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Gui Yun Tian

Bio: Gui Yun Tian is an academic researcher from Newcastle University. The author has contributed to research in topics: Nondestructive testing & Eddy current. The author has an hindex of 56, co-authored 489 publications receiving 11308 citations. Previous affiliations of Gui Yun Tian include University of East Anglia & University of Derby.


Papers
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Journal ArticleDOI
TL;DR: A framework for structural health monitoring (SHM) using IoT technologies on intelligent and reliable monitoring is introduced and technologies involved in IoT and SHM system implementation as well as data routing strategy in IoT environment are presented.
Abstract: Internet of Things (IoT) has recently received a great attention due to its potential and capacity to be integrated into any complex system. As a result of rapid development of sensing technologies such as radio-frequency identification, sensors and the convergence of information technologies such as wireless communication and Internet, IoT is emerging as an important technology for monitoring systems. This paper reviews and introduces a framework for structural health monitoring (SHM) using IoT technologies on intelligent and reliable monitoring. Specifically, technologies involved in IoT and SHM system implementation as well as data routing strategy in IoT environment are presented. As the amount of data generated by sensing devices are voluminous and faster than ever, big data solutions are introduced to deal with the complex and large amount of data collected from sensors installed on structures.

319 citations

Journal ArticleDOI
TL;DR: In this paper, the authors introduced the application of principal component analysis (PCA) in extracting information from PEC responses, which has performed better than the conventional technique in the classification of defects.
Abstract: Pulsed Eddy current (PEC) is a new emerging NDT technique for sub-surface defect detection. The technique mainly uses the response peak value and arrival to detect and quantify the defects. This could suffer from noise and be not sufficient to extract more information about the defects, e.g. depth information of defects. This paper introduces the application of principal component analysis in extracting information from PEC responses. A comparative test carried out shows that the introduced technique has performed better than the conventional technique in the classification of defects.

290 citations

Journal ArticleDOI
29 Jan 2017-Sensors
TL;DR: The challenges and state-of-the-art methods of passive RFID antenna sensors and systems in terms of sensing and communication from system point of view are highlighted and future trends are discussed.
Abstract: In recent few years, the antenna and sensor communities have witnessed a considerable integration of radio frequency identification (RFID) tag antennas and sensors because of the impetus provided by internet of things (IoT) and cyber-physical systems (CPS). Such types of sensor can find potential applications in structural health monitoring (SHM) because of their passive, wireless, simple, compact size, and multimodal nature, particular in large scale infrastructures during their lifecycle. The big data from these ubiquitous sensors are expected to generate a big impact for intelligent monitoring. A remarkable number of scientific papers demonstrate the possibility that objects can be remotely tracked and intelligently monitored for their physical/chemical/mechanical properties and environment conditions. Most of the work focuses on antenna design, and significant information has been generated to demonstrate feasibilities. Further information is needed to gain deep understanding of the passive RFID antenna sensor systems in order to make them reliable and practical. Nevertheless, this information is scattered over much literature. This paper is to comprehensively summarize and clearly highlight the challenges and state-of-the-art methods of passive RFID antenna sensors and systems in terms of sensing and communication from system point of view. Future trends are also discussed. The future research and development in UK are suggested as well.

287 citations

Journal ArticleDOI
TL;DR: This paper proposes a new colour invariant image representation based on an existing grey-scale image enhancement technique: histogram equalisation and applies the method to an image indexing application and shows that the method out performs all previous invariant representations.

216 citations

Proceedings ArticleDOI
01 Jan 2019
TL;DR: This paper proposes deep learning models for the cyber security in IoT (Internet of Things) networks and evaluated those using latest CICIDS2017 datasets for DDoS attack detection which has provided highest accuracy as 97.16% also proposed models are compared with machine learning algorithms.
Abstract: In this paper we propose deep learning models for the cyber security in IoT (Internet of Things) networks. IoT network is as a promising technology which connects the living and non-living things around the world. The implementation of IoT is growing fast but the cyber security is still a loophole, so it is susceptible to many cyber-attack and for the success of any network it most important that the network is completely secure, otherwise people could be reluctant to use this technology. DDoS (Distributed Denial of Service) attack has affected many IoT networks in recent past that has resulted in huge losses. We have proposed deep learning models and evaluated those using latest CICIDS2017 datasets for DDoS attack detection which has provided highest accuracy as 97.16% also proposed models are compared with machine learning algorithms. This paper also identifies open research challenges for usage of deep learning algorithm for IoT cyber security.

202 citations


Cited by
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Proceedings Article
01 Jan 1989
TL;DR: A scheme is developed for classifying the types of motion perceived by a humanlike robot and equations, theorems, concepts, clues, etc., relating the objects, their positions, and their motion to their images on the focal plane are presented.
Abstract: A scheme is developed for classifying the types of motion perceived by a humanlike robot. It is assumed that the robot receives visual images of the scene using a perspective system model. Equations, theorems, concepts, clues, etc., relating the objects, their positions, and their motion to their images on the focal plane are presented. >

2,000 citations

Journal ArticleDOI
01 Mar 1980-Nature

1,327 citations

Journal ArticleDOI
TL;DR: A comprehensive review of the domain of physical layer security in multiuser wireless networks, with an overview of the foundations dating back to the pioneering work of Shannon and Wyner on information-theoretic security and observations on potential research directions in this area.
Abstract: This paper provides a comprehensive review of the domain of physical layer security in multiuser wireless networks. The essential premise of physical layer security is to enable the exchange of confidential messages over a wireless medium in the presence of unauthorized eavesdroppers, without relying on higher-layer encryption. This can be achieved primarily in two ways: without the need for a secret key by intelligently designing transmit coding strategies, or by exploiting the wireless communication medium to develop secret keys over public channels. The survey begins with an overview of the foundations dating back to the pioneering work of Shannon and Wyner on information-theoretic security. We then describe the evolution of secure transmission strategies from point-to-point channels to multiple-antenna systems, followed by generalizations to multiuser broadcast, multiple-access, interference, and relay networks. Secret-key generation and establishment protocols based on physical layer mechanisms are subsequently covered. Approaches for secrecy based on channel coding design are then examined, along with a description of inter-disciplinary approaches based on game theory and stochastic geometry. The associated problem of physical layer message authentication is also briefly introduced. The survey concludes with observations on potential research directions in this area.

1,294 citations

Journal ArticleDOI
Li Li1, Jian Yao1, Renping Xie1, Menghan Xia1, Wei Zhang2 
22 Dec 2016-Sensors
TL;DR: Experimental results on a large set of challenging street-view panoramic images captured form the real world illustrate that the proposed system is capable of creating high-quality panoramas.
Abstract: In this paper, we propose a unified framework to generate a pleasant and high-quality street-view panorama by stitching multiple panoramic images captured from the cameras mounted on the mobile platform. Our proposed framework is comprised of four major steps: image warping, color correction, optimal seam line detection and image blending. Since the input images are captured without a precisely common projection center from the scenes with the depth differences with respect to the cameras to different extents, such images cannot be precisely aligned in geometry. Therefore, an efficient image warping method based on the dense optical flow field is proposed to greatly suppress the influence of large geometric misalignment at first. Then, to lessen the influence of photometric inconsistencies caused by the illumination variations and different exposure settings, we propose an efficient color correction algorithm via matching extreme points of histograms to greatly decrease color differences between warped images. After that, the optimal seam lines between adjacent input images are detected via the graph cut energy minimization framework. At last, the Laplacian pyramid blending algorithm is applied to further eliminate the stitching artifacts along the optimal seam lines. Experimental results on a large set of challenging street-view panoramic images captured form the real world illustrate that the proposed system is capable of creating high-quality panoramas.

863 citations