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AFRICOMM 2020 is going virtual! Submit your paper and get more citations & extra exposure by presenting online to a global audience (Springer, Scopus, ISI, more) December 3 – 4, 2020
June 10th, 2020 
Daniela Lopez de Luise 
ENA 2021: International conference on End to End Network Automation and get high-quality reviewers, fair recognition, faster publishing with EAI Community Review
June 9th, 2020 Daniela Lopez de Luise
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New Journal: Journal of Cyber Forensics and Advanced Threat Investigations
June 9th, 2020 Daniela Lopez de Luise Dear Cybersecurity Researcher,
Red || Yellow || Blue Practitioner,
The Journal of Cyber Forensics and Advanced Threat Investigations is
an international open-access journal that publishes original research,
practical and review articles related to all areas of cybersecurity,
digital forensics, incident response, and threat investigations. The
scope includes the measures that governments or organization should
follow to protect the online information & critical infrastructure,
the impacts of cyber-crime & cyber-attacks in organizations and/or
individuals, malware/ransomware, analysis & reversing,
hardware/software security testing, zero-day attacks & exploits,
large-scale digital investigations, unconventional penetration testing
tactics, techniques & tools, social engineering & human hacking,
anti-forensics & anti-anti-forensics, identity theft & protection,
women in cybersecurity & challenges faced by women in cyber forensics,
relevant case studies in cybersecurity, digital forensics, incident
response, & threat investigations, and proficient strategies for
tackling the various types of cyber-attacks and cyber-crimes.
The journal is pleased to welcome manuscript submissions from you.
Please browse through the journal website to find out more information
about the focus and scope of the journal and the author's guidelines.
The Journal Website: https://conceptechint.net/index.php/CFATI
The Journal welcomes three kinds of submissions:
* Research Articles,
* Practical Articles,
* Review Articles.
All submissions will be rigorously peer-reviewed. For more details,
see https://conceptechint.net/index.php/CFATI/index
All accepted articles will be published under the Creative Commons
CC-BY-NC. Each Accepted article will have a unique identifier and will
be abstracted and indexed in 7 different international databases
accessible for all academic and research communities of cybersecurity
to secure high visibility.
The journal is open access to the world and does not charge authors
publication fees or article processing fees.
Contact
All questions about submissions should be emailed to cfati@conceptechint.net
Sincerely,
Mrs. M. Leonko
Administrative and Editorial Assistant
Editorial Office, Concept Tech Publishing,
Carryduff, United Kingdom.
My pronouns are: She/Her/Hers
AI-Enabled Advanced Sensing for Human Action and Activity Recognition (Sensors Journal)
June 9th, 2020 Daniela Lopez de Luise Dear Colleagues,
The Special Issue entitled “AI-Enabled Advanced Sensing for Human Action and Activity Recognition” calls for original works revealing the latest research advancements on conventional machine learning and deep learning methods that deeply analyze the structure of human actions and activity patterns from distinct kinds of sensor data or their fusion. These recognition methods need to be based on smart and innovative machine intelligence.
The topics include but are not limited to the following:
• Deep learning for action/activity/anomaly recognition.
• Spatiotemporal features extraction for human sequential patterns analysis.
• Lightweight 2D and 3D convolutional neural networks for human action/activity recognition.
• RGB/depth/skeleton sensors-based action recognition.
• Data prioritization prior to human activity patterns analysis.
• Violence recognition.
• Embedded vision for action/activity recognition.
• Sensors/multi-sensor integrations for activity recognition.
• Activity localization, detection, and context analysis.
• IoT-assisted computationally intelligent methods for activity recognition.
• Cloud/fog computing for action and activity recognition.
• Benchmark datasets for action/activity/anomaly recognition.
SI Link: https://www.mdpi.com/journal/sensors/special_issues/HAAR
SISAP 2020 Special Session: Artificial Intelligence and Similarity
June 9th, 2020 Daniela Lopez de Luise Paper deadline: June 22, 2020.
Below you can find the text describing the special session, and more
information is here: http://sisap.org/2020/specialsessions.html
Recent years have witnessed a strong renovated interest in artificial intelligence. This has been mainly due to the outstanding performance offered by deep learning methods, thanks to the innovative architecture, the availability of huge quantities of training data, and the high computing power provided by GPU architectures.
There are noteworthy relationships between methods of artificial intelligence and similarity search. For example, similarity search is more often executed on features (for instance image features) extracted using artificial intelligence methods, rather than hand-crafted methods. This poses new challenges, given that such features have generally much higher (intrinsic) dimensionality than hand-crafted features. Artificial intelligence has also been used as an instrument for building efficient and effective methods for similarity search. Consider for instance methods of metric learning, learning to index, and learning to hash. In this case, artificial intelligence is used as an alternative to hand-crafted structures and data coding to obtain efficient and effective similarity search algorithms. In addition, consider that what is generally behind many machine learning methods is the possibility of comparing, judging relationships, and estimating similarity among objects or entities in order to classify, recognize, and take decisions.
In this special session, we seek contributions where artificial intelligence and similarity evaluation/searching is either exploited in synergy or supporting one the other. Both mature research papers and position papers are welcome.
Topics include, but are not limited to:
- AI-based feature extraction and similarity
- Clustering methods
- Machine learning methods and similarity
- Metric learning
- Learning to index
- Learning to hash
- Submissions must follow the regular paper submission and author guidelines of SISAP 2020 (guidelines)
- Submit your paper through EasyChair (link); please be sure to select “Special Session: Artificial Intelligence and Similarity” in the appropriate field of the submission form.