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Innovation, Research and Development in engineering Education. Activities of the Spanish Chapter of the IEEE Education Society: Directive Board of the IEEE Education Society Spanish Chapter 2020-2021

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Innovation, Research and Development in Engineering Educatio...

Technologies Applied to Electronics Teaching (TAEE)

作者： Ó scar Martí nez Bonastre Cristina Ferná ndez Lluí s Vicent Francisco Mur Manuel Castro Gabriel Diaz Jose Carpio Elio Sancristobal Sergio Martin Jose Sá nchez Francisco Javier Arcega Solsona Juan Suardiaz Muro Manuel Caeiro-Rodrí guez Martí n Llamas Inmaculada Plaza Baltasar Ferná ndez Manjó n Pedro Muñ oz-Merino Edmundo Tovar Telmo Zarraonandia Ayo Javier Garcia Zubia José Antonio Delgado Pení n Department of Statistics Mathematics and Computing Science Operations Research Centre Universidad Miguel Hern&#x00E1 ndez Elche Spain Department of Electronic Technology Universidad Carlos III de Madrid Madrid Spain UPF Barcelona School of Management Barcelona Spain Department of Electrical Electronic and Control Engineering UNED Madrid Spain Department of Electrical Engineering Universidad de Zaragoza Zaragoza Spain Department of Automatics Electrical Engineering and Electronic Technology Technical University of Cartagena Cartagena Spain atlanTTic Research Center University of Vigo Vigo Spain Department of Electronics and Communication Universidad de Zaragoza Zaragoza Spain Department of Software Engineering and Artificial Intelligence Complutense University of Madrid Madrid Spain Department of Telematic Engineering Universidad Carlos III de Madrid Madrid Spain Department of Computer Languages and Systems and Software Engineering Universidad Polit&#x00E9 cnica de Madrid Madrid Spain Department of Computer Science and Engineering Universidad Carlos III de Madrid Madrid Spain Department of Electronic Engineering Universidad de Deusto Bilbao Spain Universitat Polit&#x00E8 cnica de Catalunya Barcelona Spain

ISBN: (数字)9781665421614

ISBN: (纸本)9781665421621

The Technical Committee of the CESEI (Spanish Chapter of the IEEE Education Society) is focused on the Innovation, Research and Development (I+R+D) of the education in engineering, mainly Electric and Computer engineering. As in other interdisciplinary fields, the I+R+D involves several sources of information and different stakeholders, each one with its own focus and purpose. As a result, sometimes it may be complex for practitioners and researchers to identify the more appropriate entities for their interests. This paper shows how the CESEI Technical Committee tries to solve this difficulty by providing updated information regarding the main publications (journals), events (conferences) and awards to the best academic works. The paper focuses special attention on the activities held during 2020–2021.

关键词： Technological innovation Collaboration Stakeholders engineering education Research and development

Face hallucination with finishing touches

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arXiv 2020年

作者： Zhang, Yang Tsang, Ivor W. Li, Jun Liu, Ping Lu, Xiaobo Yu, Xin The School of Automation Southeast University Nanjing210096 China The Australian Artificial Intelligence Institute University of Technology Sydney UltimoNSW2007 Australia The Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Singapore138634 Singapore The Research School of Engineering Australian National University Canberra Australia

Obtaining a high-quality frontal face image from a low-resolution (LR) non-frontal face image is primarily important for many facial analysis applications. However, mainstreams either focus on super-resolving near-frontal LR faces or frontalizing non-frontal high-resolution (HR) faces. It is desirable to perform both tasks seamlessly for daily-life unconstrained face images. In this paper, we present a novel Vivid Face Hallucination Generative Adversarial Network (VividGAN) for simultaneously super-resolving and frontalizing tiny non-frontal face images. VividGAN consists of coarse-level and fine-level Face Hallucination Networks (FHnet) and two discriminators, i.e., Coarse-D and Fine-D. The coarse-level FHnet generates a frontal coarse HR face and then the fine-level FHnet makes use of the facial component appearance prior, i.e., fine-grained facial components, to attain a frontal HR face image with authentic details. In the fine-level FHnet, we also design a facial component-aware module that adopts the facial geometry guidance as clues to accurately align and merge the frontal coarse HR face and prior information. Meanwhile, two-level discriminators are designed to capture both the global outline of a face image as well as detailed facial characteristics. The Coarse-D enforces the coarsely hallucinated faces to be upright and complete while the Fine-D focuses on the fine hallucinated ones for sharper details. Extensive experiments demonstrate that our VividGAN achieves photo-realistic frontal HR faces, reaching superior performance in downstream tasks, i.e., face recognition and expression classification, compared with other state-of-the-art methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Generative adversarial networks

SPAHN novel approach for PL-AG gateway discovery for internet connectivity

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Peer-to-Peer Networking and Applications 2020年第4期14卷 2275-2284页

作者： Kannan, K. Sivaranjani, P. Sathish Kumar, S. Nalini, M. Balaji, V. R. Sanjeevi, P. Department of ECE R.M.K. College of Engineering and Technology Chennai India Department of Electronics and communication Engineering Kongu Engineering College Erode India Dept of Electrical and Electronics Engineering M. Kumarasamy College of Engineering Thalavapalayam India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of ECE Sri Krishna College of Engineering and Technology Coimbatore India Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Jiangnan University Wuxi China

Internet Gateway(IGW) main role is detecting availability nodes and providing internet to Mobile Ad Hoc Network(MANET) have whenever connected to internet. Discovery time of gateway is changed based on the throughput and packet delay. Many of the situations the mobile nodes are have fixed host connection to the internet using minimum hop path, it is not good for waiting packets because of that packets are have longer path interface queue. This research paper object is avoided above the problem mentioning using a novel approach of SPAHN (Solving Problem of Ad-Hoc Network). This paper mainly focus is classify the routing protocols of load-aware in MANET and from this classify discover the proactive load-aware gateway (PL-AG) from a device into interface queue size and min-hop-metric. This novel approach has been allowing and gives better handoff between two internet gateways for fixed host seamless connectivity. We justify the performance of the SPAHN approach using two metrics like average end-to-end delay and throughput based on this examination the SPAHN system yield good simulation results comparably existing systems.

关键词：

Characterizing human collective behaviours of COVID-19 in Hong Kong

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arXiv 2022年

作者： Du, Zhanwei Zhang, Xiao Wang, Lin Yao, Sidan Bai, Yuan Tan, Qi Xu, Xiaoke Pei, Sen Xiao, Jingyi Tsang, Tim K. Liao, Qiuyan Lau, Eric H.Y. Wu, Peng Gao, Chao Cowling, Benjamin J. WHO Collaborating Centre for Infectious Disease Epidemiology and Control School of Public Health Li Ka Shing Faculty of Medicine The University of Hong Kong Hong Kong Laboratory of Data Discovery for Health Hong Kong Science and Technology Park New Territories Hong Kong Department of Genetics University of Cambridge CambridgeCB2 3EH United Kingdom Singapore College of Information and Communication Engineering Dalian Minzu University Dalian China Department of Environmental Health Sciences Mailman School of Public Health Columbia University New YorkNY10032 United States Northwestern Polytechnical University Xi'An China

People are likely to engage in collective behaviour online during extreme events, such as the COVID-19 crisis, to express their awareness, actions and concerns. Hong Kong has implemented stringent public health and social measures (PHSMs) to curb COVID-19 epidemic waves since the first COVID-19 case was confirmed on 22 January 2020. People are likely to engage in collective behaviour online during extreme events, such as the COVID-19 crisis, to express their awareness, actions and concerns. Here, we offer a framework to evaluate interactions among individuals' emotions, perception, and online behaviours in Hong Kong during the first two waves (February to June 2020) and found a strong correlation between online behaviours of Google search and the real-time reproduction numbers. To validate the model output of risk perception, we conducted 10 rounds of cross-sectional telephone surveys from February 1 through June 20 in 2020 to quantify risk perception levels over time. Compared with the survey results, the estimates of the risk perception of individuals using our network-based mechanistic model capture 80% of the trend of people's risk perception (individuals who worried about being infected) during the studied period. We may need to reinvigorate the public by engaging people as part of the solution to live their lives with reduced risk. © 2022, CC BY-NC-ND.

关键词： Risk perception

Fire Detection based on Convolutional Neural Networks with Channel Attention

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Fire Detection based on Convolutional Neural Networks with C...

Chinese Automation Congress (CAC)

作者： Xiaobo Zhang Kun Qian Kaihe Jing Jianwei Yang Hai Yu School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education of China Future Science & Technology Park Beijing China Global Energy Interconnection Research Institute State Grid Nanjing China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

The existing research on fire detection is basically based on a two-stage method, resulting in slower detection speed, and the positioning accuracy is limited by the first-stage candidate region extraction algorithm. In order to solve the problem of high-precision real-time fire detection, this paper proposes a Yolo detection network combined with attention mechanism. The attention module is serially added to the final three convolutional networks of different scales of Yolo v3. The channel attention module updates the feature map by weighting and summing all channels, which captures the semantic dependencies between channels in the deep layers of the network, and improves the generalization ability of the model. Experiments show that the method proposed in this paper improves the accuracy of fire detection without reducing the detection speed.

关键词： Fires Semantics Feature extraction Annotations Image color analysis Deep learning Cameras

A Driver Fatigue Recognition Algorithm Based on Spatio-Temporal Feature Sequence 12

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A Driver Fatigue Recognition Algorithm Based on Spatio-Tempo...

12th International Congress on Image and Signal Processing, BioMedical engineering and Informatics, CISP-BMEI 2019

作者： Zhang, Chen Lu, Xiaobo Huang, Zhiliang Xia, Shudong Fu, Changqing School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China Beijing PKU TransInfo Technology Co. Ltd Beijing100193 China

ISBN: (纸本)9781728148526

Researches show that fatigue driving is one of the important causes of road traffic accidents, so it is of great significance to study the driver fatigue recognition algorithm to improve road traffic safety. In recent years, with the development of deep learning, the field of pattern recognition has made great development. This paper designs a real-time fatigue state recognition algorithm based on spatio-temporal feature sequence, which can be mainly applied to the scene of fatigue driving recognition. The algorithm is divided into three task networks: face detection network, facial landmark detection and head pose estimation network, fatigue recognition network. Experiments show that the algorithm has the advantages of small volume, high speed and high accuracy. © 2019 IEEE.

关键词： Face recognition

Copy and Paste GAN: Face Hallucination From Shaded Thumbnails

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Copy and Paste GAN: Face Hallucination From Shaded Thumbnail...

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Yang Zhang Ivor W. Tsang Yawei Luo Chang-Hui Hu Xiaobo Lu Xin Yu School of Automation Southeast University China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University China Centre for Artificial Intelligence University of Technology Sydney Australia School of Computer Science and Technology Huazhong University of Science and Technology China Southeast University Nanjing China Australian Centre for Robotic Vision Australian National University Australia

ISBN: (数字)9781728171685

ISBN: (纸本)9781728171692

Existing face hallucination methods based on convolutional neural networks (CNN) have achieved impressive performance on low-resolution (LR) faces in a normal illumination condition. However, their performance degrades dramatically when LR faces are captured in low or non-uniform illumination conditions. This paper proposes a Copy and Paste Generative Adversarial Network (CPGAN) to recover authentic high-resolution (HR) face images while compensating for low and non-uniform illumination. To this end, we develop two key components in our CPGAN: internal and external Copy and Paste nets (CPnets). Specifically, our internal CPnet exploits facial information residing in the input image to enhance facial details; while our external CPnet leverages an external HR face for illumination compensation. A new illumination compensation loss is thus developed to capture illumination from the external guided face image effectively. Furthermore, our method offsets illumination and upsamples facial details alternatively in a coarse-to-fine fashion, thus alleviating the correspondence ambiguity between LR inputs and external HR inputs. Extensive experiments demonstrate that our method manifests authentic HR face images in a uniform illumination condition and outperforms state-of-the-art methods qualitatively and quantitatively.

关键词： Face Lighting Gallium nitride Image resolution Feature extraction Generative adversarial networks Automation

Dynamical control of Quantum Heat Engines Using Exceptional Points

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arXiv 2022年

作者： Zhang, J.-W. Zhang, Jian-Qi Ding, G.-Y. Li, J.-C. Bu, J.-T. Wang, B. Yan, L.-L. Su, S.-L. Chen, L. Nori, F. Özdemir, S.K. Zhou, F. Jing, H. Feng, M. State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics Wuhan Institute of Physics and Mathematics Innovation Academy of Precision Measurement Science and Technology Chinese Academy of Sciences Wuhan430071 China Research Center for Quantum Precision Measurement Guangzhou Institute of Industry Technology Guangzhou511458 China School of Physics University of the Chinese Academy of Sciences Beijing100049 China School of Physics Zhengzhou University Zhengzhou450001 China Theoretical Quantum Physics Laboratory RIKEN Cluster for Pioneering Research Saitama 351-0198 Japan Physics Department The University of Michigan Ann ArborMI48109-1040 United States Department of Engineering Science and Mechanics Materials Research Institute Pennsylvania State University University Park State College PA16802 United States Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control Ministry of Education Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China Synergetic Innovation Academy for Quantum Science and Technology Zhengzhou University of Light Industry Zhengzhou450002 China

A quantum thermal machine is an open quantum system coupled to hot and cold thermal baths. Thus, its dynamics can be well understood using the concepts and tools from non-Hermitian quantum systems. A hallmark of non-Hermiticity is the existence of exceptional points where the eigenvalues of a non-Hermitian Hamiltonian or an Liouvillian superoperator and their associated eigenvectors coalesce. Here, we report the experimental realisation of a single-ion heat engine and demonstrate the effect of the Liouvillian exceptional points on the dynamics and the performance of a quantum heat engine. Our experiments have revealed that operating the engine in the exact- and broken-phases, separated by a Liouvillian exceptional point, respectively during the isochoric heating and cooling strokes of an Otto cycle produces more work and output power and achieves higher efficiency than executing the Otto cycle completely in the exact phase where the system has an oscillatory dynamics and higher coherence. This result opens interesting possibilities for the control of quantum heat engines and will be of interest to other research areas that are concerned with the role of coherence and exceptional points in quantum processes and in work extraction by thermal *** Codes 80A05, 37B55, 81P40 © 2022, CC BY.

关键词： Otto cycle

Copy and paste GAN: Face hallucination from shaded thumbnails

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arXiv 2020年

作者： Zhang, Yang Tsang, Ivor W. Luo, Yawei Hu, Changhui Lu, Xiaobo Yu, Xin School of Automation Southeast University China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University China Centre for Artificial Intelligence University of Technology Sydney Australia School of Computer Science and Technology Huazhong University of Science and Technology China School of Automation Nanjing University of Posts and Telecommunications China Australian Centre for Robotic Vision Australian National University Australia

Existing face hallucination methods based on convolutional neural networks (CNN) have achieved impressive performance on low-resolution (LR) faces in a normal illumination condition. However, their performance degrades dramatically when LR faces are captured in low or non-uniform illumination conditions. This paper proposes a Copy and Paste Generative Adversarial Network (CPGAN) to recover authentic high-resolution (HR) face images while compensating for low and nonuniform illumination. To this end, we develop two key components in our CPGAN: internal and external Copy and Paste nets (CPnets). Specifically, our internal CPnet exploits facial information residing in the input image to enhance facial details;while our external CPnet leverages an external HR face for illumination compensation. A new illumination compensation loss is thus developed to capture illumination from the external guided face image effectively. Furthermore, our method offsets illumination and upsamples facial details alternately in a coarse-to-fine fashion, thus alleviating the correspondence ambiguity between LR inputs and external HR inputs. Extensive experiments demonstrate that our method manifests authentic HR face images in a uniform illumination condition and outperforms state-of-the-art methods qualitatively and quantitatively. Copyright © 2020, The Authors. All rights reserved.

关键词： Generative adversarial networks