Advanced Software and Data Engineering for Secure Societies

Submission Deadline: 30 June 2019

IEEE Access invites manuscript submissions in the area of Advanced Software and Data Engineering for Secure Societies.

Advances in Information and Communication Technologies (ICT) have remodeled the way we live and work over the last few years. The use of mobile Internet technology is already widespread, with more than 1.1 billion people constantly connected to the digital world using smartphones and tablets. The digital world expands its frontiers every day to include not only systems and humans, but also physical objects. Machinery, shipments, infrastructures, and devices are being equipped with networked sensors and actuators that enable them to monitor their environment, report their status, receive instructions, and even collaborate to take appropriate actions. Social media platforms such as Facebook, Twitter, WhatsApp, etc., are progressively becoming the norm rather than exception as to the way through which people meet, socialize, communicate and work.

While such technologies promise to make our lives easier, they raise significant security challenges for modern societies. They can be misused by malicious individuals or groups to harm people or disrupt systems and services at unprecedented scale. For example, terrorist groups and organizations try to exploit popular social media to influence vulnerable people and drive them to commit terrorist attacks. In a recent denial of service attack, control was taken of millions of unsecured internet routers around the globe to flood a major DNS provider, leading to global internet outages. Hackers try repeatedly to compromise the information systems of many democratic organizations around the globe to release information about candidates and sway the opinions of voters.

The goal of this Special Section in IEEE Access is to collect recent advances, innovations and practices in software, data and knowledge engineering for building security systems, techniques and solutions with the objective of protecting our citizens, society and economy as well as our infrastructures and services, our prosperity, political stability and well-being.

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

  • Forensic-ready software and system engineering
  • Software architectures for fighting online radicalization, extremism and terrorism
  • Software architectures for fighting the dissemination of fake news
  • Data mining and machine learning applied to cyber security
  • Data protection in the digital space
  • Privacy protection in the cyber-physical-social space
  • Software and data architectures for the protection of critical infrastructures
  • Software and data architectures for community policing
  • Robust machine learning
  • Identification of adversarial examples
  • Protection of systems against adversarial attacks
  • Transparency for security
  • Human factors for secure software systems

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

 

Associate Editor: Mahmoud Barhamgi, Claude Bernard Lyon 1 University, France


Guest Editors:

  1. Raúl Lara-Cabrera, Autonomous University of Madrid, Spain
  2. Nobukazu Yoshioka, National Institute of Informatics, Japan
  3. Xiangliang Zhang, King Abdullah University of Science and Technology, Saudi Arabia
  4. Michael N. Huhns, University of South Carolina, USA
  5. Hoda Al Khzaimi, Center of Cyber Security, University of New York Abu Dhabi NYUAD, UAE

 

Relevant IEEE Access Special Sections:

  1. Challenges and Opportunities of Big Data Against Cyber Crime
  2. Cyber-Threats and Countermeasures in the Healthcare Sector
  3. Security Analytics and Intelligence for Cyber Physical Systems


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

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

For inquiries regarding this Special Section, please contact:  mahmoud.barhamgi@univ-lyon1.fr

 

Software Defined Networks for Energy Internet and Smart Grid Communications

Submission Deadline: 31 December 2019

IEEE Access invites manuscript submissions in the area of Software Defined Networks for Energy Internet and Smart Grid Communications.

A new network paradigm of Software Defined Networks (SDN) is being widely adapted to efficiently monitor and manage the communication networks with a global perspective. SDN has a key networking feature that separates control and data plane. Today, due to its inherent benefits, SDN has been widely applied to various networking domains including data centers, WAN, enterprise, Optical Networks, Under Water Sensor Networks (UWSN), Energy Internet (EI), and Smart Grid (SG).

Energy Internet (EI) and Smart Grid (SG) are two complementary terms. Energy Internet refers to the vision of integrating future electricity grid into the web. Smart Grid refers to the advancement of current electricity grid with the help of information and communication technologies. The key feature that distinguishes EI from the SG is its tight coupling of EI with the Internet. One might argue that EI is the advanced form of Smart Grid. Nevertheless, as both EI and SG technologies differ in various ways, especially in terms of implementation and applications, there are fundamental research questions that are yet to be addressed. In a traditional Internet scenario, organizations have local area networks (LANs). These small LANs are from the small geographical areas such as cites and are connected together to form  Metropolitan Area Networks (MANs), which are then inter-connected together to form  Wide Area Networks (WANs). Likewise, in an EI scenario, a world-wide energy-Wide Area Network (e-WAN) is composed of networked regional small-scale energy-Local Area Networks (e-LANs). Similar to a network router in the traditional Internet, we have an e-router in the EI, which is responsible for  power delivery and information forwarding.

In order to realize full functionality of EI and SG, an efficient communication system would be essential, i.e., a networked system and infrastructure with fast reliable information flow capability, and support for good system observability and controllability. Such communication systems would facilitate the EI and SG to achieve secure, reliable, and safe power and information exchange. Therefore, SDN has an immense potential in playing a significant role in managing the overall network and communication entities for the future EI and SG systems. By adapting the concepts of SDN in the current as well as to future EI and SG systems, the efficiency and resiliency of the entire system could be significantly improved by further fueling the growth of research and industry methods in EI and SG.

Overall, the goal of this proposed Special Section in IEEE Access is to publish and capture the most recent advances and trends in the promising technologies of Energy Internet and Smart Grid, particularly from the perspective of Software Defined Networks.

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

  • Software Defined Networks for Smart Grid (SG)
  • Software Defined Networks for Energy Internet (EI)
  • SDN-based Internet of Things (IoT) for Energy Internet
  • Architectures and Protocols for SDN-based SG and EI
  • Resource Allocation Techniques for SDN-based EI and SG
  • Routing and MAC Protocols for SDN-based EI and SG
  • Renewable Energy Resources and SDN-based EI and SG
  • Performance Analysis, Testbed and Simulation Tools for SDN-based EI and SG
  • Big Data Analytics for SDN-based EI and SG
  • SDN Monitoring and Management Applications in HANs, NANs, WANs, and AMI
  • SG and EI Communication Monitoring techniques through SDN

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

 

Associate Editor:  Mubashir Husain Rehmani, TSSG, WIT, Ireland


Guest Editors:

  1. Alan Davy, TSSG, Waterford Institute of Technology, Ireland
  2. Brendan Jennings, TSSG, Waterford Institute of Technology , Ireland
  3. Zeeshan Kaleem, COMSATS, Pakistan
  4. Akhilesh Thyagaturu, Intel Mobile Communications, USA
  5. Hassnaa Moustafa, Intel Corporation, USA
  6. Al-Sakib Khan Pathan, Southeast University, Bangladesh

 

Relevant IEEE Access Special Sections:

  1. The Internet of Energy: Architectures, Cyber Security, and Applications
  2. Power Quality and Harmonics Issues of Future and Smart Grids
  3. Battery Energy Storage and Management Systems


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

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

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

 

Emerging Technologies for Device to Device Communications

Submission Deadline: 30 September 2018

IEEE Access invites manuscript submissions in the area of Emerging Technologies for Device to Device Communications.

Mobile Internet, especially mobile multimedia service, has become very popular in recent years. To support mobile multimedia applications, however, network capacity has to be dramatically enhanced. As an emerging technology, Device to Device (D2D) communications, have been considered to improve the network capacity as well as reduce the traffic on base stations by offloading traffic to be delivered among mobile devices directly or in a multi-hop manner. As a result, many types of real-time services, such as mobile multimedia services, can be well supported by the new mobile network technology.

There are still many open research issues in building up a mobile network with D2D communications. For example, the mechanisms for radio resource allocation and interference management are still in their infancy. Many researchers are working on developing testbeds and/or standardizing D2D communications. Moreover, new applications are emerging, and these applications should be well supported by D2D communications. Furthermore, new technologies, such as social networks and software-defined networks, are expected to have great impacts on the design of the network architecture, supporting D2D communications. In addition, trust and privacy issues are very important concerns to users as they affect users’ willingness to use D2D communications. Researchers have been making great efforts to solve these problems and readers of IEEE Access have keen interest in the research progress in this area.

The goal of this Special Section In IEEE Access is to report up-to-date contributions in the area of the Emerging Technologies for D2D communications.

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

  • Social-aware D2D communications
  • Software-defined D2D communications
  • Outband D2D Communications
  • Neighbor discovery for D2D communications
  • Mode selection for D2D communications
  • Resources scheduling for D2D communications
  • Interference management for D2D communications
  • Power control for D2D communications
  • Privacy preserving for D2D communications
  • Trust management for D2D communications
  • Multimedia transmission for D2D communications
  • New applications for D2D communications
  • Testbed and standardization activities for D2D communications

 

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

 

Associate Editor: Honggang Wang, University of Massachusetts Dartmouth, USA


Guest Editors:

  1. Qing Yang, University of North Texas, USA
  2. Dapeng Wu, Chongqing University of Posts and Telecommunications, China
  3. Joel Rodrigues, National Institute of Telecommunications (Inatel), Brazil; Instituto de Telecomunicações, Portugal
  4. Shaoen Wu, Ball State University, USA


Relevant IEEE Access Special Sections:

 

  1. Recent Advances on Radio Access and Security Methods in 5G Networks
  2. Advances in Interference Mitigation Techniques for Device-to-Device Communications
  3. Mobile Edge Computing


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

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

For inquiries regarding this Special Section, please contact:  hwang1@umassd.edu

 

Wirelessly Powered Networks: Algorithms, Applications and Technologies

Submission Deadline: 31 October 2018

IEEE Access invites manuscript submissions in the area of Wirelessly Powered Networks: Algorithms, Applications and Technologies.

Wireless Power Transfer (WPT) is, by definition, a process that occurs in any system where electrical energy is transmitted from a power source to a load without the connection of electrical conductors. WPT is the driving technology that will enable the next stage in the current consumer electronics revolution, including battery-less sensors, passive RF identification (RFID), passive wireless sensors, the Internet of Things and 5G, and machine-to-machine solutions. WPT-enabled devices can be powered by harvesting energy from the surroundings, including electromagnetic (EM) energy, leading to a new communication networks paradigm, the Wirelessly Powered Networks.

While recent advances in wireless utensils appear to be unlimited, the dependence of their operation on batteries remains a weakness, mainly because batteries come with a limited lifetime and require a fast charge time to achieve continuous operation. This is where the technologies of WPT become useful, bringing together wireless energy and data transmission. WPT technologies substitute the traditional powering concept, where a cable or a battery is connected to the wireless device, by the transmission of energy over the air in an efficient way to power-up the device.

Wirelessly Powered Networks have recently evolved into a very active research field, as well as a topic of rapid technological progress, emerging practical developments and standardization activities. However, a solid foundational, technological, and applied background is still necessary for Wirelessly Powered Networks to achieve their full potential. The provisioning of relevant technological models, algorithmic design and analysis methods, networking principles, circuit and system design, and application methodologies is a challenging task. This Special Section in IEEE Access invites academic and industrial experts to make their contributions on Wirelessly Powered Networks. It will selectively span a coherent, large spectrum of fundamental aspects of WPT, and will focus on three main thematic pillars and relevant themes: Algorithms, Applications and Technologies.

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

Algorithms

  • Optimization and approximation algorithms (mobility/energy/data management)
  • Joint operation scheduling (routing, data gathering, ambient harvesting)
  • Precise algorithmic models and efficient distributed protocols
  • WPT devices deployment
  • Safety provisioning through EM radiation control algorithms
  • Peer-to-peer and crowd charging algorithms
  • Algorithms for simultaneous wireless information and power transfer (SWIPT)

Applications

  • Medical implants and wearable devices
  • Automotive technology and electric vehicles
  • Mobile communications, wireless sensor networks and UAVs
  • Spacecraft engineering
  • Home/Industrial appliances
  • Standardization, regulations and biological effects
  • Solutions for SWIPT

Technologies

  • RF energy harvesting, rectennas and rectenna arrays
  • High-frequency rectifying circuits, power transmitters and devices
  • Near-field (inductive, resonant) energy transfer
  • Microwave transmission and beaming
  • Novel materials, fabrication techniques
  • Energy storage elements, RFID-related electronics and self-powered sensors
  • Measurement and characterization approaches for WPT components

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

 

Associate Editor:  Theofanis P. Raptis, National Research Council, Italy


Guest Editors:

  1. Nuno Borges Carvalho, University of Aveiro, Portugal
  2. Diego Masotti, University of Bologna, Italy
  3. Lei Shu, Nanjing Agricultural University, China / University of Lincoln, UK
  4. Cong Wang, Old Dominion University, USA
  5. Yuanyuan Yang, Stony Brook University, USA


Relevant IEEE Access Special Sections:

 

  1. Energy Efficient Wireless Communications with Energy Harvesting and Wireless Power Transfer
  2. Exploiting the Benefits of Interference in Wireless Networks: Energy Harvesting and Security
  3. Energy Harvesting and Scavenging: Technologies, Algorithms, and Communication Protocols


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

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

For inquiries regarding this Special Section, please contact:  theofanis.raptis@iit.cnr.it

 

Healthcare Information Technology for the Extreme and Remote Environments

Submission Deadline: 10 April 2019

IEEE Access invites manuscript submissions in the area of Healthcare Information Technology for the Extreme and Remote Environments.

IEEE Access invites manuscript submissions in the area of Healthcare Information Technology for Extreme and Remote Environments (HITERE). Extreme and rural medicine means having to treat health issues in the most challenging and sometimes inhospitable environments. It can occur in places completely removed from all of the standard procedures, comforts, protocols, and technologies, or during a crisis such as floods, tsunamis, and earthquakes that result in power failures and computer inoperability.. Knowing how to deal with the unique challenges encountered saves lives and communities. Hospitals and clinicians are being challenged to do more with less, yet there are limited attempts to develop solutions and applications that work in such challenging environments. This Special Section in IEEE Access aims to provide researchers and practitioners a platform to present innovative solutions based on emerging technologies like IoT, blockchain, electronic data interchange (EDI) and wireless sensors networks.  The main focus of this Special Section is to address the current research challenges by encouraging submissions related to the advanced Healthcare Information technologies.

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

  • Architecture, models, and design for trustworthiness for Extreme Environments
  • Network and system trustworthiness
  • Data trust, device trust and user trust
  • Identity management and identity trust
  • Modeling, Simulation and Protocols for Extreme Environments
  • Backup Technologies for Extreme Environments
  • Patient data delivery over unsecured channels
  • Medical images processing for Extreme Environments
  • Robustness against Environmental changes (cryosphere, land, oceans, and atmosphere)
  • Remote sensoring, and their associated technologies
  • Smart OTA Healthcare Apps for Extreme Environments
  • OTA Telepresence
  • Survivable Systems
  • Robotics and unmanned vehicles for Extreme Environments
  • IoT and Wearables for Extreme Environments
  • Navigation and Communication Technologies for Extreme Environments
  • Cloud Computing for Extreme Environments

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

 

Associate Editor:  Sabah Mohammed, Lakehead University, Canada


Guest Editors:

  1. Tai-hoon Kim, Sungshin W. University, Korea
  2. Osvaldo Gervasi, University of Perugia, Italy
  3. Jinan Fiaidhi, Lakehead University, Canada


Relevant IEEE Access Special Sections:

 

  1. Heterogeneous Crowdsourced Data Analytics
  2. Trends and Advances for Ambient Intelligence with Internet of Things (IoT) systems
  3. Healthcare Big Data


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

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

For inquiries regarding this Special Section, please contact: sabah.mohammed@lakeheadu.ca

 

Data Mining and Granular Computing in Big Data and Knowledge Processing

Submission Deadline: 30 September 2018

IEEE Access invites manuscript submissions in the area of  Data Mining and Granular Computing in Big Data and Knowledge Processing.

Researchers continue to encounter an explosive growth in big data with high volume, variety, velocity, veracity and value. The “Five Vs” are the key features of big data, and also the causes of inherent uncertainties in the representation, processing, and analysis of big data. Data is continuously recorded in a fast sampling rate and is leading to an explosion of data volume which calls for a specific strategy to increase scalability of a computational method. Installation of various sensors make it possible for numerous variables to be captured. This issue not only results in exponential growth of data volume but also generates heterogeneous data samples of various types: images, videos, texts, sounds, etc. The benefits from the management of big data are clear: the larger the data, the higher the degree of knowledge that can be extracted from it. Therefore, data mining becomes an essential technique to process big data. Moreover, real-life big data is now available everywhere from the Internet, sensor networks, social networks, and proprietary databases. The big data mining remains an open issue for both academia and practitioners because of the issue of uncertainty caused by inaccurate measurement, faulty sensors, missing values, etc.

In the past few years, a great number of challenging problems have emerged, such as the problem of imbalanced data, multi-label and multi-instance problems, low quality and/or noisy data or semi-supervised learning, among others. In the realm of big data itself, research on big data processing still attracts a growing research interest where the main objective is to set up a scalable big data processing environment which allows one to perform efficient data collection, storage and analytics in an integrated manner.  Parallelization is among the most widely applied technique to handle big data. Instead of relying on a single node, it utilizes a distributed computational framework which makes possible for information to be segregated into a number of computational nodes and to be executed in parallel, thereby increasing scalability of big data processing and memory management of big data.  The Map Reduce, Apache Spark, Flink, etc. are some popular examples of big data analytics which adopt a parallelization scheme.

In the recent past, the evolution of research interest has focused on a relatively new area—granular computing (GrC), based on such technologies as fuzzy sets and rough sets. GrC provides a powerful tool for multiple granularity and multiple-view data analysis. It offers a promising solution to cope with the uncertainty of big data which often contains a significant amount of unstructured, uncertain and imprecise data. GrC can exhibit better capability and advantages in intelligent data analysis, pattern recognition, machine learning and uncertain reasoning for a noticeable amount of data. GrC aims to find a suitable level of granularity of given problems which can be adjusted according to the degree of fuzziness of the given problem. It refers to those advantages, and also challenges, derived from collecting and processing vast amounts of data. There are new challenges regarding the scalability of GrC when addressing very big data.

The exploration of data mining and granular computing in big data and knowledge processing is a multidisciplinary field, which crosses multiple research disciplines and industry domains, including transportation, communications, social network, medical health, and so on.

The goal of this Special Section in IEEE Access is to provide a specific opportunity to review the state-of-the-art of recent data mining and granular computing in big data and knowledge processing, and bringing together researchers in the relevant areas to discuss the latest progress, new research methodologies and potential research topics.

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

  • Latest classification algorithms and clustering algorithms for big data processing
  • Supervised/semi-supervised learning method for big data
  • Feature selection/extraction/construction/recognition for big data
  • Data streams and concept drift
  • Data mining in evolutionary computation for real-world applications
  • Large-scale biomedical image mining, assessment and analysis
  • Social network analysis and mining for big data
  • Multi-label/Multi-instance learning in big data and knowledge processing
  • Deep learning and transfer learning for big data analysis
  • Structured spare representation for large-scale image classification
  • Granular soft computing techniques for big data
  • Granular computing theory and application in big data
  • Granular data mining algorithm and application in big data
  • Granular data mining model based MapReduce/Apache Spark
  • Fuzzy granular support vector machines and application in big data
  • Big data analysis for decision-making
  • Multi-criteria knowledge-based systems
  • Evolutionary computation and hybrid systems in big data
  • Cooperation co-evolution for big data
  • Large-scale image and multimedia processing
  • Intelligent adaptive control and analysis in big data applications
  • Multi-agent systems and distributed control of big data
  • Application of data processing technology in large-scale medicine and healthcare 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: Weiping Ding, Nantong University, China


Guest Editors:

  1. Gary G. Yen, Oklahoma State University, USA
  2. Gleb Beliakov, Deakin University, Australia
  3. Isaac Triguero, University of Nottingham, United Kingdom
  4. Mahardhika Pratama, Nanyang Technological University, Singapore
  5. Xiangliang Zhang, King Abdullah University of Science and Technology, Saudi Arabia
  6. Hongjun Li, Nantong University, China


Relevant IEEE Access Special Sections:

 

  1. Recent Computational Methods in Knowledge Engineering and Intelligence Computation
  2. Advanced Big Data Analysis for Vehicular Social Networks
  3. Big Data Analytics in Internet-of-Things and Cyber-Physical System


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

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

For inquiries regarding this Special Section, please contact: dwp9988@hotmail.com

 

Cyber-Physical Systems

Submission Deadline: 31 December 2018

IEEE Access invites manuscript submissions in the area of  Cyber-Physical Systems.  

Recent years have witnessed the increasing synergy between the computational technologies and physical components. A Cyber-Physical System (CPS) is composed of a collection of devices interacting with each other and communicating with the physical world. It integrates computation and communication aspects together with control and monitoring techniques. Various CPS applications can be found in almost all areas of human life, such as manufacturing systems, smart grids, robotics, transportation systems, medical devices, military, home area networks and smart buildings, etc. 

The aim of this Special Section in IEEE Access is to discuss recent advances of the design, modeling, specification, analysis, verification and application merits of CPS. Such aspects involve interdisciplinary fields of science, thus the following wide range of topics is covered (but not limited to):

Control techniques of CPS:

      • Control systems, concurrent control systems, automatic control and robotics.
      • Distributed and networked control systems.
      • Control algorithms and methodologies.

Design, analysis and verification of CPS:

      • Design methodologies of CPS.
      • Model-based design, including Model-Driven Development, Unified Modeling Language (UML, SysML), etc.
      • Mixed-signal design.
      • Concurrency modeling and analysis, including Petri net-based systems.
      • Optimization techniques.
      • Verification and validation techniques, including formal verification methods.
      • Performance evaluation.
      • Integrated tool suits for CPS design, analysis and verification.

Software and hardware aspects of CPS:

      • Computation models, including mathematical descriptions and models.
      • Cloud computing.
      • Real-time systems, including real-time sensing and computing.
      • Embedded systems.
      • Programmable devices, including logic synthesis and implementation methods.

Networking in CPS:

      • Networked embedded systems.
      • Wireless sensor networks.
      • Internet of things, including aspects of designing, organization and implementation.

Applications of CPS:

      • Autonomous, adaptive and cooperative CPS.
      • Mobile, wearable, and implantable CPS in healthcare.
      • Cognitive CPS with perception, learning, and optimal decision making.
      • Reference architectures for various application domains.
      • Smart grids, power generation and distribution, power systems.
      • Smart cities, home area networks (HANs).
      • Manufacturing, flexible manufacturing systems, smart factories, Industry 4.0.
      • Reconfigurable control systems (including distributed and integrated systems).
      • Dependable CPS (cryptology, security algorithms, security aspects).

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

 

Associate Editor:  Remigiusz Wisniewski, University of Zielona Gora, Poland

Guest Editors:

  1. Grzegorz Benysek, University of Zielona Gora, Poland
  2. Luis Gomes, Universidade Nova de Lisboa, Portugal
  3. Dariusz Kania, Silesian University of Technology, Poland
  4. Theodore Simos, University of Peloponnese, Greece
  5. MengChu Zhou, New Jersey Institute of Technology, USA


Relevant IEEE Access Special Sections:

  1. Security Analytics and Intelligence for Cyber Physical Systems
  2. Big Data Analytics in Internet-of-Things And Cyber-Physical System
  3. Data-Driven Monitoring, Fault Diagnosis and Control of Cyber-Physical Systems


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

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

For inquiries regarding this Special Section, please contact: R.Wisniewski@iee.uz.zgora.pl

Collaboration for Internet of Things

Submission Deadline: 31 December 2018

IEEE Access invites manuscript submissions in the area of Collaboration for Internet of Things.

As the network of objects/things embedded with electronics, software, sensors, and network connectivity, Internet of Things (IoT) creates many exciting applications (e.g., smart grids, smart homes, smart cities) by enabling objects/things to collect and exchange data so that they can be sensed and controlled. To fulfill IoT, one essential step is to connect various objects/things (e.g., mobile phones, cars, buildings) so that they can “talk” to each other (i.e., collect and exchange data). However, substantial case studies show that simply connecting them without further collaboration among the objects/things when “talking” to each other leads to unnecessary energy consumption, uncertain security, unstable performance, etc., for IoT. Therefore, collaboration for IoT is very important. Specifically, there are a lot of critical issues in terms of how to perform a robust collaboration among the objects/things for IoT. For instance, how to conduct collaboration among the objects/things so that more energy-efficient communication can be achieved for IoT? How to conduct collaboration among the objects/things so that computing with higher performance can be achieved for IoT? How to improve the security of IoT with collaboration among the objects/things? How to enhance the Quality of Service of IoT with collaboration among the objects/things? How to minimize the overhead costs when objects/things are collaborating in IoT?

This Special Section solicits articles with novel contributions that address such issues regarding collaboration for IoT. Emerging technologies (e.g., fog computing, cognitive computing, software defined networks, deep learning) on collaboration for IoT are particularly welcome. 

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

  • Collaboration for communication in the Internet of Things
  • Collaboration for computing in the Internet of Things
  • Collaboration for energy consumption in the Internet of Things
  • Collaboration for security in the Internet of Things
  • Collaboration for robustness in the Internet of Things
  • Collaboration for Quality of Service in the Internet of Things
  • Fog computing for collaboration in the Internet of Things
  • Cognitive computing for collaboration in the Internet of Things
  • Software defined networks for collaboration in the Internet of Things
  • Deep learning for collaboration in the Internet of Things
  • Testbed on collaboration for the Internet of Things

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

 

Associate Editor:  Chunsheng Zhu, The University of British Columbia, Canada

Guest Editors:

  1. Vincenzo Piuri, Universita’ degli Studi di Milano, Italy
  2. Joel J. P. C. Rodrigues, National Institute of Telecommunications, Brazil; Instituto de Telecomunicações, Portugal
  3. Huansheng Ning, University of Science and Technology Beijing, China
  4. Huan Zhou, China Three Gorges University, China
  5. Zhangbing Zhou, China University of Geosciences, China


Relevant IEEE Access Special Sections:

  1. Real-Time Edge Analytics for Big Data in Internet of Things
  2. Multimedia Analysis for Internet-of-Things
  3. Convergence of Sensor Networks, Cloud Computing, and Big Data in Industrial Internet of Things


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

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

For inquiries regarding this Special Section, please contact: chunsheng.tom.zhu@gmail.com

Advanced Information Sensing and Learning Technologies for Data-centric Smart Health Applications

Submission Deadline:  28 February 2019

IEEE Access invites manuscript submissions in the area of Advanced Information Sensing and Learning Technologies for Data-centric Smart Health Applications.

Smart health is bringing vast promising possibilities on the way to pervasive health management. Smart health applications are strongly data-centric, and thus empowered by two key factors: information sensing and information learning. In a smart health system, it is crucial to effectively sense individuals’ health information, and afterwards intelligently learn from it high level health insights. These two factors are also closely coupled. For example, to enhance the signal quality, a sensing array requires advanced information learning techniques to fuse the information; and to enrich medical insights in mobile health monitoring, we need to combine ‘multimodal signal processing and machine learning techniques’ and ‘nonintrusive multimodality sensing methods’. In new smart health application exploration, challenges arise in both information sensing and learning, and especially their interaction areas.

This Special Section in IEEE Access invites academic and industrial experts to make their contributions to information sensing and learning in smart health systems. Studies are expected to build new bridges on many gaps between human subjects and their health insights, leveraging information sensing and learning technologies, such as physiological sensing, motion sensing, multimodal signal processing, health data representation techniques, machine learning, deep learning, data mining, computing platforms, and other related techniques. These technologies are required to build a whole data flow from humans to the health insights we pursue. This Special Section will allow readers to identify advancements, challenges and new opportunities in information sensing and learning for emerging smart health applications.

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

  • Physiological sensing: Heart ECG, Brain EEG, Muscle EMG, Optical PPG, Bioelectrical Impedance, etc.
  • Motion and activity sensing: movement, daily activities, behavior, etc.
  • Multichannel biomedical signal sensing and processing
  • Multimodal biomedical signal sensing and processing
  • Motion artifacts suppression techniques in wearable health monitoring
  • Data representation techniques for smart health data
  • Machine/deep learning from smart health data
  • Transfer learning applied to smart health applications with limited data
  • Time series analysis techniques using deep learning
  • Biomedical image and image processing
  • Platforms for computing intensive and/or low power smart health applications
  • Human-computer interaction for assisted living
  • Mobile health and precision medicine applications
  • Medical decision support systems
  • Wearable feedback systems for rehabilitation

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

Associate Editor:  Qingxue Zhang, Harvard University, USA

Guest Editors:

 

  1. Vincenzo Piuri, University of Milan, Italy
  2. Edward A. Clancy, Worcester Polytechnic Institute, USA
  3. Dian Zhou, University of Texas at Dallas & Fudan University, USA & China
  4. Thomas Penzel, Charite University Hospital, Germany
  5. Walter Hu, University of Texas at Dallas & One-Chip Co., Ltd., USA & China
  6. Liang Peng, Huawei Silicon Valley Center, USA

Relevant IEEE Access Special Sections:

 

  1. Mobile Multimedia for Healthcare
  2. Soft Computing Techniques for Image Analysis in the Medical Industry – Current trends, Challenges and Solutions
  3. Human-Centered Smart Systems and Technologies


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

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

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

Applications of Big Data in Social Sciences

Submission Deadline: 31 December 2018

IEEE Access invites manuscript submissions in the area of Applications of Big Data in Social Sciences.

What does Big Data mean for contemporary Social Sciences? How can velocity, variety and volume of Big Data streams be employed to gain a better understanding of complex socio-economical facts? Is Big Data a viable tool to address social problems? As data becomes more and more valuable, who will own and control access to it?

With the rapid increase of the sheer amount of social data produced and that is available, a particular recent trend for researchers from Social Sciences is to understand the potential of Big Data in complementing traditional research methods and their value in making decisions. Indeed, Big Data requires a revisit of data analysis techniques in fundamental ways at all stages from data acquisition and storage to data transformation and interpretation. In particular, the task of collecting and analyzing data — which is at the heart of the Big Data Analytics pipeline — underwent pressing (and somewhat daunting) challenges in the domain of Social Sciences. The types of available data fall into various categories: social data (e.g., Twitter feeds, Facebook likes), data about mobility and geospatial locations (e.g., sensor data collected through mobile phones or satellite images), data collected from government administrative sources and multi-lingual text datasets, only to name a few. In addition, data is often fragmented across many sources and often requires translation from one language (or specific format) to another and, in some extreme cases, a translation between different scientific disciplines is needed.

Several major issues have to be closely investigated around Big Data in Social Sciences. First, missing data is a main concern for Social Science researchers, especially for those who aim to study the effectiveness of data-driven approaches in the decision-making process. Second, social data generated from human interactions are often unreliable. Data collection processes should therefore incorporate mechanisms  to spot potential inaccuracies and quantify to what extent inaccuracies are reflected in the outcomes of the data analysis tasks. Finally, the speed at which social data is generated from humans interacting through the increasing number of platforms and the myriad of interacting devices poses several challenges for effective real-time responses.

This Special Section in IEEE Access aims at presenting the latest developments, trends, and research solutions of Big Data in Social Sciences. The topics of interest include, but are not limited to:

  • Data Heterogeneity issues in Social Sciences
  • Big Data applications and methods in Sociology, Politics, Economics
  • Novel data collection techniques for reliable Social data
  • Novel Infrastructures and architectures for data-driven social applications
  • Big Data infrastructures for Social Sciences and Humanities
  • Big Data analytics for social sciences in IoT
  • Ethical frameworks about privacy and informed consent
  • Social Media in Social Sciences and Politics
  • Using Big Data to test social theories
  • Predictive modeling of social behaviors
  • Applications concerning Big Data in Humanities and Art
  • Investigations about the impact of Big Data analytics on human behaviors
  • Programming frameworks and middleware for “agile’’ Big Data analytics
  • Machine Learning techniques for Big Data analytics in social sciences
  • Cognitive technologies for Big Data in social sciences

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

 

Associate Editor: Pasquale De Meo, University of Messina, Italy

Guest Editors:

  1. Fabrizio Messina, University of Catania, Italy
  2. Michael Sheng, Macquarie University, Australia
  3. Jianguo Yao, Shanghai Jiao Tong University (SJTU), China
  4. Giuseppe Di Fatta, University of Reading, UK

 

Relevant IEEE Access Special Sections:

  1. Cyber-Physical-Social Computing and Networking
  2. Advanced Data Analytics for Large-scale Complex Data Environments

 

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

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

For inquiries regarding this Special Section, please contact: pdemeo@unime.it