Impact Score 6.76
Pattern Recognition for Cyber-Physical-Social Services Proposed acronym PR-CPSS Description of the issue scope and motivation Cyber-Physical-Social-Systems (CPSS) is an emerging cross-disciplinary research area that features the combination of Cyber-Physical-Systems (CPS) and Social Networks, which is a complex system integrating the objects in cyber, physical, and social space to enable proactive services and applications. Smart home, as a typic example of CPSS, will be more intelligent and convenient by providing users with diverse, reliable and safe CPSS services. On the other hand, it is efficient processing of CPSS big data, in which analyze and mine valuable information such as users’ hobbies according to the users’ feedback and trace data. Then, the CPSS system is constantly updated through the analysis of CPSS big data, mining and deriving feedback of valuable information from such data, still taking into account privacy and security issues. Pattern recognition can contribute to the process of processing and analyzing various forms of CPSS information (such as numerical, literal and logical) representing things or phenomena to describe, recognize, classify and can help explaining things or phenomena of CPSS. As efficient CPSS data processing methods, a lot of pattern recognition-related areas (such as gait recognition, iris recognition, face recognition) are used to recognize objects and users by automatically recognizing patterns and regularities of CPSS big data. For example, for elderly guardianship in smart homes, the behavioral data of different users will be analyzed and recognized to mining their needs and provide corresponding services such as eating, drinking, treatment and nursing after a fall. However, the CPSS big data is complex and massive, especially multi-model and multiattributes, which brings many unpredictable challenges for CPSS big data processing by pattern recognition. Traditional approaches and algorithms of pattern recognition not fully meet the demand of processing and analyzing such massive and complex CPSS big data, so that novel and advanced strategies are needed. This Special Issue is on “Pattern Recognition for Cyber-Physical-Social Services”. Original technical papers with novel contributions are welcome. The Special Issue will be advertised using various mailing lists in order to solicit original technical manuscripts with novel contributions dealing with pattern recognition in cyber-physical-social systems.
The Topics of interest for this special issue include, but are not limited to:
● Pattern recognition-based User-oriented services in CPSS; e.g., recommendation, assistance
● Optimization and analysis of pattern recognition for Big Data in CPSS
● High performance methods for Big Data pattern recognition in CPSS
● Parallel and distributed pattern recognition approaches for Big Data in CPSS
● Machine learning and Artificial Intelligence (AI) for Big Data pattern recognition in CPSS
● Deep learning and Artificial neural network for pattern recognition in CPSS
● Cloud/edge-based CPSS services based on Big Data pattern recognition
● Pattern recognition strategies for processing Big Data sets with heterogeneous features from multiple different sources
Prospective authors are invited to upload their papers through the Editorial Manager system. The platform will start accepting submissions approximately one week before the submission period begins. When submitting your manuscript please select the article type “VSI: PR-CPSS”. It is mandatory that the manuscripts be submitted by the deadline indicated. All manuscripts should adhere to the Journal’s guidelines: please take into account that Special Issue papers follow the same submission rules as regular articles.
All submissions deemed suitable to be sent for peer review will be evaluated by at least two independent reviewers. Once your manuscript is accepted, it will go into production, and will be simultaneously published in the current regular issue and pulled into the online Special Issue. Articles from this Special Issue will appear in different regular issues of the journal, though they will be clearly marked and branded as Special Issue articles.
Please see an example here: https://www.sciencedirect.com/journal/science-of-the-total-environment/special-issue/10SWS2W7VVV
Please make sure you have read the Guide for Authors before preparing your manuscript. The Guide for Authors and the link to submit your manuscript are available on the Journal’s homepage.
Prof. David (Zhiwei) Gao, University of Northumbria at Newcastle, NE1 8ST, UK, [email protected] (Managing Guest Editor)
Dr. Xiaokang Wang, St. Francis Xavier University, Canada, [email protected]
Dr. Carmen Bisogni, University of Salerno, Italy, [email protected]