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.

Internet-of-Things Attacks and Defenses: Recent Advances and Challenges

Submission Deadline: 30 September 2020

IEEE Access invites manuscript submissions in the area of Internet-of-Things Attacks and Defenses: Recent Advances and Challenges.

The Internet of Things (IoT) technology has been widely adopted by the vast majority of businesses and is influencing every aspect of the world. However, the nature of the Internet, communication, embedded OS and backend recourses make IoT objects vulnerable to cyber attacks. In addition, most standard security solutions designed for enterprise systems are not applicable to IoT devices. As a result, we are facing a big IoT security and protection challenge, and it is urgent to analyze IoT-specific cyber attacks, and design novel and efficient security mechanisms.

The objective of the Special Section is to compile recent developments and efforts dedicated to research IoT attacks and defenses. The main purpose of this Special Section is to provide both academic and industry researchers with a forum to discuss either practical or theoretical solutions to identify IoT vulnerabilities and relevant security mechanisms. For this purpose, we encourage original research articles related to this topic, as well as high-quality review articles describing the current state of the art.

This Special Section will mainly focus on IoT-related attacks and defenses across IoT networks and devices.

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

  • Malware and unwanted software for IoT
  • Vulnerability analysis and reverse engineering for IoT
  • IoT security and privacy
  • IoT forensic techniques
  • Usable security and privacy for IoT
  • Intrusion detection and prevention for IoT
  • Cyber intelligence techniques for IoT
  • IoT infrastructures and mitigation techniques
  • IoT Hardware security
  • Cyber physical systems security
  • Adversarial learning for IoT
  • IoT Cyber crime
  • Denial-of-Service attacks for IoT
  • Security measurement for IoT
  • IoT security visualization techniques
  • Edge/Fog computing attack and defense
  • Trust models and management
  • Phishing and spam prevention

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

 

Associate Editor:  Weizhi Meng, Technical University of Denmark, Denmark

Guest Editors:

    1. Javier Lopez, University of Malaga, Spain
    2. Shouhuai Xu, University of Texas at San Antonio, USA
    3. Chunhua Su, University of Aizu, Japan
    4. Rongxing Lu, University of New Brunswick, Canada

 

Relevant IEEE Access Special Sections:

  1. Security and Trusted Computing for Industrial Internet of Things
  2. Internet-of-Things (IoT) Big Data Trust Management
  3. Security and Privacy in Applications and Services for Future 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: weme@dtu.dk.

Geometric Algebra in Signal Processing

Submission Deadline: 02 October 2020

IEEE Access invites manuscript submissions in the area of Geometric Algebra in Signal Processing.

Geometric algebra (GA) is the proper algebra to handle geometric elements and their transformations. It is a coherent body of concepts and methods that works for any dimension, and has great algebraic and algorithmic power, but is fundamentally simple. Since these features are lacking in the currently taught geometric methods at any level, there are strong reasons to see geometric algebra as the geometric language of choice for the 21st century and to strive for its wide acceptance in education and research.

This Special Section on geometric algebra in signal processing is intended to help bridge the gap between geometric algebra and signal processing research communities by providing a forum for high-quality research articles that explore challenges faced in this overlap. The Special Section is an opportunity to foster increased dialogue between these research communities and encourage new and exciting avenues of research that span across them.

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

  • Applications of GA to image processing
  • Applications of GA to medical images
  • Applications of GA to wireless networks
  • Applications of GA to computer vision
  • Applications of GA to artificial neural networks
  • Applications of GA to image understanding
  • Applications of GA to target tracking
  • Applications of GA to intelligent vision systems
  • Applications of GA to multimedia
  • Applications of GA to deep learning
  • Applications of GA to communication

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

 

Associate Editor: Wenming Cao, Shenzhen University, Shenzhen, China

Guest Editors:

    1. Zhihai He, Missouri University, USA
    2. Mylène C.Q. Farias, University of Brasília (UnB), Brasília – DF, Brazil
    3. Guitao Cao, East China Normal University, China
    4. Guoping Qiu, University of Nottingham, Nottingham, UK
    5. Daquan Feng, Shenzhen University, Shenzhen, China

 

Relevant IEEE Access Special Sections:

  1. Soft Computing Techniques for Image Analysis in the Medical Industry – Current trends, Challenges and Solutions
  2. Emerging Trends, Issues and Challenges for Array Signal Processing and Its Applications in Smart City
  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: wmcao@szu.edu.cn.