Journal Information
Connection Science
http://www.tandfonline.com/toc/ccos20/current
Impact Factor:
0.673
Publisher:
Taylor & Francis
ISSN:
0954-0091
Viewed:
6004
Tracked:
1

Call For Papers
Connection Science is an interdisciplinary scientific and technical journal that has, since 1989, been a focus for research on connectionist modelling and neural network learning in both living and artificial systems with an emphasis on cognition and AI. Papers on these traditional themes are still strongly encouraged. However, in 2002, in response to exciting new work in evolutionary methods and adaptive robotics, its scope was broadened to include computational research on all biologically inspired adaptive mechanisms as well as all areas of biologically inspired robotics research.
 
Papers submitted to the journal may be of a practical nature including, but not restricted to, new adaptive methods, novel implementations of existing methods as well as empirical work that has a strong modelling or theoretical component in psychology, biology, neuroscience or biologically inspired robotics. Submissions may also be theoretical or philosophical. Review papers are welcomed and authors are encouraged to consult with the Editor-in-Chief if they are considering a submission.
Last updated by Dou Sun in 2020-05-05
Special Issues
Special Issue on Intelligent Data Analytics for Internet of Underwater Things
Submission Date: 2020-08-31

Water bodies including oceans and lakes cover one-third of the earth's surface. Due to the frequent changes in the underwater environment like ocean temperature, carbon sink, sea-level rise, coastal erosion, etc., incorporating periodic monitoring of change detection is essential. The recent advances in wireless sensing technologies have made considerable changes in the exploration and monitoring of underwater resources. This includes interconnecting the Internet of Things (IoT) with underwater objects which leads to a new paradigm called the Internet of Underwater Things (IoUT). Using IoUT a network of physical devices is created which enables underwater data collection with improved communication. The data sensed through various devices are analyzed and used for research, and decision-making in many fields such as defense, coastal environment protection, consumer market, fishing & aquaculture industry. However, to support the IoUT concept, an effective underwater wireless sensor network system should be equipped with sensor nodes and smart sensing devices. Some of the smart interconnected underwater objects that can be employed for data analytics are from autonomous underwater vehicles, navigation ships, buoys, underwater robots, etc. The management of an extensive amount of raw data sensed by the underwater objects is to be analyzed. Also, the data generated from the underwater objects are real-time, which increases implemental difficulties for analyzing the data due to its enormous volume and variety. Combining IoUT and data analytics provides potential growth in monitoringunderwater by consistently giving insightful calculations for a variety of data. With the continuous increase of real-time and heterogeneous data, the analysis process becomes crucial in case of accurate prediction. Also, there may be sensitive information which is to be analyzed in the process and can end up in irreversible damages to the existing system and environment. Using the intelligent application with IoUT overcomes problems related to sensitive information and other prerequisites. Since Intelligent Data Analytics is an interdisciplinary study concerned with intelligent analysis of huge data, it provides a timely prediction for any critical underwater situation. Furthermore, Intelligent Data Analytics also extracts necessary data captured by the IoUT based sensors and helps in identifying insightful information. Such insightful information is powerful for underwater researchers, government & non-governmental organizations, and professionals actively seeking to better manage underwater resources. This special issue on “Intelligent Data Analytics for Internet of Underwater Things” will independently focus on providing an arena to share the authentic works related to the intelligent data analytic methods, techniques and technologies with application of internet of underwater things. Topics of interest include but are not restricted to: Intelligent data analytics architecture for the Internet of Underwater Things Intelligent Control Algorithm and Dynamic Management Scheme for Underwater IoT Applications Future Intelligent Underwater Network and System Architectures Artificial Life and Swarm Intelligence for Underwater Applications Intelligent Learning approaches for modeling of Internet of Underwater Things applications AI and Big data analytics for Internet of Underwater Things A Study of Intelligent Techniques for Control of Underwater Disasters Intelligent prediction models for the near-future Internet of Underwater Things AI Technology for Underwater Robots Intelligent Search and Optimization Methods in Underwater Applications Recent Advances in Intelligent Data Analytics and Internet of Underwater Things Privacy-Preserving and Security Approaches for Intelligent Data Analytics Intelligent Sensing, Data Interpretation, and Interpretation of Data from Multiple IoUT Sources
Last updated by Dou Sun in 2020-05-05
Special Issue on Big Data, IoT and Cloud Computing for Smart system
Submission Date: 2020-09-30

In recent years the combination of three distinct disciplines such as Big data, Internet of Things (IoT), and Cloud Computing are becoming more interdependent to each other in day to day activities of our lives. These technologies are advanced forms of sensors and data processing solutions. Here, IoT is a connection of multiple devices or network of devices which can collect and transfer data between them. Since IoT generates a huge amount of data from several connected devices, to manage the data complexities big data-based ecosystem can be utilized. Whether the data is organized or unorganized, the huge volumes of streaming or static data can be processed using big data techniques. Furthermore, to increase the computing capacity of this complex data rapidly, the use of cloud computing comes into the picture; it can store, process, and analyze huge volumes of data with an added advantage of sharing and accessing the information more securely from anywhere across the globe. When Big Data, IoT and Cloud Computing is used as an integrated concept in building a smart environment, a rapid increase in the overall efficiency of the existing system can be achieved. This happens due to the several devices and applications such as processors, sensors, actuators, gateways, cloud services, analytical tools, etc. work together from sensing the data to process and analyzing the sensed data into insightful measurement data. The transformation of product-oriented outcomes into information-based outcomes can be achieved by using the BIC measurement system. Recently, most of the organizations are trying to extract maximum values by utilizing their humungous amount of data collected through various applications and sensors. Here, the implementation of BIC based concept can explore new opportunities and possibilities that will revolutionize the existing business circumstances. Also, using the BIC related measurement system, the integration and automation of many functions will be simpler and less reliant. Some of the fields like agriculture, healthcare, education, transport, manufacturing, governmental and non-governmental organizations, and many more can be explored by using BIC based system for building a smart connected environment with increased information intelligence and optimized decision-making possibilities. Since information and communication technologies are becoming a necessity in both urban and rural environments, to achieve a smart and sustainable social and economic development in various departments, the appropriate utilization of Big data, the Internet of Things (IoT), and cloud computing is very important. However, there may be many challenges and risks related to security, safety, and other technical aspects while implementing a BIC based measurement system in a smart environment. By addressing all the potential threats carefully, a smart future can build successfully. Papers are welcomed on the following topics but not confined to: Big Data, IoT and Cloud Computing based measurement devices for a smart manufacturing environment A study on designing Big Data, IoT and Cloud Computing based measurement system for smart infrastructure The Need of Big Data, IoT and Cloud Computing environment for healthcare services Benefits of Big Data, IoT and Cloud Computing in the industrial ecosystem Big Data, IoT and Cloud Computing for increasing consumer credibility in the retail industry Role of Big Data, IoT and Cloud Computing based measurement system for smart future cities The ultimate convergence of Big Data, IoT and Cloud Computing for creating a smart connected environment Challenges and risks in integrating Big Data, IoT and Cloud Computing into any smart environment Application of Big Data, IoT and Cloud Computing based system in smart transportation and parking Role of Big Data, IoT and Cloud Computing in business and social issues Big Data, IoT and Cloud Computing for urban computing and evaluation Limitation of Big Data, IoT and Cloud Computing measurement system for enabling the smart world Big Data, IoT and Cloud Computing for the future of government planning and decision making Case Studies on Innovative Applications using Big Data, IoT and Cloud Computing system
Last updated by Dou Sun in 2020-05-05
Special Issue on Security, Trust and Privacy in Computer Networks
Submission Date: 2020-10-31

Modern computer networks like IoT allow billions of devices in the physical world as well as virtual environments to exchange data with each other in an autonomous way, with the aim of creating smart environments such as automotive, healthcare, logistics, environmental monitoring, and many others. However, modern computer networks also introduce new challenges for the security and trust of systems and processes and the privacy of individuals. Protecting the information in modern computer networks is a complex and difficult task, i.e., modern networks are expected to provide global connectivity and accessibility, which results in that the number of attack vectors available to malicious attackers might become incredibly large. As a result, there is an increasing demand for development of new security, trust and privacy approaches to protect modern computer networks. To address these issues and opportunities, this special issue invites original research that develops security, trust and privacy mechanisms for computer networks. The topics include but not limited to the followings. Secure Data Management in computer networks Intrusion Detection and Prevention, Firewalls, Packet Filters Malware, Botnets, and Distributed Denial of Service in networks Communication Privacy and Anonymity Forensics Techniques Secure Routing in computer networks Security & Privacy in Pervasive and Ubiquitous Computing Security & Privacy for IoT applications. Incident Recovery in IoT Communication and Networks. Reliability of IoT Communication.
Last updated by Dou Sun in 2020-05-05
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