography) data instances to discover potential recognizable patterns has been a emerging hot topic in recent years, particularly for cognitive analysis in online education areas. Machine learning techniques have been widely adopted in EEG analytical processes for non-invasive brain research. Existing work indicated th...
Article
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The advancement of cognitive computing for traffic status understanding, powered by machine learning and data analytics, enables prediction of traffic anomalies from continuously generated big GPS trajectory data. Existing methods generally use traffic indicators such as traffic flows and speeds to detect anomalies, but they may over-identify anoma...
Article
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Cardiac ischemia-reperfusion (I/R) injury is associated with mitochondrial dysfunction. Recent studies have reported that mitochondrial function is determined by mitochondrial dynamics. Here, we hypothesized that AMPKα2 functions as an upstream mediator that sustains mitochondrial dynamics in cardiac I/R injury and cardiomyocyte hypoxia-reoxygenati...
Conference Paper
The traditional blockchain has the shortcoming that a single-chain can only deal with one or a few specific data types. The research question of how to make blockchain be able to deal with various data types has not been well studied. In this paper, we propose a single-chain based extension model of blockchain for fintech (SEBF). In the financial e...
Article
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Wireless-body-area-networks (WBANs) comprise various types of sensors to monitor and collect various vital signals, such as blood pressure, pulse, heartbeat, body temperature, and blood sugar. A dense and mobile WBAN often suffers from interference, which causes serious problems, such as wasting energy and degrading throughput. In reality, not all...
Article
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Research on electroencephalography (EEG) signals and their data analysis have drawn much attention in recent years. Data mining techniques have been extensively applied as efficient solutions for non-invasive brain–computer interface (BCI) research. Previous research has indicated that human brains produce recognizable EEG signals associated with s...
Article
The increasing amount of solid waste is becoming a significant problem that needs to be addressed urgently. The reliable and accurate classification method is a crucial step in waste disposal because different types of wastes have different disposal ways. The existing waste classification models driven by deep learning are not easy to achieve accur...
Article
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When multiple Wireless Body Area Networks (WBANs) are aggregated, the overlapping region of their communications will result in internetwork interference, which could impose severe impacts on the reliability of WBAN performance. Therefore, how to mitigate the internetwork interference becomes the key problem to be solved urgently in practical appli...
Chapter
The process of blending gas transmission contains multiple kinds of influence factors that are related with the achievement of maximal overall profit for a refinery gas company. It is, therefore, a multiple objective optimization problems. To maximize overall profit, we proposes a multiple objective resultant gradient descent method (RGDM) to solve...
Chapter
With the advent of next-generation sequencing technology, sequencing costs have fallen sharply compared to the previous sequencing technologies. Genomic big data has become the significant big data application. In the face of growing genomic data, its storage and migration face enormous challenges. Therefore, researchers have proposed a variety of...
Article
Network‐on‐chip (NoC) is a new design method of system‐on‐chip used in very large scale integrated circuit (VLSI) systems. It is an important issue for choosing the appropriate topology for NoC. Wirelength and layout area are significant parameters affecting NoC due to the restriction of chip area. In this paper, we propose a new interconnection ne...
Book
This book constitutes the refereed proceedings of the 6th International Conference on Data Science, ICDS 2019, held in Ningbo, China, during May 2019. The 64 revised full papers presented were carefully reviewed and selected from 210 submissions. The research papers cover the areas of Advancement of Data Science and Smart City Applications, Theor...
Article
To improve the quality of service and network performance for the Flash P2P video-on-demand, the prediction Flash P2P network traffic flow is beneficial for the control of the network video traffic. In this paper, a novel prediction algorithm to forecast the traffic rate of Flash P2P video is proposed. This algorithm is based on the combination of...
Article
The performance of active contour model is limited on retinal vessel segmentation as vessel images are usually corrupted with intensity inhomogeneity, low contrast, and weak boundary, which severely affect the segmentation results of retinal vessels. A new active contour model combining the local and global information is proposed in this paper to...
Article
Objective: To assess the risk factors associated with acute gastrointestinal failure (AGF) in critically ill patients with traumatic brain injury (TBI). Methods: Prospective, observational study was conducted in NanFang Hospital, Southern Medical University. All patients admitted to the Department of Critical Care Medicine and Department of Neur...
Article
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With the maturity of genome sequencing technology, huge amounts of sequence reads as well as assembled genomes are generating. With the explosive growth of genomic data, the storage and transmission of genomic data are facing enormous challenges. FASTA, as one of the main storage formats for genome sequences, is widely used in the Gene Bank because...
Article
Discovering frequent itemsets is essential for finding association rules, yet too computational expensive using existing algorithms. It is even more challenging to find frequent itemsets upon streaming numeric data. The streaming characteristic leads to a challenge that streaming numeric data cannot be scanned repetitively. The numeric characterist...
Article
Eigenvalue decomposition is widely used in dimensionality reduction for knowledge engineering, in particular principal component analysis. Traditional eigenvalue decomposition algorithms for decomposing a matrix of size $n \times n$ are usually of complexity $O(n^3)$ , due to a bottleneck in which Householder/Givens transforms convert a general...
Conference Paper
Collaborative filtering is a main-stream technique to alleviate information overload. Singular Value Decomposition (SVD) has become very popular in the field of collaborative filtering. For computation of collaborative filtering, traditional SVD algorithms are too slow, randomized SVD algorithms using sampling techniques are more practical than the...
Conference Paper
Cyberspace topologies can be demonstrated mathematically by a graph theoretic approach which basic structure is in accord with the interconnected world of social networks. Subgraph pattern matching analysis is an approach to performing computer network data analysis that executes efficient continuous queries on dynamic social graphs and minimizes t...
Article
With the rise of cloud service providers and the continuous virtualization of data centers, data center networks are also developing rapidly. As data centers become more and more complex, the demand for security increases dramatically. This paper discusses the privacy inherent in data centers. However, there is no general solution to the privacy pr...
Article
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The graph isomorphism problem is to determine two finite graphs that are isomorphic which is not known with a polynomial‐time solution. This paper solves the simple undirected graph isomorphism problem with an algorithmic approach as NP=P and proposes a polynomial‐time solution to check if two simple undirected graphs are isomorphic or not. Three n...
Article
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Techniques of performance analysis, comprising of various metrics such as accuracy, efficiency and consuming time, have been conducted to evaluate the measures of properties and interestingness for the association rule mining method. Therefore, these metrics combined with different parameters (partitioning points, fuzzy sets) should be analysed tho...
Article
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Discovering the concealed patterns of Electroencephalogram (EEG) signals is a crucial part in efficient detection of epileptic seizures. This study develops a new scheme based on Douglas-Peucker algorithm (DP) and principal component analysis (PCA) for extraction of representative and discriminatory information from epileptic EEG data. As the multi...
Article
Individuals' right to privacy includes control over access to their location information. With the advent of location‐based services and personal transport services (such as ridesharing), the risk of location privacy breaches is increased greatly. The potential negative effects of location privacy leakages include spam location‐based service floodi...
Article
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Over the past few decades, many classifier methods are suggested for credit risk evaluation. With ever-increasing amounts of data, for multi-criteria optimization classifier (MCOC) and other traditional classification methods, owing to the correlation among different features in data these classifiers often give the poor predictive performance. Thu...
Article
For forecasting by regression, more and more instances and features are collected and added to the regression models. When there are many noisy and redundant instances and features, these models often give the poor predictive accuracy and interpretability owing to overfitting and computational complexity. Besides, least squares support vector regre...
Article
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The concept of smart city seems to have received considerable attention shortly after its proposal. Nearly 200 projects in the world related to smart healthcare are in the implementation phase [1], and this number is gradually expanding. The smart healthcare is essential parts of creating a smart city, because anyone can go to the hospital for trea...
Article
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Data mining and machine learning are both useful tools in the field of data analysis. Classification algorithm is one of the most important techniques in data mining, therefore, it is of great significance to select suitable classification models with high efficiency to show superiority when solving classification problems with the use of Iris data...
Article
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While the Internet has been proposed for a long time, the Internet of Things is a relatively new concept which is constantly evolving, and it is also an embodiment of the practical use for the construction of smart cities. In this study of smart cities, we first illustrate the data processing problems in smart cities, especially the data distributi...
Article
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A bi-level programming model is constructed for the oilfield development in this paper with the objective to maximize the total benefit. The management level of the oil company is regarded as the leader in this model, which makes the global programming and assigns the allocated investments to four oilfield development modes (the follower). The lowe...
Article
The problem of risk classification and prediction, an essential research direction, aiming to identify and predict risks for various applications, has been researched in this paper. To identify and predict risks, numerous researchers build models on discovering hidden information of a label (positive credit or negative credit). Fuzzy logic is robus...
Chapter
The emergence of wearable smart devices enables people to understand their health level in more details and efficiently process information. According to the physical form of the wearable smart device, this paper classifies the wearable smart devices into four categories and conducts the survey regarding the development of related technologies thro...
Chapter
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Density-based clustering, such as Density Peak Clustering (DPC) and DBSCAN, can find clusters with arbitrary shapes and have wide applications such as image processing, spatial data mining and text mining. In DBSCAN, a core point has density greater than a threshold, and can spread its cluster ID to its neighbours. However, the core points selected...
Article
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This paper proposes a method to address misreadings and consequent inadequacy of Radio- Frequency Identification (RFID) data for social insect monitoring. Six months worth of field experiment data were collected to demonstrate the application of the method. The data is transformed into a linear combination of Gaussian model and curve-fitted using e...
Article
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The chip has been developed for over 60 years, and its design process, manufacturing process, and packaging and testing methods are all mature, and its scale, performance, and functions are constantly improving. Through the research of the whole development process of the chip, this paper expounds the current development status of the chip, involve...
Article
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The current safety regulations and its correlative specifications of the coal industry ignore the problem of malfunction. To solve the issue completely, an optimized location model based on the methane sensor is proposed in this paper. The proposed model is not only economic but also reliable for a sensor of methane. In the procedure of establishin...
Article
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Diabetes alone does not affect the health, but its complications always bring danger to people’s health. To avoid the development of diabetes and posterior to discover diabetes, checking blood glucose level is an effective way. The development of glucose screening measurements is introduced. Non-invasive glucose monitor methods, as accurate, safe,...
Article
Space-time template matching is considered as a promising approach for human action recognition. However, a major drawback of template based methods is computational overhead due to matching in spatial domain. Recently, spacetime correlation based action filters have been proposed for recognizing human actions in frequency domain. These action filt...