Visual Perception Modeling in Consumer and Industrial Applications

Submission Deadline: 31 May 2020

IEEE Access invites manuscript submissions in the area of Visual Perception Modeling in Consumer and Industrial Applications.

In recent literature, various visual perception mechanisms have been modeled to facilitate the relevant consumer and industrial applications, from low-level visual attention to higher-level quality of experience, object detection, and recognition. Specifically, visual attention can help us handle massive amounts of visual information efficiently, and visual attention modeling can help us simulate such visual attention mechanisms and focus on more salient information. Since the ultimate receiver of the processed signal is often human, the receiver’s perception of the overall quality is also very important, and quality perception modeling can help control the whole processing chain and guarantee a good perceptual quality of experience. Due to the rapid advancement of machine learning techniques, higher-level perception modeling related to semantics also becomes possible. How to utilize the most recent big data and learning techniques to interpret and model visual perception also becomes a problem. What’s more, a growing number of advanced multimedia technologies have become available over the last decade, such as High dynamic range (HDR) imaging, virtual reality (VR), augmented reality (AR), mixed reality (MR), and light field imaging. Visual perception modeling for such advanced multimedia technologies also needs further research. This Special Section solicits novel and high-quality articles to present reliable solutions and technologies of the above-mentioned problems.

The topics of interest include, but are not limited to:

  • Visual perception modeling for various consumer and industrial applications
  • Visual attention modeling, including the mechanism of visual attention, visual saliency prediction and the utilization of visual attention models in relevant applications
  • Visual quality of experience modeling, including visual quality assessment, control, and optimization for consumer electronics and industrial applications
  • Advanced learning technologies, such as deep learning, random forests (RF), multiple kernel learning (MKL), and their applications in visual perception modeling
  • Statistical analytics and modeling based on big data (cloud) for images, videos or other formats of industrial data
  • Emerging multimedia technologies, such as virtual reality (VR), augmented reality (AR), 4-dimensional (4-D) light fields, and high dynamic range (HDR), including visual perception modeling for these emerging technologies and their use in industry

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility and downloads of articles.

 

Associate Editor: Guangtao Zhai, Shanghai Jiao Tong University, China

Guest Editors:

    1. Xiongkuo Min, The University of Texas at Austin, USA
    2. Vinit Jakhetiya, Indian Institute of Technology (IIT), Jammu, India
    3. Hamed Rezazadegan Tavakoli, Aalto University, Finland
    4. Menghan Hu, East China Normal University, China
    5. Ke Gu, Beijing University of Technology, China

 

Relevant IEEE Access Special Sections:

  1. Recent Advances in Video Coding and Security
  2. Biologically inspired image processing challenges and future directions
  3. Integrative Computer Vision and Multimedia Analytics


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: zhaiguangtao@sjtu.edu.cn.

Polymeric Materials for HVDC Insulation

Submission Deadline: 31 May 2020

IEEE Access invites manuscript submissions in the area of Polymeric Materials for HVDC Insulation.

High voltage direct current (HVDC) power transmission plays a key role in the global power grid today and in the future, particularly for high-capacity, long-distance, and regional power grid interconnections. With the high voltage level of the HVDC power system, the most important concern is the operating safety of polymeric materials as well as solutions for HVDC insulation. During polarity reversal and over-voltages on the HVDC system, polymeric insulation can break down in cables, cable accessories, apparatus bushings and gas insulated switchgears. The issues regarding polymeric materials which include the DC conductivity, charge transportation and partial discharge, have become key problems in restraining the development of the HVDC power system.

The topics of interest include, but are not limited to:

  • Characterization of polymeric material for HVDC insulation including electrical, physical and chemical analysis
  • Flashover and tracking phenomenon in HVDC GIS&GIL and outdoor insulator
  • Partial discharge and breakdown in HVDC bushing
  • Electrical tree development and breakdown processes in HVDC insulation materials
  • Surface charge, space charge and interfacial charge in HVDC insulation materials
  • Ageing and life expectancy of HVDC insulation materials
  • Nanotechnologies and nanodielectrics for HVDC insulation materials
  • New materials for HVDC insulation
  • Environmentally friendly polypropylene cable

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility and downloads of articles.

 

Associate Editor:  Boxue Du, Tianjin University, China

Guest Editors:

    1. George Chen, University of Southampton, UK
    2. Hulya Kirkici, University of South Alabama, USA

 

Relevant IEEE Access Special Sections:

  1. Advanced Energy Storage Technologies and Their Applications
  2. Emerging Technologies for Energy Internet
  3. Intelligent and Cognitive Techniques for Internet of Things


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: duboxue@tju.edu.cn.

Intelligent Biometric Systems for Secure Societies

Submission Deadline: 30 September 2020

IEEE Access invites manuscript submissions in the area of Intelligent Biometric Systems for Secure Societies.

Recent discourse in security domains points to the emergence of intelligent biometric systems as some of the most potent authentication systems for government agencies, border surveillance, anomaly detection, and medical data protection. New and emerging biometric research spurred scientific debate and empowered innovations in on-line security, e-banking, healthcare, and collaborative spaces, to name a few.  This Special Section on Intelligent Biometric Systems for Secure Societies in  IEEE  Access  will  focus  on  novel  biometrics  knowledge  representation  theories, methodologies, applications and technological implementations, aimed towards ensuring smarter, safer and more secure societies. Particular emphasis will be put on real-world and industrial applications supported by experimental or empirical studies.

The topics of interest include, but are not limited to:

  • Intelligent biometric-based authentication protocols
  • Intelligent biometric system architectures
  • Biometric-based identity and trust management
  • Cloud-based biometric identification
  • Cognitive biometric systems
  • Biometric intelligence from social media
  • Social behavioral biometrics
  • Machine learning and deep learning for biometrics
  • Multi-modal biometrics
  • Information fusion for reliable decision-making
  • Biometric-based digital rights management
  • Quality of biometric data
  • Security of biometric databases
  • Biometrics and online security
  • Biometric template protection and privacy
  • Mobile biometrics
  • Biometrics-based healthcare
  • Emerging biometrics

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility and downloads of articles.

 

Associate Editor:  Marina L. Gavrilova, University of Calgary, Canada

Guest Editors:

    1. Gee-Sern Jison Hsu, National Taiwan University of Science and Technology, Taiwan
    2. Khalid Saeed, Bialystok University of Technology, Poland
    3. Svetlana Yanushkevich, University of Calgary, Canada

 

Relevant IEEE Access Special Sections:

  1. Advanced Data Mining Methods for Social Computing
  2. Distributed Computing Infrastructure for Cyber-Physical Systems
  3. Emerging Approaches to Cyber Security


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: mgavrilo@ucalgary.ca.

New Advances in Blockchain-Based Wireless Networks

Submission Deadline: 31 December 2020

IEEE Access invites manuscript submissions in the area of New Advances in Blockchain-Based Wireless Networks.

Blockchain, as a game changer for ultra-secured and efficient digital society, has been gaining ever-increasing attention far beyond its initial application in digital currencies. One of the most fascinating topics currently is how to characterize the privacy and security in blockchain-based wireless networks. On the one hand, modern wireless communication systems are suffering from a wide range of security threats. On the other hand, traditional security operations such as encryption and protocol design are becoming increasingly incompetent for guaranteed reliability and safety in contemporary wireless networks. Against this background, providing effective blockchain proposals for efficient and secure transactions in modern wireless networks emerges as a pressing research issue both in academia and industry.

Although there have been some legacy algorithms and techniques which can prevent the disclosure of private information as well as the destruction of wireless links, such as AES encryption and beamforming in 5G networks, they may not be effective in a wide range of applications which are important to people in different specialty areas. As a matter of fact, venerability scanning has revealed a series of weaknesses in different layers of existing wireless networks. This motivates researchers in wireless security related areas to develop effective solutions to prevent the wireless systems from being hacked and/or damaged. From this point of view, our proposed Special Section will provide a valuable and timely platform for the exchange of the latest advances in this area.

A tremendous effort has been devoted to protecting privacy and security in wireless networks. Apart from many cryptography and security protocols, there has been solid work on enforcing industry standards such as the 3rd Generation Partnership Project (3GPP) and government policies (e.g., the IMT-2020 and 802.11) to grant individuals control over their own security operations. These techniques and policies aim to block the illegal disclosure of secured communication to a certain extent but may be incompetent for secured wireless transmissions at all times.

This Special Section solicits high-quality contributions that focus on the design and development of novel algorithms, technologies, and tools to address the security and privacy issues towards blockchain-based wireless networks.

The topics of interest include, but are not limited to:

  • New network architectures for blockchain systems
  • Performance evaluation in blockchain-based wireless networks
  • Network management in blockchain-based wireless networks
  • Privacy-aware secured protocols for blockchain-based wireless networks
  • Privacy and security in physical, link and network layer transmission for blockchain-based wireless networks
  • Heterogeneous cooperation techniques for blockchain-based wireless networks
  • Resource allocation and scheduling in blockchain-based wireless networks
  • Physical layer security in blockchain-based wireless networks
  • Cognitive and sensing techniques for blockchain-based wireless networks
  • Artificial intelligence assisted techniques for blockchain-based wireless networks
  • Routing techniques for blockchain-based wireless networks
  • Hybrid encryption techniques for blockchain-based wireless networks
  • Cross layer operations in blockchain-based wireless networks
  • Information theory and related signal processing techniques for blockchain theories, models and applications
  • Smart contracts in wireless networks
  • Semantic blockchain & knowledge-based blockchain in digital world

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility and downloads of articles.

Associate Editor:  Yuan Gao, Tsinghua University, China

Guest Editors:

    1. Zhipeng Cai, Georgia State University, USA
    2. Yunchuan Sun, Beijing Normal University, China
    3. Ruidong Zhang, University of Wisconsin – Eau Claire, China
    4. Lei Zhang, University of Glasgow, UK
    5. Muhammad Zeeshan Shakir, University of the West of Scotland, UK
    6. Hamed Ahmadi, University of York, UK

 

Relevant IEEE Access Special Sections:

 

  1. Blockchain-Enabled Trustworthy Systems
  2. Secure Communication for the Next Generation 5G and IoT Networks


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: yuangao08@tsinghua.edu.cn.

Gigapixel Panoramic Video with Virtual Reality

Submission Deadline: 15 August 2020

IEEE Access invites manuscript submissions in the area of Gigapixel Panoramic Video with Virtual Reality.

Panoramic video is also known as a Panoramic Video Loop, in which traditional static photos are replaced by more dynamic representations. As a counterpart of the image stitching, panoramic video can provide more information and improve the quality of digital entertainment. Unlike a typical rectangular video that shows only the front view of a scene, gigapixel panoramic video captures omni-directional lights from the surrounding environment. This allows a viewer to interactively look around the scene, possibly providing a strong sense of presence. This potential change of the viewing paradigm arising from the use of gigapixel panoramic vides has attracted much attention from the industry and the general public. Panoramic video streaming services are now available through companies such as YouTube and Facebook, and head-mounted display devices such as Samsung Gear VR and Oculus Rift, which support 360-degree viewing, are starting to be more commonly used. In the fields of virtual reality and augmented reality, content creators have constructed gigapixel panoramic video in order to deliver stories with more visually immersive experiences than previously possible.

Although constructing image panoramas by assembling multiple photos from a shared viewpoint is a well-studied problem, it is still difficult to construct large-scale panoramic video. Generally, the key step for constructing gigapixel panoramic video is to stitch unsynchronized videos into a large-scale dynamic panorama. The processing of gigapixel panoramic video construction involves several stages including video stabilization, dynamic feature tracking, vignetting correction, gain compensation, loop optimization, color consistency and image blending. At present, all existing panoramic video devices use tiled multiscale image structures to enable viewers to interactively explore the captured image stream. Size, weight, power and cost of the devices are central challenges in gigapixel panoramic video.

This Special Section aims to review the latest results of image panorama techniques and devices in gigapixel panoramic video construction, as well as their applications. We hope that the Special Section will also help researchers exchange the latest technical progress in the field.

The topics of interest include, but are not limited to:

  • Gigapixel panoramic video loops
  • Gigapixel image stitching
  • Video stabilization for gigapixel video panorama
  • Gain compensation
  • Color consistency for gigapixel panoramic video
  • Image blending for gigapixel panoramic video
  • Vignetting correction for gigapixel panoramic video
  • Loop optimization for gigapixel panoramic video
  • Gigapixel panoramic video for virtual reality
  • Gigapixel panoramic video for augmented reality
  • Novel devices for producing Gigapixel panoramic video
  • Novel approaches to gigapixel panoramic video-based content creation
  • Super-resolution for Gigapixel image/video

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility and downloads of articles.

 

Associate Editor:  Zhihan Lv, University of Barcelona, Spain

Guest Editors:

    1. Shangfei Wang, School of Computer Science and Technology, China
    2. Rong Shi, Facebook, USA
    3. Neeraj Kumar, Thapar Institute of Engineering and Technology, India

 

Relevant IEEE Access Special Sections:

  1. Recent Advances in Video Coding and Security
  2. Advanced Optical Imaging for Extreme Environments
  3. Biologically inspired image processing challenges and future directions


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: lvzhihan@gmail.com.

Human-driven Edge Computing (HEC)

Submission Deadline: 01 September 2020

IEEE Access invites manuscript submissions in the area of Human-driven Edge Computing (HEC).

The advent of Fifth Generation (5G) and Internet of Things (IoT) is expected to  make it possible to collect and disseminate information for various crowd-sensing services in densely populated environments. It will also result in greater demand for these services, with the rapid evolution of artificial intelligence and edge computing, which provides cloud computing and cache capabilities to reduce the computational load of cellular networks, the edges of such networks. However, the costs for deployment and maintenance of Mobile Edge Computing (MEC) are still high. Human-driven Edge Computing (HEC) is a novel model which integrates the elements of Humans, Devices, Internet and Information, and combines the power of MEC architecture and the large-scale sensing ability of Mobile Crowd-sensing (MCS). There is a great deal of research interest, from both academia and industry, on how to improve data spreading methods and environmental coverage in smart cities based on HEC. Although the study of human-driven edge computing for 5G and IoT is attractive, there are still many issues, such as fusion analysis, efficient resource usage, low latency communication, large-scale search, and data security and privacy. The objective of this Special Section is to present a collection of high-quality research articles to report the latest research advances addressing the related challenges and limitations in the area of human-driven edge computing.

The topics of interest include, but are not limited to:

  • Cognitive inspired HEC
  • New model, architecture and framework of HEC
  • Computation offloading in HEC
  • Resource allocation and management in HEC
  • Data harvesting, fusion and analytics
  • Fusion analysis and computing
  • Large-scale data search and recommendation
  • Deep learning and data mining in HEC
  • AI Hardware Accelerators in HEC
  • Emerging AI techniques and their combination with MEC
  • Energy-efficient and low-latency communication and computation
  • Novel QoS and QoE improvement techniques
  • Security and privacy challenges
  • Application and case studies of HEC for 5G and IoT
  • Novel techniques and future perspective in HEC

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor: Rongbo Zhu, South-Central University for Nationalities, China

Guest Editors:

    1. Lu Liu, University of Leicester, UK
    2. Ashiq Anjum, University of Derby, UK
    3. Maode Ma, Nanyang Technological University, Singapore
    4. Shiwen Mao, Auburn University, USA

 

Relevant IEEE Access Special Sections:

  1. Communication and Fog/Edge Computing Towards Intelligent Connected Vehicles (ICVs)
  2. Information Centric Wireless Networking with Edge Computing for 5G and IoT
  3. Innovation and Application of Intelligent Processing of Data, Information and Knowledge as Resources in Edge Computing


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: rbzhu@mail.scuec.edu.cn.

Body Area Networks

Submission Deadline: 30 July 2020

IEEE Access invites manuscript submissions in the area of body area networks, wireless sensors networks, medical ICT, intelligent health management, and big data analysis.

Wearable communications and personal health management are the future trends of the healthcare industry. To make this happen, new technologies are required to provide trustable measurement and communication mechanisms, from the data source to medical health databases. Wireless body area networks (WBAN) are the focus of this Special Section, not just on-body devices, but also technologies providing information from inside the body. Dependable communications combined with accurate localization and behavior analysis will benefit WBAN technology and make healthcare processes more effective.

The topics of interest include, but are not limited to:

  • Wearable computing
  • Embedded devices and medical applications
  • In-, on- and off-body communications & networking
  • Antennas and propagation
  • Security and privacy of health data communications
  • Smart BAN for social inclusion
  • Socio-economic aspects of health caring
  • Medical device regulation
  • Human bond communications
  • Remote patient management and preventive care
  • Radio coexistence and interference management
  • Rehabilitation and activity monitoring
  • Wellness and sport applications of body area networks
  • ICT solutions for health and wellness education
  • Molecular communications
  • WBANs supporting cognitive impairments

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor:  Lorenzo Mucchi, University of Florence, Italy

Guest Editors:

    1. Matti Hämäläinen, University of Oulu, Finland
    2. Massimiliano Pierobon, University of Nebraska-Lincoln, USA
    3. Diep Nguyen, University of Technology Sydney, Australia
    4. Hirokazu Tanaka, Hiroshima Hiroshima City University, Dept. of Biomedical Information Sciences

 

Relevant IEEE Access Special Sections:

  1. Wearable and Implantable Devices and Systems
  2. Molecular Communication Networks
  3. Advances of Multisensory Services and Technologies for Healthcare in Smart Cities


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: lorenzo.mucchi@unifi.it.

Trends and Advances in Bio-Inspired Image-Based Deep Learning Methodologies and Applications

Submission Deadline: 31 October 2020

IEEE Access invites manuscript submissions in the area of Trends and Advances in Bio-Inspired Image-Based Deep Learning Methodologies and Applications.

Many of the technological advances we enjoy today have been inspired by biological systems due to their ease of operation and outstanding efficiency. Designing technological solutions based on biological inspiration has become a cornerstone of research in a variety of areas ranging from control theory and optimization to computer vision, machine learning and artificial intelligence. Especially in the latter few areas, biologically relevant solutions are becoming increasingly important as we look for new ways to make artificial systems more efficient, intelligent and overall effective.

It is generally acknowledged that the human brain is a multitude of times more efficient than the best artificial intelligence algorithms and machine learning models available today. This suggests that there is still something fundamental to learn from the way the brain processes information and new (biologically-inspired) ideas are needed to devise a more effective form of computation capable of competing with the efficiency of biological systems.

One of the hottest and most active research topics in the field of machine learning and artificial intelligence right now is deep learning. Deep learning models exhibit a certain kind of biological relevance, but differ significantly from what we see in the human brain in their structure and efficiency, and the way they process information. Deep learning models, such as convolutional neural networks, consist of several processing layers that represent data at multiple levels of abstraction. Such models are able to implicitly capture the intricate structures of large-scale data and are closer in terms of information processing mechanisms to biological systems than earlier so-called shallow machine learning models.

However, despite the recent progress in deep learning methodologies and their success in various fields, such as computer vision, speech technologies, natural language processing, medicine, and the like, it is obvious that current models are still unable to compete with biological intelligence. It is, therefore, natural to believe that the state of the art in this area can be further improved if bio-inspired concepts are integrated into deep learning models.

The purpose of the Special Section is to present and discuss novel ideas, research, applications and results related to techniques of image processing and computer vision approaches based on bio-inspired intelligence and deep learning methodologies. It aims to bring together researchers from various fields to report the latest findings and developments in bio-inspired image-based intelligence, with a focus on deep learning methodologies and applications, and to explore future research directions.

The topics of interest include, but are not limited to, image-based methodologies, applications, and techniques such as:

  • Bio-inspired deep model architectures
  • Theoretical understanding of bio-inspired deep architectures, models and loss functions
  • Novel bio-inspired training approaches for deep learning models
  • Effective and scalable bio-inspired parallel algorithms to train deep models
  • Bio-inspired deep learning techniques for modeling sequential (temporal) data
  • Biologically relevant adaptation techniques for deep models
  • End-to-end bio-inspired deep learning solutions
  • Bio-inspired model design
  • Bio-inspired visualizations and explanations of deep learning
  • Applications of bio-inspired deep approaches in various domains

Note that “bio-inspired” is a crucial keyword in the above list. Thus, the submissions are expected to include a discussion about the bio-inspired background of the presented method. The authors must explain how their method and its novelty correlate with what we find in nature and/or organisms, brain, psychology and similar.

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor:  Peter Peer, University of Ljubljana, Slovenia

Guest Editors:

    1. Carlos M. Travieso-González, University of Las Palmas de Gran Canaria, Spain
    2. Vijayan K. Asari, University of Dayton Vision Lab, USA
    3. Malay K. Dutta, Dr. A.P.J. Abdul Kalam Technical University, India

 

Relevant IEEE Access Special Sections:

  1. Deep Learning: Security and Forensics Research Advances and Challenges
  2. Scalable Deep Learning for Big Data
  3. Deep Learning Algorithms for Internet of Medical Things


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: peter.peer@fri.uni-lj.si.

Intelligent Logistics Based on Big Data

Submission Deadline: 20 May 2020

IEEE Access invites manuscript submissions in the area of Intelligent Logistics Based on Big Data.

The advent of the era of big data and the rapid development of e-commerce have provided a new development direction for the modern logistics industry, prompting the logistics industry to think more about data. In addition, the operation mode has gradually changed from the traditional extensive mode to the intelligent logistics one, characterized by information, data, sharing and intelligence.

Intelligent logistics based on big data has significantly improved the intelligence level of warehousing, transportation and distribution, including the intelligent location of logistics outlets, the optimal configuration of transportation routes, the highest loading rate of transportation vehicles, and the optimal distribution of the last mile, which can be used to explore greater potential business value through massive logistics data analysis.

The goal of this Special Section in IEEE Access is to provide a specific opportunity to review the state-of-the-art of intelligent logistics in big data, and bring together researchers in the relevant areas to share the latest progress, novel methodologies and potential research topics.

The topics of interest include, but are not limited to:

  • Design and development of intelligent logistics system
  • Data collection and knowledge management for intelligent logistics based on Big Data
  • Analysis of intelligent logistics mode based on Big Data
  • Development of smart logistics systems using Big Data
  • Emergency logistics modeling and optimization based on Big Data
  • Optimal design of manufacturing/remanufacturing logistics network
  • Data-driven-based intelligent logistics management methods & technologies
  • Internet-of-things-based intelligent logistics design and optimization
  • Environment analysis of reverse logistics based on Big Data
  • Modeling of network design for intelligent logistics using Big Data

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor:  Zhiwu Li, Macau University of Science and Technology, Macau

Guest Editors:

    1. Guangdong Tian, Shandong University, China
    2. Di Wu, Hunan University, China
    3. MengChu Zhou, New Jersey Institute of Technology, Newark, USA
    4. Feng Chu, Univeristy of Paris-Saclay and University of Evry, France

 

Relevant IEEE Access Special Sections:

  1. Applications of Big Data in Social Sciences
  2. AI-Driven Big Data Processing: Theory, Methodology, and Applications
  3. Urban Computing and Intelligence


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: systemscontrol@gmail.com.

Energy Harvesting Technologies for Wearable and Implantable Devices

Submission Deadline: 31 December 2020

IEEE Access invites manuscript submissions in the area of Energy Harvesting Technologies for Wearable and Implantable Devices.

Implantable and wearable electronic devices can improve the quality of life as well as the life expectancy of many chronically ill patients, provided that certain biological signs can be accurately monitored. Thanks to advances in packaging and nanofabrication, it is now possible to embed various microelectronic and micromechanical sensors (such as gyroscopes, accelerometers and image sensors) into a small area on a flexible substrate and at a relatively low cost. Furthermore, these devices have been integrated with wireless communication technologies to enable the transmission of both signals and energy.  However, to ensure that these devices can truly improve a patient’s quality of life, new preventative, diagnostic and therapeutic devices that can provide hassle-free, long-term, continuous monitoring will need to be developed, which must rely on novel energy harvesting solutions that are non-obstructive to their wearer.  So far, research in the field has focussed on materials, new processing techniques and one-off devices. However, existing progress is not sufficient for future electronic devices to be useful in any new application and a great demand exists towards scaling up the research towards circuits and systems. A few interesting developments in this direction indicate that special attention should be given towards the design, simulation and modeling of energy harvesting techniques while keeping system integration and power management in mind.

The topics of interest include, but are not limited to:

  • Novel piezoelectric, thermoelectric and photovoltaic energy harvesting technologies that lead to enhanced efficiency and controllability under standard or varying working conditions
  • Novel control strategies for achieving maximum or optimum energy harvesting
  • Power management circuits for energy harvesters
  • Novel data driven techniques for optimizing and forecasting the amount of energy that can be harvested
  • Low-Power circuits and sensors
  • Flexible sensors, circuits and energy harvesters for wearables
  • Implantable electronics
  • Novel wireless power transfer and delivery techniques
  • Numerical and computational modeling techniques

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor: Hadi Heidari, University of Glasgow, UK

Guest Editors:

    1. Mehmet Ozturk, North Carolina State University, USA
    2. Rami Ghannam,University of Glasgow, UK
    3. Law Man Kay, University of Macau, China
    4. Hamideh Khanbareh, University of Bath, UK
    5.  Abdul Halim Miah, University of Florida, USA

 

Relevant IEEE Access Special Sections:

  1. Smart Health Sensing and Computational Intelligence: From Big Data to Big Impacts
  2. Neural Engineering Informatics
  3. Wearable and Implantable Devices and Systems


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact:  hadi.heidari@glasgow.ac.uk.