Recent Advances on Hybrid Complex Networks: Analysis and Control

Submission Deadline: 31 October 2020

IEEE Access invites manuscript submissions in the area of Recent Advances on Hybrid Complex Networks: Analysis and Control.

Due to varied complexities such as network dynamics complexity, statistical complexity and so on, some complex networks involve more than one discipline. Among network dynamics, both  impulsive effects and logical dynamics have attracted increasing attention recently. It is of interest and importance to study the complex networks with impulsive effects and logical dynamics. Note that these networks are called hybrid complex networks, which widely exist in cells, ecology, social systems and communication engineering.

In hybrid complex networks, many nodes are coupled together through networks, and their properties lead to very complex dynamic behaviors, including discrete and continuous dynamic behaviors, with both the time and state space taking finite values. The continuous parts of systems are often described by differential equations, while the discrete parts can be described by difference equations. The logical networks are usually used to model the systems where time and state space take finite values. Although interesting work has been reported on hybrid complex networks, there is some conservativeness on both the analysis method and relevant results. To be specific, conservative impulsive delay inequalities were used in some literatures and corresponding stability or synchronization criteria seem hard to check. Therefore, it is necessary to find effective approaches to break some conservativeness on both the analysis method and relevant results of hybrid complex networks.

Our proposed Special Section will provide a valuable and timely platform for the exchange of the latest advances in hybrid complex networks.

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

  • Analysis of hybrid complex networks: stability/ synchronization/ consensus/ robustness/ complexity analysis/ controllability/ observability/ nonsingularity
  • Synthesis of hybrid complex networks: stabilization/ disturbances decoupling problem/ functions perturbations/ attacks/ optimization

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

 

Associate Editor:  Jianquan Lu, Southeast University, China

Guest Editors:

    1. Daniel W. C. Ho, City University of Hong Kong, Hong Kong, China
    2. Tingwen Huang, Texas A&M University, Qatar
    3. Jürgen Kurths, Potsdam Institute for Climate Impact Research, Germany
    4. Ljiljana Trajkovic, Simon Fraser University, Canada

 

Relevant IEEE Access Special Sections:

  1. Complex Networks Analysis and Engineering in 5G and beyond towards 6G
  2. Body Area Networks
  3. Internet-of-Things Attacks and Defenses: Recent Advances and Challenges


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: jqluma@seu.edu.cn.

Lightweight Security and Provenance for Internet of Health Things

Submission Deadline: 31 October 2020

IEEE Access invites manuscript submissions in the area of Lightweight Security and Provenance for Internet of Health Things.

As an extension of the Internet of Things (IoT), the Internet of Health Things (IoHT), play an important role in the remote exchange of data of different physical processes such as patient monitoring, treatment progress, observation and consultation. In IoHT, the connectivity, integration, computation and interoperability are enabled through various sensors, actuators, and controllers, thereby providing seamless connectivity with efficient utilization of resources. In emergency situations, when a patient is being shifted to a hospital, seamless connectivity between Ambulance to Hospital (A2H), Hospital to Hospital (H2H) and Hospital to Ambulance (H2A), is very critical. With advances in tele-medicine, telesurgery, and other health-care applications, streaming has become an essential part of IoHT. The data traffic in IoHT applications, such as interactive multimedia streaming, traffic generated from faulty sensors, and vital signs, can tolerate packet loss but have stringent delay requirements. On the other hand, video streaming applications cannot tolerate jitter. Similarly, the low-power devices are sensitive to packet loss, and the periodic physiological traffic of medical traffic can tolerate delay, or jitter, but not packet loss.  Routing data in different IoHT applications has varying quality of service (QoS) requirements in terms of delay, packet loss, jitter, and throughput. Most of the algorithms used today to secure the data and cryptography techniques in IoHT contain high computational complexities with high energy consumption. However, due to the energy limitations of low-power embedded devices, traditional cryptographic solutions are not viable for most of the IoHT applications. Less computational complexity, less space acquisition and energy-efficient security primitives are key building blocks for end-to-end content protection, user authentication, and consumer confidentiality in the IoHT.  Once the data is gathered from different applications, it must be accurate and information about its origin should also be known. Due to scalability, tiny devices installed in IoHT are not usually physically protected. Data security and provenance therefore serve as the backbone for implementing IoHT applications.

This Special Section targets original technical articles with novel contributions on the improvement of security of IoHT, in particular by finding the correct lightweight solution. Review articles of high quality that provide thorough overview of the subject will also be considered. The topics of interest include, but are not limited to:

  • Lightweight security for IoHT
  • Low energy IoHT systems
  • Low energy security algorithms for A2H, H2H, and H2A in IoHT
  • Lightweight solutions for data forensics in IoHT
  • Lightweight routing algorithms for data provenance in IoHT
  • Secure lightweight protocols for A2H, H2H, and H2A in IoHT
  • Security framework and architecture for IoHT
  • Lightweight video streaming mechanism for IoHT

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

 

Associate Editor:  Muhammad Tariq, FAST National University of computer & Emerging Sciences, Pakistan and Princeton University, USA

 

Guest Editors:

    1. Takuro Sato, Waseda University, Waseda University, Tokyo, Japan
    2. Gautam Srivastava, Brandon University, Canada
    3. Vuk Marojevic, Mississippi State University, USA
    4. Mario Goldenbaum, Bremen University, Bremen, Germany

 

Relevant IEEE Access Special Sections:

  1. Secure Communication for the Next Generation 5G and IoT Networks
  2. Deep Learning: Security and Forensics Research Advances and Challenges
  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: mtariq@princeton.edu.

Challenges and Endeavors of Radiated Radio Frequency Tests for 5G Radios

Submission Deadline: 31 January 2021

IEEE Access invites manuscript submissions in the area of Challenges and Endeavors of Radiated Radio Frequency Tests for 5G Radios.

By now, we have entered the fifth generation (5G) era with intensive research and development (R&D) of various 5G applications from both industry and academia. The 5G systems promise higher spectral efficiency/energy efficiency, lower latency, and more reliable communications. These advantages are supported by millimeter wave (mmWave) and/or massive multiple-input multiple-output (M-MIMO) techniques.

Cable conducted testing has been the dominant testing method for sub-6 GHz conventional communication systems, where antenna ports are mostly accessible for conducted testing. In the conducted testing, antenna characteristics are omitted completely by testing from antenna ports.  However, for M-MIMO antenna systems with hundreds of antenna elements, conducted testing obviously becomes infeasible. Moreover, it is likely that mmWave systems will not have standard antenna ports, rendering over-the-air (OTA) the only testing solution. However, many challenges for OTA testing of 5G devices arise, e.g., the lack of antenna connectors especially at frequency region (FR) 2, the high number of antenna connectors at RF1 for base stations; the complicated and expensive system resource requirement for testing electrically large 5G devices; the time-consuming array diagnosis and calibration for M-MIMO and millimeter-wave systems; the large measurement range requirement in the test system to meet the far field assumption; the link budget issue at FR2, etc. Besides conventional antenna and radio frequency (RF) testing, it is necessary as well to test both mmWave and M-MIMO systems with appropriate channel models due to the fact that the use of beamforming and spatial filtering is sensitive to time-variant radio channel conditions.

In addition, the electromagnetic compatibility (EMC) problems of 5G systems become very serious due to the existence of complicated circuits and numerous wireless components. In practice, the EMC test needs to not only evaluate the radiated/conducted emission/susceptibility, but also identify the key sources of EMC failures. Due to the complexity of 5G systems, the identification of EMC failure source is especially challenging. Therefore, new testing solutions and post-processing techniques are needed to address the challenges of 5G EMC tests, also accounting for coexistence with existing fixed and mobile installations.

The objective of this Special Section is to address the challenges in OTA/EMC tests for 5G Technologies. The topics of interest include, but are not limited to:

  • Anechoic chamber based testing methods for 5G applications
  • Reverberation chambers based testing methods for 5G applications
  • M-MIMO antenna array diagnosis and calibration
  • Millimeter-wave antenna array diagnosis and calibration
  • Numerical modeling and simulation methods for M-MIMO systems and 5G applications
  • OTA testing of 5G base stations and terminals
  • EMC tests of 5G devices and coexisting issues
  • Virtual drive testing
  • Performance evaluation of communication systems in critical propagation scenarios
  • Progress in standardization of 5G metrology
  • Developments 5G channel model, radio channel emulator, and other testbeds for performance testing
  • OTA methods of fading emulation for demodulation and radio resource management (RRM) testing
  • OTA methods for RF performance testing
  • Uncertainty analyses for OTA/EMC tests

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

 

Associate Editor:   Wei Fan, Aalborg University, Denmark
Huapeng Zhao, University of Electronic Science and Technology of China, China

 

Guest Editors:

    1. Xiaoming Chen, Xi’an Jiao tong University, China
    2. Su Yan, Howard University, USA
    3. Pekka Kyösti, Keysight technologies and Oulu University, Finland
    4. Jukka-Pekka Nuutinen, Spirent Technologies, USA
    5. Valter Mariani Primiani, Università Politecnica delle Marche – Ancona, Italy

 

Relevant IEEE Access Special Sections:

  1. Antenna and Propagation for 5G and Beyond
  2. 5G and Beyond Mobile Wireless Communications Enabling Intelligent Mobility
  3. Millimeter-wave and Terahertz Propagation, Channel Modeling and Applications


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: wfa@es.aau.dk.

Key Enabling Technologies for Prosumer Energy Management

Submission Deadline: 31 December 2020

IEEE Access invites manuscript submissions in the area of Key Enabling Technologies for Prosumer Energy Management.

Distributed energy resources (DERs), such as photovoltaics, electric vehicles, energy storage and heat pump devices, play a central role in the energy transition from fossil fuels to renewables. The growing penetration of DERs has made it possible for traditional passive consumers to evolve into active prosumers. Compared with traditional consumers, prosumers are capable of managing their energy generation, storage and consumption simultaneously. Prosumers can not only participate in electricity market transactions, e.g., minimizing the cost of energy procurement, but also facilitate smart grid operations, e.g., providing ancillary service to power grids. With the booming development of prosumers, a prosumer energy management system is urgently needed to take full advantage of prosumers’ flexibility while taking the interests of other parties into account. In recent years, several prosumer energy management strategies have been proposed in literature, such as the peer-to-peer approach, coordinated scheduling-based scheme and centralized control method. However, these strategies have the following deficiencies: (1) they lack comprehensive analytics and intelligent control tools compatible with the existing energy management systems to reduce energy costs; (2) they do not address how to increase the prosumer profitability through improved customer segmentation; (3) they do not analyze the intrinsic revenue streams among prosumers.

To handle these deficiencies, the current energy management system needs to be rigorously re-engineered into an integrated and intelligent system that manages not only the smart grid but also the multi-energy system with couplings of electricity, thermal and natural gas networks. To this end, a large number of prosumers will actively participate in system-wide and local coordination tasks. Therefore, the modeling methods and related key enabling technologies are still hot topics that require substantial scientific research.

Research into prosumer energy management involves a wide range of disciplines, including power engineering, computer science, (micro) economics, thermal and control engineering. This Special Section will bring together researchers and practitioners to introduce and discuss key enabling technologies covering monitoring, operation, planning, marketing and control architectures related to the prosumer energy management.

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

  • Electricity market design for prosumer energy management
  • Prosumer-oriented home energy management system
  • Data management and ICT technologies to promote energy trading between prosumers
  • IoTs/Cloud based solutions for prosumer monitoring, management and control
  • Aggregation and disaggregation technologies for integrating and managing prosumers’ DERs
  • New coordinated control methodologies to integrate prosumers’ flexibility into smart grid operations
  • Automated technologies based on market behavior analysis to improve the robustness of prosumer energy management system
  • Market modeling methods based on peer to peer (P2P) energy trading and blockchain
  • Cyber physical modeling and cyber security of prosumer energy management system
  • Interactive energy management system that facilitates the prosumers’ operation
  • Transactive energy system for enabling the operation of prosumer energy management
  • Experiences and lessons learned from the field implementations
  • Renewable energy policies that can promote the development of prosumers in future smart grid
  • Standardization and new technologies that facilitate the application of prosumer energy management

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

 

Associate Editor:  Bin Zhou, Hunan University, China

Guest Editors:

  1. Nian Liu, North China Electric Power University, China
  2. Junjie Hu, North China Electric Power University, China
  3. Guangya Yang, Technical University of Denmark, Denmark
  4. Ahmad F. Taha, University of Texas, USA
  5. Huaizhi Wang, Shenzhen University, China
  6. Hugo Morais, EDF R&D Department, France
  7. Siqi Bu, The Hong Kong Polytechnic University, Hong Kong
  8. Jiayong Li, Hunan University, China

Relevant IEEE Access Special Sections:

  1. Artificial Intelligence Technologies for Electric Power Systems
  2. Emerging Technologies for Energy Internet
  3. Smart Caching, Communications, Computing and Cybersecurity for Information-Centric 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: binzhou@hnu.edu.cn.

Emerging Deep Learning Theories and Methods for Biomedical Engineering

Submission Deadline: 31 August 2020

IEEE Access invites manuscript submissions in the area of Emerging Deep Learning Theories and Methods for Biomedical Engineering.

The accelerating power of deep learning in diagnosing disease and analyzing medical data will empower physicians and speed up decision-making in clinical environments. Applications of modern medical instruments and digitalization of medical care have generated large amounts of biomedical information in recent years. However, new AI methods and computational models for efficient data processing, analysis, and modeling with the generated data is important for clinical applications and in understanding the underlying biological process.

Deep learning has rapidly developed in recent years, in terms of both methodological development and practical applications. It provides computational models of multiple processing layers to learn and represent data with various levels of abstraction. It can implicitly capture intricate structures of large-scale data and is ideally suited to some of the hardware architectures that are currently available.

The purpose of this Special Section aims to provide a diverse, but complementary, set of contributions to demonstrate new theories, techniques, developments, and applications of Deep learning, and to solve emerging problems in biomedical engineering.

The ultimate goal of this Special Section is to promote research and development of deep learning for multimodal & multidimensional signals in biomedical engineering by publishing high-quality research articles and reviews in this rapidly growing interdisciplinary field.

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

  • Theoretical understanding of deep learning in biomedical engineering
  • Transfer learning and multi-task learning
  • Joint Semantic Segmentation, Object Detection and Scene Recognition on biomedical images
  • Improvising on the computation of a deep network; exploiting parallel computation techniques and GPU programming
  • Multimodal imaging techniques: data acquisition, reconstruction; 2D, 3D, 4D imaging, etc.
  • Translational multimodality imaging and biomedical applications (e.g., detection, diagnostic analysis, quantitative measurements, image guidance of ultrasonography)
  • Optimization by deep neural networks, multi-dimensional deep learning
  • New model or new structure of convolutional neural network
  • Visualization and explainable deep neural network
  • Missing data imputation for multi-source biomedical data
  • Sparse screening, feature screening, feature merging, quality assessment for biomedical data

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

 

Associate Editor: Yu-Dong Zhang, University of Leicester, United Kingdom

Guest Editors:

    1.  Zhengchao Dong, Columbia University, USA
    2. Juan Manuel Gorriz, University of Granada, Spain
    3. Yizhang Jiang, Jiangnan University, China
    4. Ming Yang, Nanjing Medical University, China
    5. Shui-Hua Wang, Loughborough University, UK

 

Relevant IEEE Access Special Sections:

  1. Deep Learning Algorithms for Internet of Medical Things
  2. Smart Health Sensing and Computational Intelligence: From Big Data to Big Impacts
  3. Data-Enabled Intelligence for Digital Health

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:  yudongzhang@ieee.org.

Real-Time Machine Learning Applications In Mobile Robotics

Submission Deadline: 31 December 2020

IEEE Access invites manuscript submissions in the area of Real-Time Machine Learning Applications In Mobile Robotics.

In the last ten years, advances in machine learning methods have brought tremendous developments to the field of robotics. The performance in many robotic applications such as robotics grasping, locomotion, human-robot interaction, perception and control of robotic systems, navigation, planning, mapping, and localization has improved since the appearance of modern machine learning methods. In particular, deep learning methods have brought significant improvements in a broad range of robot applications, including drones, mobile robots, robotics manipulators, bipedal robots, and self-driving cars. The availability of big data and more powerful computational resources, such as Graphics Processing Units (GPUs), have made numerous robotics applications feasible that were not possible previously.

Despite recent advances, there are still gaps in applying available machine learning methods to real robots. Directly transferring algorithms that work successfully in the simulation to the real robot and self-learning of robots are among the current challenges. Moreover, there is also a need for new real-time algorithms and more explainable and interpretable models that receive and process data from the sensors such as cameras, Light Detection and Ranging (LIDAR), Inertial Measurement Unit (IMU), and Global Positioning System (GPS), preferably in an unsupervised or semi-supervised fashion.

This Special Section in IEEE Access aims to present the works relating to the design and usage of the real-time machine learning methods on all mobile robots including legged and humanoid platforms, focusing on state-of-the-art methods, such as deep learning, generative adversarial networks, scalable evolutionary algorithms, reinforcement learning, probabilistic graphical models, Bayesian methods, and explainable and interpretable approaches. The Special Section will present original research articles covering the implementations and applications of mobile robots and incorporating up-to-date results, theorems, algorithms, and systems.

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

  • Robotic learning by simulations
  • Learning and adaptive algorithms for robotic mobile manipulators and humanoid robots
  • Human-robot interaction, learning from human demonstrations
  • Learning for human-robot collaborative tasks
  • Autonomous grasping and manipulation by using mobile robots
  • Multi-robot systems, networked robots, and robot soccer
  • Control, complex action learning, and predictive learning from sensorimotor information for bio-inspired social robots
  • Autonomous driving, navigation, planning, mapping, localization, collision avoidance, and exploration
  • Robotics and autonomous system design and implementation
  • Nonlinear control and visual servoing in robotic systems
  • Soft robotics
  • Usage of sensors, such as EEG, ECG, and IMU in robotics
  • Usage of explainable machine learning and interpretable artificial intelligence in robotics

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

Associate Editor:  Aysegul Ucar, Firat University, Turkey

Guest Editors:

    1. Jessy W. Grizzle, University of Michigan, USA
    2. Maani Ghaffari Jadidi, University of Michigan, USA
    3. Mattias Wahde, Chalmers University of Technology, Sweden
    4. Levent Akin, Bogazici University, Turkey
    5. Jacky Baltes, National Taiwan Normal University, Taiwan
    6. Işıl Bozma, Bogazici University, Turkey
    7. Jaime Valls Miro, University of Technology Sydney, Australia

Relevant IEEE Access Special Sections:

  1. Advances in Machine Learning and Cognitive Computing for Industry Applications
  2. Integrative Computer Vision and Multimedia Analytics
  3. Uncertainty Quantification in Robotic Applications


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: agulucar@firat.edu.tr.

Behavioral Biometrics for eHealth and Well-Being

Submission Deadline: 28 February 2021

IEEE Access invites manuscript submissions in the area of Behavioral Biometrics for eHealth and Well-Being.

Artificial Intelligence (AI) is changing the healthcare industry from many perspectives. A very challenging issue deals with the development of non-intrusive AI technologies that could be integrated into everyday activities, thus allowing continuous health state monitoring and enabling automatic warnings when a dangerous change is predicted. Behavioral biometrics play a crucial role within this challenge. Behavioral biometrics, such as speech, handwriting, gait, etc. can be used to quantify human physiology, pathophysiological mechanisms, and actions. The final acquired signal is a mixture of at least four components:

  • The physical one, which enables the user to make the action (e.g. mouth, lips, tongue, etc.);
  • The cognitive one, which deals with mental abilities (learning, thinking, reasoning, remembering, problem-solving, decision-making, and attention);
  • The learned one, which deals with culture, habits, personalization, etc.;
  • The contingent contour one, which deals with the acquisition device, the emotional state, the specific task to be performed, etc.

It is evident that disease at its early stage, as well as during its course, could affect one or more of these components. Behavioral biometrics in eHealth seek solutions to diagnose, assess, and monitor diseases that are measurable just when the patient performs an action. This action could be walking, talking, writing or typing on a touchscreen, and many more. Behavioral biometrics also deal with the way the human being responds to natural and social events around her/him and emotions. The adoption of non-intrusive behavioral biometrics techniques in the set of daily activities would be pervasive: the user would be asked to do what she/he already does normally. The output of these systems could be provided to doctors, thus helping them in a deep disease inspection. At the same time these technologies could be directly adopted by doctors. These aspects are extremely important for the development of Computer Aided Diagnosis (CAD) tools. Nevertheless, specific behavioral biometrics tasks and activities could be planned to support rehabilitation activities.

This Special Section in IEEE Access aims to attract original research articles that advance the state of the art in behavioral biometrics for e-health and well-being. The goal is that it provides an opportunity to gain a significantly better understanding of the field’s current developments and future direction.

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

  • Signal processing techniques
  • Pattern Recognition techniques
  • Computer Vision techniques
  • Artificial Intelligence techniques
  • Continuous learning and recognition
  • Acquisition tools, procedures and protocols
  • Biometrics data mining
  • Wearable and non-intrusive sensors
  • Brain signals analysis for disease and emotional states recognition
  • Eye movement analysis for disease recognition
  • Face analysis for disease and emotional state recognition
  • Gait analysis for disease and emotional state recognition
  • Handwriting analysis for disease and emotional state recognition
  • Keystroke dynamics for disease and emotional state recognition
  • Sleep analysis for disease and emotional state recognition
  • Speech analysis for disease and emotional state recognition
  • Biometric data and clinical data fusion
  • Multiple behavioral biometrics
  • Development of complete CAD systems
  • Real-time health alerts and long-term health trend analytics
  • Applications

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

 

Associate Editor:  Donato Impedovo, University of Bari Aldo Moro, Italy

Guest Editors:

    1. Thurmon Lockhart, Arizona State University, United States
    2. Jiri Mekyska, Brno University of Technology, Czech Republic
    3. Bijan Najafi, Baylor College of Medicine, United States
    4. Toshihisa Tanaka, Tokyo University of Agriculture and Technology, Japan

 

Relevant IEEE Access Special Sections:

  1. Data-Enabled Intelligence for Digital Health
  2. Smart Health Sensing and Computational Intelligence: From Big Data to Big Impacts
  3. Data Analytics and Artificial Intelligence for Prognostics and Health Management (PHM) Using Disparate Data Streams


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: donato.impedovo@uniba.it.

Communications in Harsh Environments

Submission Deadline: 31 December 2020

IEEE Access invites manuscript submissions in the area of Communications in Harsh Environments.

Communication systems deployed in harsh environments, such as a high-speed train, subway, desert, trench, forest, or underground mining, should be specially constructed to withstand extreme conditions such as high or low temperatures, corrosive humidity, extreme weather or excessive dust and dirt. Such applications require specially designed wireless communication, fiber-optic communications, satellite communication, or signal processing techniques that can perform under extreme conditions and meet the QoS, security, and reliability requirement.

Quite often, communications in harsh environments have extremely low signal-to-noise ratio (SNR), high doppler shift, and long latency, and often consumes more power and energy. Bandwidth limitation in harsh environment requires spectrum efficient communications. The current state of art technologies such as massive MIMO, advanced modulation and channel coding, artificial intelligence, and signal processing provide different venues to explore this challenging area. The goal of the Special Section is to publish the most recent (unclassified) results of communications in harsh environments. Review articles on this topic are also welcome.

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

  • Wireless channel modeling for communications in harsh environments
  • Signal processing techniques for communications in harsh environments
  • Massive MIMO for communications in harsh environments
  • Space-time coding for communications in harsh environments
  • Information theory foundation for communications in harsh environments
  • Fiber-optic communications in harsh environments
  • Satellite communications in harsh environments
  • Ultra-wide band communications in harsh environments
  • Spectrum efficiency for communications in harsh environments
  • Energy efficiency for communications in harsh environments
  • New modulation for communications in harsh environments
  • New multiple access techniques for communications in harsh environments
  • Channel coding for communications in harsh environments
  • Artificial intelligence for communications in harsh environments
  • Sensor communications in harsh environments

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

 

Associate Editor:  Qilian Liang, University of Texas at Arlington, USA

Guest Editors:

    1. Tariq S. Durrani, University of Strathclyde, UK
    2. Xin Wang, Qualcomm Inc, USA
    3. Wei Wang, Tianjin Normal University, China
    4. Jinhwan Koh, Gyeongsang National University, Korea
    5. Qiong Wu, Amazon, USA

 

Relevant IEEE Access Special Sections:

  1. Millimeter-Wave Communications: New Research Trends and Challenges
  2. Artificial Intelligence for Physical-Layer Wireless Communications
  3. Millimeter-wave and Terahertz Propagation, Channel Modeling and Applications


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: liang@uta.edu.

Blockchain Technology: Principles and Applications

Submission Deadline: 31 January 2021

IEEE Access invites manuscript submissions in the area of Blockchain Technology: Principles and Applications.

Blockchain is a disruptive technology for building consensus and trust in a peer-to-peer network without centralized control. It was first used in bitcoin, the very first cryptocurrency released at the beginning of 2009, to implement a secure ledger of transactions. This secure ledger ensures that once a transaction is placed in the ledger, it cannot be altered without being detected, which is a prerequisite for any digital currency implementation because it must guarantee that no one can double-spend one’s money. After a quiet period, the interest on blockchain has exploded in recent years. The number publications indexed by Web of Science on blockchain increased from 2 in 2013 (the first year in which publications on blockchain started to appear), to 4 in 2014, 21 in 2015, 118 in 2016, 521 in 2017, and 1,080 in 2018.

The research and developmental activities related to blockchain technology can be roughly divided into two areas: (1) The application of the blockchain in various industry sectors, such as fintech, medicine and health, energy and power generation systems, real estate, travel, manufacturing, education, or even government; (2) Fundamental research on blockchain technology itself, such as alternative consensus algorithms that consume less energy, provide better scalability, are more robust to cyberattacks, and are more scalable. In the former area, interesting issues could arise due to the particular needs of an application. For example, blockchain could be used to secure the data produced from a sensor network. However, the amount of data could easily exceed the capacity of any current blockchain platform. For the latter area, we have seen alternative consensus algorithms being proposed, such as proof of stake, that are likely to make blockchains more scalable, secure, and robust in the long term.

This Special Section welcomes original research and review articles on all aspects of blockchain technology.

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

  • Consensus algorithms
  • Cyberattacks on blockchains
  • Economic impact on cyberattacks
  • Security and trust on permissioned blockchains
  • Scalability of blockchains
  • Reliability analysis on blockchain-based systems
  • Smart contracts
  • Visualization of blockchain data
  • Blockchain for Banking and Finance
  • Blockchain for Supply Chain
  • Blockchain for Consumer Products and Retail
  • Blockchain for Government
  • Blockchain for Automotive
  • Blockchain for Medicine and Health Care
  • Blockchain for Travel and Transportation
  • Blockchain for Internet of Things
  • Blockchain for Agriculture

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

 

Associate Editor: Wenbing Zhao, Cleveland State University, USA

Guest Editors:

    1. Chunming Rong, University of Stavanger, Norway
    2. Jun Wu, Shanghai Jiao Tong University, China
    3. Zhixin Sun, Nanjing University of Posts and Telecommunications, China
    4. Srinivas Sampalli, Dalhousie University, Canada

 

Relevant IEEE Access Special Sections:

  1. Innovation and Application of Internet of Things and Emerging Technologies in Smart Sensing
  2. Innovation and Application of Intelligent Processing of Data, Information and Knowledge as Resources in Edge Computing
  3. New Technologies for Smart Farming 4.0: Research Challenges and Opportunities


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: w.zhao1@csuohio.edu.

Evolving Technologies in Energy Storage Systems for Energy Systems Applications

Submission Deadline: 01 January 2021

IEEE Access invites manuscript submissions in the area of Evolving Technologies in Energy Storage Systems for Energy Systems Applications.

Growing concern for the increasing demand in energy and a deteriorating climate has prompted  researchers and scientists to try to think of renewable energy sources. This creates propitious opportunities in mitigating the production of greenhouse gases and fabricating innovative electrical models to make the technology accessible worldwide. However, these sources are intermittent in nature, causing discrepancies in supply and demand due to phenomena such as the production of duck curve. Energy storage systems such as batteries, flywheels and super/ultra-capacitors play vital roles in compensating such inconsistencies. Different batteries are being modeled and analyzed according to their capacity and usage in grids or industries. Battery management systems perform various analyses on miscellaneous parameters such as state of charge, state of health, depth of charge, and internal resistance to determine the quality. They furthermore implement several control schemes based on artificial intelligence or machine learning to make these batteries capable  of versatile applications. At the end of a battery’s calendar life, it can be refurbished for a second life, making it substantially more usable for numerous applications, such as powering up residences, transportation, and communication systems. Electric vehicles, being the primary source of second-life batteries, have many promising uses of energy storage systems. The standards, policies, safety concerns, business models, barriers, and possible solutions should be investigated to promote more use of second-life batteries. Proper recycling and disposal procedures should also be followed after the end of their second life, which is a matter of considerable research interest.

As the conventional electrical infrastructure is moving towards a distributed scheme, smart grids and microgrids are propagating to meet the users’ requirements.

Energy storage is of the utmost importance for distributed power systems and utility-scale applications. Storage systems largely affect the plans of load leveling, load shifting, and energy arbitrage in power systems. New electric models of power electronic devices in these systems are making grid-tied technologies possible, facilitating the designs of state-of-the-art storage systems. As power and energy density vary in distributed systems, different storage devices fulfill one of the criteria for grid resiliency. This is where hybrid energy storage systems come into play, combining different devices of alternate features for improved steady and transient characteristics. Along with the existing storage technologies, several advanced battery schemes such as solid-state batteries and thin-film Li-ion batteries are studied to make future contributions in the field of energy storage systems.

This Special Section in IEEE Access will target numerous prospects in evolving technologies in energy storage systems for energy systems applications. We invite both review and research articles in order to represent ingenious technologies related to the domain, which would make our Special Section more resourceful.

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

  • Roles of different energy storage systems in Energy System applications
  • Parametric analysis and electric modeling of energy storage systems
  • Design of power electronic devices in the domain of energy storage
  • Prospects of energy storage systems in electric vehicles
  • Planning of utility scale energy storage
  • Roles of energy storage schemes in distributed power systems
  • Battery management systems and their control strategies
  • Trends and potentialities of second life batteries
  • Alternative and hybrid energy storage systems
  • Future of energy storage systems and advanced battery technologies

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

 

Associate Editor: Eklas Hossain, Oregon Institute of Technology, USA

Guest Editors:

    1. Sanjeevikumar Padmanaban, Aalborg University, Denmark
    2. Moin Hanif, Higher Colleges of Technology, UAE and University of Johannesburg, South Africa
    3. Ramazan Bayindir, Gazi University, Turkey
    4. Ryan Mayfield, Mayfield Renewables, USA

 

Relevant IEEE Access Special Sections:

  1. Addressing Challenging Issues of Grids with High Penetration of Grid Connected Power Converters: Towards Future and Smart Grids
  2. Emerging Technologies for Energy Internet
  3. Advances in Machine Learning and Cognitive Computing for Industry Applications


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: eklas.hossain@oit.edu.