Xinheng Wang's research while affiliated with Xi'an Jiaotong-Liverpool University and other places
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Publications (140)
The current methods for evaluating the operating condition of electricity transmission lines (ETLs) and providing early warning have several problems, such as the low correlation of data, ignoring the influence of seasonal factors, and strong subjectivity. This paper analyses the sensitive factors that influence dynamic key evaluation indices such...
The developments on next generation IoT sensing devices, with the advances on their low power computational capabilities and high speed networking has led to the introduction of the edge computing paradigm. Within an edge cloud environment, services may generate and consume data locally, without involving cloud computing infrastructures. Aiming to...
Due to the barely resonant earthed system used in the transmission line, it is more challenging to identify faults at a 66 kV voltage level because of insufficient fault identification techniques. In this paper, a 66 kV transmission line fault identification method based on a fault characteristic matrix and an improved particle swarm optimization (...
Aiming at the difficulty of fault location of multi-source transmission lines, this paper proposes a fault location method for multi-terminal transmission lines based on a fault branch judgment matrix. The fault traveling wave signal is decomposed by Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), and the IMFs sensitiv...
Fast-growing trees pose risks to the operational safety of overhead power lines. Traditional methods of inspecting tree growth, such as ground inspection, are time-consuming and not accurate. Latest development employs drones equipped with either light detection and ranging (LiDAR) or camera for accurate inspections. However, those methods are expe...
Transmission lines are primarily deployed overhead, and the transmission tower, acting as the fulcrum, can be affected by the unbalanced force of the wire and extreme weather, resulting in the transmission tower tilt, deformation, or collapse. This can jeopardize the safe operation of the power grid and even cause widespread failures, resulting in...
This paper proposes an integrated positioning algorithm for mobile devices and achieves long-term and high-accuracy indoor pedestrian tracking under severe non-Line-of-Sight (NLOS) scenarios. The traditional fusion method for hand-held devices lacks zero-speed correction and cannot clear the accumulated error of the Pedestrian Dead Reckoning (PDR)....
Dijkstra's algorithm is one of the most popular classic path planning algorithms, achieving optimal solutions across a wide range of challenging tasks. However, it only calculates the shortest distance from one vertex to another, which is hard to directly apply to the Dynamic Multi-Sources to Single-Destination (DMS-SD) problem. This paper proposes...
Directly processing 3D point cloud data becomes dominant in classification and segmentation tasks. Present mainstream point based methods usually focus on learning in either geometric space (i.e. PointNet++) or semantic space (i.e. DGCNN). Owing to the irregular and unordered data property of point cloud, these methods still suffer from drawbacks o...
With the emergence of COVID-19, social distancing detection is a crucial technique for epidemic prevention and control. However, the current mainstream detection technology cannot obtain accurate social distance in real-time. To address this problem, this paper presents a first study on smartphone-based social distance detection technology based on...
Background
T1–2 breast cancer patients with only one sentinel lymph node (SLN) metastasis have an extremely low non-SLN (NSLN) metastatic rate and are favorable for axillary lymph node dissection (ALND) exemption. This study aimed to construct a nomogram-based preoperative prediction model of NSLN metastasis for such patients, thereby assisting in...
Recent advances in both lightweight deep learning algorithms and edge computing increasingly enable multiple model inference tasks to be conducted concurrently on resource-constrained edge devices, allowing us to achieve one goal collaboratively rather than getting high quality in each standalone task. However, the high overall running latency for...
Homomorphic encryption with the ability to compute over encrypted data without access to the secret key provides benefits for the secure and powerful computation, storage, and communication of resources in the cloud. One of its important applications is fast-growing robot control systems for building lightweight, low-cost, smarter robots with intel...
Scientific evidence shows that acoustic analysis could be an indicator for diagnosing COVID-19. From analyzing recorded breath sounds on smartphones, it is discovered that patients with COVID-19 have different patterns in both the time domain and frequency domain. These patterns are used in this paper to diagnose the infection of COVID-19. Statisti...
Background and Objective
Sentinel lymph node biopsy (SLNB) is used to assess the status of axillary lymph node (ALN), but it causes many adverse reactions. Considering the low rate of sentinel lymph node (SLN) metastasis in T1 breast cancer, this study aims to identify the characteristics of T1 breast cancer without SLN metastasis and to select T1...
Breast cancer (BRCA) is one of the leading causes of death among women worldwide, and drug resistance often leads to a poor prognosis. Necroptosis is a type of programmed cell death (PCD) and exhibits regulatory effects on tumor progression, but few studies have focused on the relationships between necroptosis-associated lncRNAs and BRCA. In this s...
IIndustry 5.0 requires intelligent self-organized, self- managed and self-monitoring applications with ability to analyze and predict both the human as well as machine behaviors across interconnected devices. Tackling dynamic network behavior is a unique challenge for IoT applications in industry 5.0. Knowledge- Defined Networks (KDN) bridges this...
Many end-to-end deep learning algorithms seeking to classify malicious traffic and encrypted traffic have been proposed in recent years. End-to-end deep learning algorithms require a large number of samples to train a model. However, it is hard for existing methods fully utilizing the heterogeneous multimodal input. To this end, we propose the SHAP...
With the development of the Internet of Things, it has been widely studied and deployed in industrial manufacturing, intelligent transportation, and healthcare systems. The time-series feature of the IoT makes the data density and the data dimension higher, where anomaly detection is important to ensure hardware and software security. However, the...
In this paper, we focus on tackling the precise keypoint coordinates regression task. Most existing approaches adopt complicated networks with a large number of parameters, leading to a heavy model with poor cost-effectiveness in practice. To overcome this limitation, we develop a small yet discrimicative model called STair Network, which can be si...
Blockchain can help edge IoT-enabled Maritime Transportation Systems (MTS) in solving its privacy and security problems. In this paper, a lightweight blockchain called LBlockchainE is designed for edge IoT-enabled MTS to guarantee the security of sensor data stored in an edge computing environment. To save the resources of edge servers on ship, a d...
The dysregulation of transfer RNA (tRNA) expression contributes to the diversity of proteomics, heterogeneity of cell populations, and instability of the genome, which may be related to human cancer susceptibility. However, the relationship between tRNA dysregulation and cancer susceptibility remains elusive because the landscape of cancer-associat...
Existing navigation services provide route options based on a single metric without considering user's preference. This results in the planned route not meeting the actual needs of users. In this paper, a personalized route planning algorithm is proposed, which can provide users with a route that meets their requirements. Based on the multiple prop...
Wi-Fi fingerprint systems provide cost-effective and reliable solution for indoor positioning. However, such systems incur high calibration cost in the training phase and high searching overhead in the positioning phase. Moreover, huge storage requirement for the radio map of a large-scale fingerprint system is another major issue. Several solution...
Location-aware recommendation is considered as one of human behavior cognitive analyses in the world of human-machine-environment system. The development of 5G technology and ubiquitous mobile devices has led to the emergence of a new online platform, location-based social networks (LBSNs), which allows users to share their locations. The essential...
Smartphone ownership has increased rapidly over the past decade, and the smartphone has become a popular technological product in modern life. The universal wireless communication scheme on smartphones leverages electromagnetic wave transmission, where the spectrum resource becomes scarce in some scenarios. As a supplement to some face-to-face tran...
This two-volume set constitutes the refereed proceedings of the 16th International Conference on Collaborative Computing: Networking, Applications, and Worksharing, CollaborateCom 2020, held in Shanghai, China, in October 2020.
The 61 full papers and 16 short papers presented were carefully reviewed and selected from 211 submissions. The papers ref...
This two-volume set constitutes the refereed proceedings of the 17th International Conference on Collaborative Computing: Networking, Applications, and Worksharing, CollaborateCom 2021, held in October 2021. Due to COVID-19 pandemic the conference was held virtually.
The 62 full papers and 7 short papers presented were carefully reviewed and select...
The Internet of Things (IoT) technology is not just about the connection among billions of devices but also about enabling a wide range of new capabilities, architectures, or service paradigms. The scale of the IoT is set to have a major economic, social, and environmental impact. However, the implementation of IoT faces various challenges, includi...
This two-volume set constitutes the refereed proceedings of the 16th International Conference on Collaborative Computing: Networking, Applications, and Worksharing, CollaborateCom 2020, held in Shanghai, China, in October 2020.
The 61 full papers and 16 short papers presented were carefully reviewed and selected from 211 submissions. The papers ref...
This two-volume set constitutes the refereed proceedings of the 17th International Conference on Collaborative Computing: Networking, Applications, and Worksharing, CollaborateCom 2021, held in October 2021. Due to COVID-19 pandemic the conference was held virtually.
The 62 full papers and 7 short papers presented were carefully reviewed and select...
Object detection for autonomous driving in smart transportation systems requires comprehensive consideration of accuracy, speed and sensitivity for detecting multi-objects. The one-stage algorithm, Single Shot MultiBox Detector (SSD), can basically satisfy the above requirements. However, there are still rooms for improvement of the overall precisi...
The multi-access edge computing (MEC) has higher computing power and lower latency than user equipment and remote cloud computing, enabling the continuing emergence of new types of services and mobile application. However, the movement of users could induce service migration or interruption in the MEC network. Especially for highly mobile users, th...
The security of data storage, transmission, and processing is emerging as an important consideration in many data analytics techniques and technologies. For instance, in machine learning, the datasets could contain sensitive information that cannot be protected by traditional encryption approaches. Homomorphic encryption schemes and secure multi-pa...
Over the last fifteen years, wireless local area networks (WLANs) have been populated on large variety of pervasive devices hosting heterogeneous applications. Pervasive edge computing has accelerated more distributed network applications for these devices, eliminating the round-trip to help in achieving zero latency dream. However, These applicati...
The Multi-Access Edge Computing (MEC) has higher computing power than user equipment and lower latency than remote cloud computing, making new types of services and mobile applications keep emerging. However, the movement of users could induce service migration or interruption in the MEC network. Especially for highly mobile users, they accelerate...
Fine-grained image classification is used to identify dozens or hundreds of subcategory images which are classified in a same large category. This task is challenging due to the subtle inter-class visual differences. Most existing methods try to locate discriminative regions or parts of objects to develop an effective classifier. However, there are...
Over the last few years, owing to the development, deployment, and use of Internet of Things (IoT) systems and smart devices, a large volume of data has been generated from various operation systems. High speed 4G networks and low cost of data usage foster the commercialization of a few heavy data driven social networks, such as Tik Tok and Instagr...
With the prevalent application of Internet-of-Things (IoT) in real world, services have become a widely used means of providing configurable resources. As the number of services is large and is also increasing fast, it is an inevitable mission to determine the suitability of a service to a user. Two typical tasks are needed, which are service recom...
The rapid advancements of Micro/NanoBOTs (MNBOTs) introduce a new research opportunity in routing multiple MNBOTs to perform practical biomedical applications. In this paper, leveraging on existing group communication and motion control schemes for MNBOTs, we propose an Activation Based Molecular Routing (ABMR) scheme in MNBOT networks to coordinat...
In recent years, as cloud data center has grown constantly in size and quantity, the energy consumption of cloud data center has increased dramatically. Therefore, it is of great significance to study the energy-saving issues of cloud data centers in depth. Therefore, this paper analyzes the architecture of energy consumption of IT system in cloud...
Hardware and software lightweight solutions became the mainstream for current and future emerging technologies. Container-based virtualization provides more efficient and faster solutions than traditional virtual machines, offering good scalability, flexibility, and multi-tenancy. They are capable of serving in a heterogeneous and dynamic environme...
Multiple Input and Multiple Output (MIMO) systems use multiple antennas at both transmitter and receiver ends for increasing link capacity and spectral efficiency. However, combining schemes used for such systems face critical issues such as presence of interference, signals to interference and noise ratios (SINRs) and complexity. To overcome the a...
With the advent of the Internet of Things, the security of the network layer in the Internet of Things is getting more and more attention. Traditional intrusion detection technologies cannot be well adapted in the complex Internet environment of the Internet of Things. Therefore, it is extremely urgent to study the intrusion detection system corres...
In this paper, a method for measuring the grounding resistance of the tower without disconnecting all the down conductors is proposed for the first time in view of the shortage of manual measurement of the grounding resistance of the tower. This paper introduces the measurement model of single or multiple down conductors, and uses a hybrid genetic...
This paper investigates the issue of Quality of Experience (QoE) for multimedia services over heterogeneous networks. A new concept of “Isomorphism Flow” (iFlow) was introduced for analyzing multimedia traffics, which is inspired by the abstract algebra based on experimental research. By using iFlow, the multimedia traffics with similar QoE require...
This book constitutes the thoroughly refereed proceedings of the 15th International Conference on Collaborative Computing: Networking, Applications, and Worksharing, CollaborateCom 2019, held in London, UK, in August 2019. The 54 full papers presented were carefully reviewed and selected from 121 submissions. The papers reflect the conference sessi...
Mobile video applications have started to dominate the global mobile data traffic in recent years, and both opportunities and challenges have arisen when the emerging mobile cloud paradigm is introduced to support the resource-demanding video processing and networking services. This chapter offers in-depth discussions for content- and context-aware...
This book constitutes the thoroughly refereed proceedings of the 14th International Conference on Collaborative Computing: Networking, Applications, and Worksharing, CollaborateCom 2018, held in Shanghai, China, in December 2018. The 43 full and 19 short papers presented were carefully reviewed and selected from 106 submissions. The papers reflect...
In this paper, a novel time of arrival (TOA) estimation method is proposed based on an iterative cleaning process to extract the first path signal. The purpose is to address the challenge in dense multipath indoor environments that the power of the first path component is normally smaller than other multipath components, where the traditional match...
Providing location recommendations has become an essential feature for location-based social networks (LBSNs) because it helps users explore new places and makes LBSNs more prevalent to users. Existing studies mostly focus on introducing new features that affect users' check-in behaviours in LBSNs. Despite the difference in the type of the features...
In recent years, research on location predictions by mining trajectories of users has attracted a lot of attentions. Ex- isting studies on this topic mostly focus on individual movements, considering the trajectories as solo movements. However, a user usually does not visit locations just for the personal interest. The preference of a travel group...
Digital healthcare is becoming increasingly important as the ageing population and the number of people diagnosed with chronic diseases is increasing. The face of healthcare delivery has changed radically and at its core is a digital and customer revolution. Connected health is the convergence of medical devices, security devices, and communication...
Through the availability of location-acquisition devices, huge volumes of spatio-temporal data recording the movement of people is provided. Discovery of the group of people who travel together can provide valuable knowledge to a variety of critical applications. Existing studies on this topic mainly focus on the movement of vehicles or animals wit...
Through the availability of location-acquisition devices, huge volumes of spatio-temporal data recording the movement of people are provided. Discovery of the group of people who travel together can provide valuable knowledge to a variety of critical applications. Existing studies on this topic mainly focus on the movement of vehicles or animals wi...
Background: A new technology for indoor positioning is proposed in this paper by applying combined RFID (Radio Frequency ID) / IRID (Infrared ID) and spatial fluctuations of the ambient magnetic field. Due to the presence of interior reinforced concrete construction, furniture, electronics and other indoor subjects, the distribution of the magnetic...
To address the issue of finegrained classification of Internet multimedia traffic from a Quality of Service (QoS) perspective with a suitable granularity, this paper defines a new set of QoS classes and presents a modified K-Singular Value Decomposition (K-SVD) method for multimedia identification. After analyzing several instances of typical Inter...
In software defined networks, route optimization among controllers is critical in reducing the traffic. Previous approaches are using generic algorithms or Lagrange optimization, which the computation complexity is rather high. In this paper, an efficient hybrid routing combining proactive and reactive approaches is proposed that significantly redu...
As the demand for indoor localization is increasing to support our daily life in large and complex indoor environments, sound-based localization technologies have attracted researchers’ attention because they have the advantages of being fully compatible with commercial off-the-shelf (COTS) smartphones, they have high positioning accuracy and low-c...
This paper presents a simultaneous localization and mapping (SLAM) method that utilizes the measurement of ambient magnetic fields present in all indoor environments. In this paper, an improved exponentially weighted particle filter was proposed to estimate the pose distribution of the object and a Kriging interpolation method was introduced to upd...
Digital healthcare is becoming increasingly important as the ageing population and the number of people diagnosed with chronic diseases is increasing. The face of healthcare delivery has changed radically and at its core is a digital and customer revolution. Connected health is the convergence of medical devices, security devices, and communication...
With the development of new networking paradigms and wireless protocols, nodes with different capabilities are used to form a heterogeneous network. The performance of this kind of networks is seriously deteriorated because of the bottlenecks inside the network. In addition, because of the application requirements, different routing schemes are req...
Molecular Nanoscale Sensor Networks (MNSNs) introduce a new molecular routing paradigm where the molecular communication is enabled by activating the nanosensors on the routing path to release the molecules. This new molecular activation mechanism is a new many-to-many scheme where the transmitting nanosensors transmits molecules to multiple receiv...
In order to lower the power consumption and improve the coefficient of resource utilization of current cloud computing systems, this paper proposes two resource pre-allocation algorithms based on the "shut down the redundant, turn on the demanded" strategy here. Firstly, a green cloud computing model is presented, abstracting the task scheduling pr...
Localization is an active research area in the field of wireless sensor networks (WSNs). It is supportive in different domains, e.g., object tracing, fire detection, health monitoring, traffic surveillance, military sensing and habitat monitoring. So, in such many cases, localization is one of the major challenges in WSNs. The main categories of lo...
The multipath effect and movements of people in indoor environments lead to inaccurate localization. Through the test, calculation and analysis on the received signal strength indication (RSSI) and the variance of RSSI, we propose a novel variance-based fingerprint distance adjustment algorithm (VFDA). Based on the rule that variance decreases with...
With each passing day, the information and communication technologies are evolving with more and more information shared across the globe using the internet superhighway. The threats to information, while connected to the cyber world are getting more targeted, voluminous, and sophisticated requiring new antifragile and resilient network security me...