School of Advanced Technology

School of Advanced Technology
Xi'an Jiaotong-Liverpool University
111 Ren'ai Road Suzhou Dushu Lake Science and Education Innovation District , Suzhou Industrial Park
Suzhou,Jiangsu Province,P. R. China,215123
1. Low-Latency Heterogeneous Networks with Millimeter-Wave Communications

Author:Yang, G;Xiao, M;Alam, M;Huang, YM


Abstract:The heterogeneous network (HetNet) is a key enabler to largely boost network coverage and capacity in the forthcoming 5G and beyond. To support the explosively growing mobile data volumes, wireless communications with millimeter-wave (mmWave) radios have attracted massive attention, and is widely considered as a promising candidate in 5G HetNets. In this article, we give an overview on the end-to-end latency of HetNets with mmWave communications. In general, it is rather challenging to formulate and optimize the delay problem with buffers in mmWave communications, since conventional graph-based network optimization techniques are not applicable when queues are considered. Toward this end, we develop an adaptive low-latency strategy, which uses cooperative networking to reduce the end-to-end latency. Then we evaluate the performance of the introduced strategy. Results reveal the importance of proper cooperative networking in reducing the end-to-end latency. In addition, we have identified several challenges in future research for low-latency mmWave HetNets.
2. Speed Tracking Based Energy-Efficient Freight Train Control Through Multi-Algorithms Combination

Author:Yang, J;Jia, LM;Fu, YX;Lu, SF


Abstract:Based on the characteristics of freight train control, which are nonlinear, time-delay, with multi-constraint and multiobjective, this paper focuses on speed tracking problem. Firstly, in a gradual process, a multi-modal fuzzy PID (MM-FPID) control algorithm is presented on the basis of a brief analysis of PI and PID control, which is generally used to train control in active services. Secondly, in order to deal with the time-delay problem of freight train, the paper adopts an approach of traction force feed-forward, which greatly improves the dynamic performance of the controller. Thirdly, for the overspeed brake problem caused by speed overshoot, the strategy of adaptive traction force limitation is adopted, and we get satisfactory results without increasing the safety speed margin. Fourthly, inspired by the selflearning characteristic of neural networks (NNs), an integrated controller of MM-FPID and NNs is proposed. Finally, with the help of a computer simulation platform, the paper puts forward a set of simulations, comparing the MM-FPID and the integrated control method with classical PID and fuzzy control. The results show that both MM-FPID and the integrated controller has satisfactory control effect, and their multi-modal structure makes it easy to fit different applications well, while the integrated controller has more potential in self-learning.
3. Minimum-Backflow-Power Scheme of DAB-Based Solid-State Transformer With Extended-Phase-Shift Control

Author:Shi, HC;Wen, HQ;Chen, J;Hu, YH;Jiang, L;Chen, GP;Ma, JM


Abstract:As key component for the flexible dc distributed power system, the dual active bridge (DAB)-converter-based solid-state transformer (SST) with high efficiency for a wide operating range is essential. However, with the traditional phase-shift control, high backflow power and current stress will significantly affect the conversion efficiency. In this paper, the backflow power characteristics in both sides of DAB-based SST converters are comprehensively analyzed. On this basis, complete transmission power, backflow power, and peak current mathematical models are established. Then, a minimum-backflow-power-based extended-phase-shift control strategy is proposed with the determination of optimal phase-shift pairs by using the Karush-Kuhn-Tucker function for various scenarios. The backflow power and current stress curves with different algorithms are compared. It shows the proposed control can improve the output power regulation flexibility, minimize the backflow power, and improve the efficiency in wide operating range. Finally, a DAB-based SST prototype was developed and the experimental results verified the effectiveness of the proposed control strategy.
4. Multi-source social media data sentiment analysis using bidirectional recurrent convolutional neural networks

Author:Abid, F;Li, C;Alam, M


Abstract:Subjectivity detection in the text is essential for sentiment analysis, which requires many techniques to perceive unanticipated means of communication. Few accomplishments adapted to capture the syntactic, semantic, and contextual sentimental information via distributed word representations (DWRs)(1). This paper, concatenating the DWRs through a weighted mechanism on Recurrent Neural Network (RNN) variants joint with Convolutional Neural network (CNN) distinctively involving weighted attentive pooling (WAP)(2). Whereas, CNNs with traditional pooling operations comprise many layers merely able to capture enough features. Our considerations empower the sentiment analysis over DWRs contains Word2vec, FastText, and GloVe to produce dense efficient concatenated representation (DECR)(3) to hold long term dependencies on a single RNN layer acquired by Parts of Speech Tagging (POS) explicitly with verbs, adverbs, and noun only. Then use these representations gained in a way, inputted to CNN contain single convolution layer engaging WAP on multi-source social media data to handle the issues of syntactic and semantic regularities as well as out of vocabulary (OOV) words. Experimentations demonstrate that DWRs together with proposed concatenation qualified in resolving the mentioned issues by moderate hyper-parameter configurations. Our architecture devoid of stacking multiple layers achieved modest accuracy of 89.67%% by DECR-Bi-GRU-CNN (WAP) on IMDB as compared to random initialization 81.11%% on SST.
5. Electrical and Electronic Technologies in More-Electric Aircraft: A Review

Author:Ni, K;Liu, YJ;Mei, ZB;Wu, TH;Hu, YH;Wen, HQ;Wang, YG

Source:IEEE ACCESS,2019,Vol.7

Abstract:This paper presents a review of the electrical and electronic technologies investigated in more-electric aircraft (MEA). In order to change the current situation of low power efficiency, serious pollution, and high operating cost in conventional aircraft, the concept of MEA is proposed. By converting some hydraulic, mechanical, and pneumatic power sources into electrical ones, the overall power efficiency is greatly increased, and more flexible power regulation is achieved. The main components in an MEA power system are electrical machines and power electronics devices. The design and control methods for electrical machines and various topologies and control strategies for power electronic converters have been widely researched. Besides, several studies are carried out regarding energy management strategies that intend to optimize the operation of MEA power distribution systems. Furthermore, it is necessary to investigate the system stability and reliability issues in an MEA, since they are directly related to the safety of passengers. In terms of machine technologies, power electronics techniques, energy management strategies, and the system stability and reliability, a review is carried out for the contributions in the literature to MEA.
6. Fourier-transform-based two-stage camera calibration method with simple periodical pattern

Author:Chen, XC;Fan, RM;Wu, J;Song, XK;Liu, Q;Wang, YW;Wang, YJ;Tao, B


Abstract:Clear and focused pattern images are essential prerequisites for accurate feature detection in traditional camera calibration methods, which introduce numerous limitations in various areas, such as long-distance photogrammetry. A feature detection method robust against defocusing is proposed for extracting the centers or corners of a planar square periodic target. A Fourier transform is employed to calculate two wrapped phase maps from the periodic target images, which are then used to accurately extract the feature points. The calibration procedure is divided into two stages to obtain more accurate results. A rough calibration is performed to calculate the rotation angles between the target and the camera. If the tilt angle is larger than 12 degrees, the corresponding images are removed. Subsequently, the remaining images are used for precise calibration. The simulations and the experiments demonstrate that the proposed method can accurately calibrate a camera with a planar square periodic pattern, even in the case of severe defocusing.
7. E-marketing services and e-marketing performance: the roles of innovation, knowledge complexity and environmental turbulence in influencing the relationship

Author:Chong, WK;Bian, D;Zhang, N


Abstract:The business-to-business electronic marketplace (e-marketplace) is becoming critical for small- and medium-sized enterprises (SMEs). However, which e-marketing services determine a firm's e-marketing performance and how innovation, knowledge complexity and environmental turbulence influence the relationship between e-marketing services and e-marketing performance are under-researched topics in the field. We first empirically tested 176 SMEs from China to evaluate which e-marketing services are significantly related to e-marketing performance and how these services collectively influence the performance. Then, we used an NK model to examine how innovation, knowledge complexity and environmental turbulence mediate/moderate the relationship. The results show that five e-marketing services (e-CRM, e-SCM, e-competitiveness, IS/IT integration and information transparency) can greatly influence e-marketing performance; innovation positively mediates the relationship between e-marketing services and performance; and knowledge complexity and environmental turbulence positively moderate the relationship.
8. Multi-Step Short-Term Power Consumption Forecasting with a Hybrid Deep Learning Strategy

Author:Yan, K;Wang, XD;Du, Y;Jin, N;Huang, HC;Zhou, HX


Abstract:Electric power consumption short-term forecasting for individual households is an important and challenging topic in the fields of AI-enhanced energy saving, smart grid planning, sustainable energy usage and electricity market bidding system design. Due to the variability of each household's personalized activity, difficulties exist for traditional methods, such as auto-regressive moving average models, machine learning methods and non-deep neural networks, to provide accurate prediction for single household electric power consumption. Recent works show that the long short term memory (LSTM) neural network outperforms most of those traditional methods for power consumption forecasting problems. Nevertheless, two research gaps remain as unsolved problems in the literature. First, the prediction accuracy is still not reaching the practical level for real-world industrial applications. Second, most existing works only work on the one-step forecasting problem; the forecasting time is too short for practical usage. In this study, a hybrid deep learning neural network framework that combines convolutional neural network (CNN) with LSTM is proposed to further improve the prediction accuracy. The original short-term forecasting strategy is extended to a multi-step forecasting strategy to introduce more response time for electricity market bidding. Five real-world household power consumption datasets are studied, the proposed hybrid deep learning neural network outperforms most of the existing approaches, including auto-regressive integrated moving average (ARIMA) model, persistent model, support vector regression (SVR) and LSTM alone. In addition, we show a k-step power consumption forecasting strategy to promote the proposed framework for real-world application usage.
9. Comproportionation Reaction Synthesis to Realize High-Performance Water-Induced Metal-Oxide Thin-Film Transistors

Author:Liu, QH;Zhao, C;Mitrovic, IZ;Xu, WY;Yang, L;Zhao, CZ


Abstract:Solution-processed metal-oxide thin films have been widely studied in low-power and flexible electronics. However, the high temperature required to form a condensed and uniform film limits their applications in flexible and low-cost electronics. Here, a novel and environmental-friendly comproportionation reaction synthesis (CRS) is presented to obtain amorphous aluminum oxide (AlOx) thin films for solution-processed thin-film transistors (TFTs) employing water as the precursor solvent. The thermal decomposition of CRS-AlO(x)precursor is completed at approximate to 300 degrees C, which is 100 degrees C lower than that of the conventional water-induced AlOx. The morphological, optical, compositional, and electrical properties of CRS-AlO(x)dielectric films are studied systematically. Meanwhile, TFTs based on water-induced In(2)O(3)metal oxide semiconductor layers deposited on these dielectrics at low temperatures are formed and characterized. Compared with TFTs based on conventional AlO(x)showing low mobility and low clockwise hysteresis, In2O3TFTs based on CRS-AlO(x)exhibit improved electrical performance and counterclockwise hysteresis in the transfer curves. Water-induced TFTs fabricated on CRS-AlO(x)formed at a low temperature of 250 degrees C have average mobility of 98 cm(2)V(-1)s(-1). Through chemical composition characterization and electrical characterization, the high mobilities of TFTs based on CRS-AlO(x)dielectrics are correlated to trap states, which resulted in counterclockwise hysteresis in the transfer curves.
10. Minimum-Current-Stress Boundary Control Using Multiple-Phase-Shift-Based Switching Surfaces

Author:Shi, Haochen ; Wen, Huiqing ; Cao, Zhenyan ; Hu, Yihua ; Jiang, Lin

Source:IEEE Transactions on Industrial Electronics,2021,Vol.68

Abstract:The derivation and implementation of multiple-phase-shift-based switching surfaces for a dual active bridge (DAB) converter is the main focus of this article. First, the mathematical models of multiple natural switching surfaces under different operation states of DAB converters are derived, which lays the foundation to achieve a fast transient response during startup, sudden voltage reference, and load changing conditions. Moreover, in order to improve the overall performance of DAB converters systematically, a minimum-current-stress boundary control (MBC) is proposed that can reduce the inductor peak current stress and achieve fast dynamic response simultaneously by using the multiple-phase-shift-based switching surfaces. The analytical derivation of the proposed MBC is presented together with the simulation and experimental evaluations, which shows the superior performance of the proposed MBC algorithm in terms of the efficiency and dynamic response improvement under various operating conditions. © 1982-2012 IEEE.
11. Geometrically nonlinear analysis of CNT-reinforced functionally graded composite plates integrated with piezoelectric layers

Author:Zhang, SQ;Gao, YS;Zhao, GZ;Yu, YJ;Chen, M;Wang, XF


Abstract:The paper develops a geometrically nonlinear finite element model with large rotation based on the first-order shear deformation (FOSD) hypothesis for static and dynamic analyses of piezoelectric integrated carbon nanotube reinforced functionally graded (P-CNT-FG) composite structures. A constant electric field distribution through the thickness of plate is considered. An eight-node quadrilateral plate element with five mechanical degrees of freedom (DOFs) and one electric degree of freedom is developed for finite element analysis. Four typical forms of CNT distributions are included in the model, namely uniform, V-shaped, O-shaped, and X-shaped distributions. The nonlinear model considers fully geometrically nonlinear strain-displacement relations and large rotations of the shell direction of plate. Using the Hamilton's principle, a nonlinear dynamic model including dynamic and sensory equations is obtained. The proposed nonlinear model is validated by a frequency analysis of a simply supported P-CNT-FG composite plate. Furthermore, the effects of various parameters on the static and dynamic behavior are investigated, e.g. CNT-reinforcement orientation, CNT distribution, the number of laminate layers and volume fraction.
12. The Primitive Cognitive Network Process in healthcare and medical decision making: Comparisons with the Analytic Hierarchy Process

Author:Yuen, KKF


Abstract:Analytic Hierarchy Process (AHP) is increasingly applied to healthcare and medical research and applications. However, knowledge representation of pairwise reciprocal matrix is still dubious. This research discusses the related drawbacks, and recommends pairwise opposite matrix as the ideal alternative. Pairwise opposite matrix is the key foundation of Primitive Cognitive Network Process (P-CNP), which revises the AHP approach with practical changes. A medical decision treatment evaluation using AHP is revised by P-CNP with a step-by-step tutorial. Comparisons with AHP have been discussed. The proposed method could be a promising decision tool to replace AHP to share information among patients or/and doctors, and to evaluate therapies, medical treatments, health care technologies, medical resources, and healthcare policies. (C) 2013 Elsevier B.V. All rights reserved.
13. Review on Non-Volatile Memory with High-k Dielectrics: Flash for Generation Beyond 32 nm

Author:Zhao, C;Zhao, CZ;Taylor, S;Chalker, PR


Abstract:Flash memory is the most widely used non-volatile memory device nowadays. In order to keep up with the demand for increased memory capacities, flash memory has been continuously scaled to smaller and smaller dimensions. The main benefits of down-scaling cell size and increasing integration are that they enable lower manufacturing cost as well as higher performance. Charge trapping memory is regarded as one of the most promising flash memory technologies as further down-scaling continues. In addition, more and more exploration is investigated with high-k dielectrics implemented in the charge trapping memory. The paper reviews the advanced research status concerning charge trapping memory with high-k dielectrics for the performance improvement. Application of high-k dielectric as charge trapping layer, blocking layer, and tunneling layer is comprehensively discussed accordingly.
14. Interactive Learning Environment for Bio-Inspired Optimization Algorithms for UAV Path Planning

Author:Duan, HB;Li, P;Shi, YH;Zhang, XY;Sun, CH


Abstract:This paper describes the development of BOLE, a MATLAB-based interactive learning environment, that facilitates the process of learning bio-inspired optimization algorithms, and that is dedicated exclusively to unmanned aerial vehicle path planning. As a complement to conventional teaching methods, BOLE is designed to help students consolidate the concepts taught in the course and motivate them to explore relevant issues of bio-inspired optimization algorithms through interactive and collaborative learning processes. BOLE differs from other similar tools in that it places greater emphasis on fundamental concepts than on complex mathematical equations. The learning tasks using BOLE can be classified into four steps: introduction, recognition, practice, and collaboration, according to task complexity. It complements traditional classroom teaching, enhancing learning efficiency and facilitating the assessment of student achievement, as verified by its practical application in an undergraduate course "Bio-Inspired Computing." Both objective and subjective measures were evaluated to assess the learning effectiveness.
15. A Centralized Reactive Power Compensation System for LV Distribution Networks

Author:Chen, SX;Eddy, YSF;Gooi, HB;Wang, MQ;Lu, SF


Abstract:A centralized reactive power compensation system is proposed for low voltage (LV) distribution networks. It can be connected with any bus which needs reactive power. The current industry practice is to locally install reactive power compensation system to maintain the local bus voltage and power factor. By centralizing capacitor banks together, it can help to maintain bus voltages and power factors as well as reduce the power cable losses. Besides, the centralized reactive power system can be easily expanded to meet any future load increase. A reasonably sized centralized reactive power compensation system will be capable of meeting the requirements of the network and the optimization algorithm proposed in this paper can help to find this optimal size by minimizing the expected total cost (ETCH). Different load situations and their respective probabilities are also considered in the proposed algorithm. The concept of the centralized reactive power compensation system is applied to a local shipyard power system to verify its effectiveness. The results show that an optimally sized centralized reactive power system exists and is capable of maintaining bus voltages as well as reducing the power losses in the distribution network. A significant power loss reduction can be obtained at the optimal capacity of the centralized reactive power compensation system in the case study.
16. Multiview video quality enhancement without depth information

Author:Jammal, S;Tillo, T;Xiao, JM


Abstract:The past decade has witnessed fast development in multiview 3D video technologies, such as Three-Dimensional Video (3DV), Virtual Reality (VR), and Free Viewpoint Video (FVV). However, large information redundancy and a vast amount of multiview video data needs to be stored or transmitted, which poses a serious problem for multiview video systems. Asymmetric multiview video compression can alleviate this problem by coding views with different qualities. Only several viewpoints are kept with high-quality and other views are highly compressed to low-quality. However, highly compressed views may incur severe quality degradation. Thus, it is necessary to enhance the visual quality of highly compressed views at the decoder side. Exploiting similarities among the multiview images is the key to efficiently reconstruct the multiview compressed views. In this paper, we propose a novel method for multiview quality enhancement, which directly learns an end-to-end mapping between the low-quality and high-quality views and recovers the details of the low-quality view. The mapping process is realized using a deep convolutional neural network (MVENet). MVENet takes a low-quality image of one view and a high-quality image of another view of the same scene as inputs and outputs an enhanced image for the low-quality view. To the best of our knowledge, this is the first work for multiview video enhancement where neither a depth map nor a projected virtual view is required in the enhancement process. Experimental results on both computer graphic and real datasets demonstrate the effectiveness of the proposed approach with a peak signal-to-noise ratio (PSNR) gain of up to 2dB over low-quality compressed views using HEVC and up to 3.7dB over low-quality compressed views using JPEG on the benchmark Cityscapes.
17. Minimize Reactive Power Losses of Dual Active Bridge Converters using Unified Dual Phase Shift Control

Author:Wen, HQ;Su, B


Abstract:This paper proposed an unified dual-phase-shift (UDPS) control for dual active bridge (DAB) converters in order to improve efficiency for a wide output power range. Different operating modes of UDPS are characterized with respect to the reactive current distribution. The proposed UDPS has the same output power capability with conventional phase-shift (CPS) method. Furthermore, its implementation is simple since only the change of the leading phase-shift direction is required for different operating power range. The proposed UDPS control can minimize both the inductor rms current and the circulating reactive current for various voltage conversion ratios and load conditions. The optimal phase-shift pairs for two bridges of DAB converter are derived with respect to the comprehensive reactive power loss model, including the reactive components delivered from the load and back to the source. Simulation and experimental results are illustrated and explained with details. The effectiveness of the proposed method is verified in terms of reactive power losses minimization and efficiency improvement.
18. Moving shadow detection via binocular vision and colour clustering

Author:Lu, L;Xu, M;Smith, JS;Yan, YY

Source:IET COMPUTER VISION,2020,Vol.14

Abstract:A pedestrian segmentation algorithm in the presence of cast shadows is presented in this study. The novelty of this algorithm lies in the fusion of multi-view and multi-plane homographic projections of foregrounds and the use of the fused data to guide colour clustering. This brings about an advantage over the existing binocular algorithms in that it can remove cast shadows while keeping pedestrians' body parts, which occlude shadows. Phantom detection, which is inherent with the binocular method, is also investigated. Experimental results with real-world videos have demonstrated the efficiency of this algorithm.
19. MidSens'09 - International Workshop on Middleware Tools, Services and Run-Time Support for Sensor Networks, Co-located with the 10th ACM/IFIP/USENIX International Middleware Conference Preface

Author:Michiels, Sam ; Hughes, Danny

Source:MidSens'09 - International Workshop on Middleware Tools, Services and Run-Time Support for Sensor Networks, Co-located with the 10th ACM/IFIP/USENIX International Middleware Conference,2009,Vol.

20. Cascode GaN Power Device and Its Application in Wireless Power Transmission System

Author:Qian Hongtu;Zhu Yongsheng;Deng Guangmin;Liu Wen;Chen Dunjun;Pei Yi

Source:Journal of Power Supply,2019,Vol.17

Abstract:To achieve a higher power conversion efficiency, a cascode structure based on 650 V gallium nitride high electron mobility transistor(GaN HEMT) was introduced, together with its applications in wireless power transmission. From the aspect of GaN HEMT design, the effects of field plate design on capacitance and electric field were discussed through simulations. The fabricated cascode device had a leakage current of 2 muA at drain-source voltage of 650 V. At 400 V, the input capacitance C_(iss), the output capacitance C_(oss) and the reverse transfer capacitance Crss were 1 500 pF, 32 pF and 12 pF, respectively, and the dynamic on-resistance increased by about 16%%. Based on the design of this cascode device, a wireless charging prototype with operation frequency of 240~320 kHz and full-load power of 1 kW was designed and presented. Compared with the equivalent Si device, its efficiency was obviously higher within the load range of 200~1 000 W, with the peak efficiency higher than 95%%.
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