Klub Informatyka

 
 
 

CALL FOR PAPERS

Cognitive Cloud Continuum Ecosystems: Theory and Practice
Honolulu, Hawaii, January 3-6, 2024

HICSS57 Minitrack
https://hicss.hawaii.edu/tracks-57/software-technology/

Cognitive Cloud is an enhanced Cloud-Fog-Edge system that is capable of sensing its environment, learning from it, and opportunistically and dynamically adapting its computational loads to the user intents. Here, the core enabling technologies, for management of resources, services and data are AI/ML techniques, which infuse the cognitive aspects into the continuum.

This minitrack intends to solicit papers that discuss the theoretical and practical aspects of Cognitive Cloud Ecosystems from a system perspective. Topics of interest include:
* Architectures for the Cognitive Cloud for systems that are user-aware, self-aware and (semi-)autonomous; address the need for real-time capable solutions; and solve performance challenges, such as data streaming and filtering near/at the edge, overcoming latency and network constraints
* Service mesh networking that controls service-to-service communication across cognitive cloud ecosystem
* Orchestration of (sub)systems in the Cognitive Cloud, possibly subdivided into orchestration of resources, services, and data (including zero-touch approaches)
* Use of distributed AI across the Cognitive Cloud to make it intelligent
* Interconnection of Cognitive Clouds with Data Spaces
* Security, privacy and trust (likely, by design) in a multi-tenet de-centralized systems, possibly with no single point of governance
* Interoperability across the Cognitive Cloud Ecosystems to cope with the increased complexity of vast numbers of heterogeneous devices, while supporting demands for data sharing combined with the demand for protection of privacy
* Role of intelligent devices, drawing from applicable results in micro/nano/bio technologies, including resource-aware hardware/software concepts, low power processor platforms integrating computing, networking, storage and acceleration elements, new communication schemes and topologies that range from the cloud continuum towards mesh, and securing computing and communication at device level with constrained resources
* Tactile/contextual Internet of Things based on human-centric sensing/actuating, augmented/virtual reality and new service capabilities such as integration with parallel and opportunistic computing capabilities, neuromorphic and contextual computing.
* Energy aware systems from the perspective of systems integration for efficient deployment of services and use of resources in the Cognitive Cloud
* Strategies for the deployment of hyper-distributed applications in the Cognitive Cloud from services description to dynamic reorganization of the deployment
* Extreme data processing applications and Frugal AI in the cognitive cloud
* Applications of Cognitive Cloud including implementation of ecosystems, pilots, lessons learned, barriers, etc.

Important Dates
Submission Deadline: June 15, 2023 | 11:59 pm HST
Notification of Acceptance/Rejection: August 17, 2023 | 11:59 pm HST
Deadline for Submission of Final Manuscript
for Publication: September 22, 2023 | 11:59 pm HST
Deadline for at least one author
to register for HICSS-57: October 1, 2023 | 11:59 pm HST

Minitrack Co-Chairs

Marcin Paprzycki (Primary Contact)
Polish Academy of Sciences
[masked]

Maria Ganzha
Polish Academy of Sciences
[masked]

Harilaos Koumaras
Institute of Informatics and Telecommunications
[masked]

Carlos Palau
Univeristat Politecnica de Valencia
[masked]

 
 
 

## Introduction

In the age of multimedia and social network, there is a rapid growth in user generated data, which needs to be analyzed, processed to understand the user subjective perception. Sentiment analysis is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. The Affective Computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects. It is a new ways of bringing together Emotion AI and other affective technologies in order to make people's lives better. As the rapid growth of user-generated data from social networks, wikis and social tagging systems, it is necessary to understand the high-level semantics and user subjective perceptions from such a large volume of data. Emotions or sentiments are one of the most important aspects as the user-generated data are always with emotional loads of their creators. Along with the development of the computational techniques for sentiment analysis and opinion mining, the increasing psychological and cognitive models/theories are exploited for modeling sentiments and emotions by incorporating with social computing techniques such as social network and personalization, mining user reviews, user profiling in social network and so on. Connecting affective/sentimental models and social computing techniques not only can facilitate the understanding big data in at semantic-levels but also improve the performance of various social computing applications in the big data era. It combines affective/sentimental models with social computing as a promising direction and offers opportunities for developing novel algorithms, methods and tools.
This special issue will be a platform to researchers to provide the opportunity to address the recent trends in “Sentiment Analysis and Affective computing in Multimedia Data on Social Network”. This issue will also promote significant research contributions by scholars and scientist worldwide included specific topics. This will be also a good reference to the professional in this area of research, target to present, endorse and discuss current research.

## Recommended topics (but not limited to)

Authors are invited for original contributions on, but not limited to, the themes and topics in the following areas of research:

• Aspect-based sentiment analysis,
• Personalized sentiment analysis,
• Context-based sentiment analysis,
• Multi-model sentiment analysis,
• Multilingual aspect of sentiment analysis,
• Real-time sentiment analysis and its research perspective,
• Computing resources for sentiment analysis or Affective Computing,
• Effective sentiment analysis with limited computing resources,
• Affective Computing with limited resources,
• Sarcasm detection,
• Fake review detection,
• Fake news classification,
• Vocal language context identification,
• Authenticity of viral message/video/clip detection,
• Sentiment analysis tools and its application,
• Application perspective of Sentiment analysis,
• Sentiment analysis and finance,
• Sentiment analysis and healthcare,
• Sentiment analysis and digital marketing,
• Sentiment analysis and direct selling,
• Recommendation Systems,
• Context-aware recommendation systems,
• Personalized recommendation systems,
• Dynamic recommendation systems,
• Opinion Mining, and
• Many more…

## Important dates

Submission deadline: 31 July, 2023
Authors notification: 15 September, 2023
Final version submission: 15 October, 2023

## Submission guidelines

Original and unpublished works on any of the topics aforementioned or related are welcome. The SCPE journal has a rigorous peer-reviewing process and papers will be reviewed by at least two referees. All submitted papers must be formatted according to the journal's instructions, which can be found here.
During submission please select a Special Issue that you want to submit to and provide this information in the Comments for the Editor field.

## Guest Editors

Dr. Rajni Mohana, Associate Professor, CS/IT Department, Jaypee University of Information and Technology, Solan, H.P., India
Dr. Anand Nayyar, Lecturer, Researcher and Scientist, Graduate School, Duy Tan University, 254 Nguyen Van Ling Street, Duy Tan University, Da Nang[masked], Viet Nam
Dr Pradeep Kumar, Associate Professor, Discipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, South Africa
Dr Aman Sharma, Assistant Professor (SG), CS/IT Department, Jaypee University of Information and Technology, Solan, H.P., India

https://scpe.org/index.php/scpe/CFP_SI_SAACMD

 
 
 

## Introduction

Advancements in sensor technology and networking have led to the evolution of large, distributed clusters of microsensors. It also kicks up the transition from fixed sensors to mobile nodes, wired to wireless communication, and from static network topology to dynamic network topology. Appropriate distributed services and network protocols provide a solution to mobility, dispersion, weak and intermittent disconnection, dynamic reconfiguration, and limited power availability. Distributed Sensor Networks (DSNs) must self-organize their routing and key management as it is one the integral parts of the IoT domain with its application in the military sector, environmental protection, industrial monitoring, smart cities, and many more. More attention is required to promote an efficient method for exchanging information between the nodes, and Collaborative Signal Processing between the nodes to gather useful information about the physical world. DSNs emulate the asset of sensor hardware and support extensible radio models such that the applications can be simulated with high reliability and also employs a distributed-memory parallel cluster system to attack the complex simulation problem. Due to hardware issues, depleted batteries, and environmental factors; sensor nodes are prone to frequent topological changes. This requires a design of network topology with a high degree of inherent fault tolerance and the ability to configure itself. Local collaboration of nearby sensor nodes achieves a higher level of confidence and improvement in sensing quality is achieved by integrating multiple independent sensors.
The technological advancements pose new challenges due to limited bandwidth, power constraints, and unstable and dynamic environments. Technological and research advances are required to gain scalability in a significant manner. Such advancements are necessary for network protocols, middleware, and operating systems, data processing algorithms, etc. Different technologies evolving around cloud and edge computing allow organizing streamlined development and operational tasks. These technologies allow a flexible development and integration process of the system components and facilitate monitoring and scalability. Further, IoT software services can be modelled using microservices design patterns. This special issue aims to look into the possibilities and the schemes to meet the challenges in the domain of distributed sensor networks with a particular focus on scalability and sustainability.

## Recommended topics (but not limited to)

Authors are invited for original contributions on, but not limited to, the themes and topics in the following areas of research:

• Localization and Synchronization in Sensor Networks
• Efficient Device-to-Cloud Integration for Scalable Sensor and Actuator Networks
• Distributed Sensor Networks - Networking / Caching Issues
• Edge Computing for Scalable Sensor and Actuator Networks
• Sensor Networks for the Internet of Things (IoT)
• Efficient Device-to-Cloud Integration for Scalable Sensor and Actuator Networks
• Real-time embedded systems
• Pervasive and ubiquitous systems
• Real-time embedded systems
• Machine Learning in energy-efficient distributed sensor networks
• Fog and Mobile Edge Computing
• Advances in Cloud Computing, Grid and cluster computing
• Deep Learning for Distributed Sensor Networks
• Distributed Sensor Networks Data Analytics

## Important dates

Submission deadline: 31 August, 2023
Authors notification: 31 November, 2023
Completion of Special Issue: 31 December, 2023

## Submission guidelines

Original and unpublished works on any of the topics aforementioned or related are welcome. The SCPE journal has a rigorous peer-reviewing process and papers will be reviewed by at least two referees. All submitted papers must be formatted according to the journal's instructions, which can be found here.
During submission please select a Special Issue that you want to submit to and provide this information in the Comments for the Editor field.

## Guest Editors

Dr. Sathishkumar V E, Department of Software Engineering, Jeonbuk National University, Jeonji-si, Jeollabuk-do, Republic of Korea, email: [masked]

Dr.Venkatachalam K, Department of Applied Cybernetics, University of Hradec Kralove , Hradec Kralove,Hradec Kralove, Czech Republic, email: [masked]

Prof. Dr. Fadi Al-Turjman, Head of the Department of Artificial Intelligence Engineering. Near East University, Nicosia, Cyprus, email: [masked]

 
 
 

Oddział Białostocki PTI serdecznie zaprasza na XVII Konferencję "Technologie Eksploracji i Reprezentacji Wiedzy", która odbędzie się w dn. 11-14 września 2023 w Hołnach Mejera.

Szczególnie zapraszamy osoby przygotowujące rozprawy doktorskie. Autorzy najlepszych prac spośród doktorantów będą zwolnieni z opłaty konferencyjnej.

Szczegóły: http://irys.wi.pb.edu.pl/terw/