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Submission Preparation Checklist

As part of the submission process, authors are required to check off their submission's compliance with all of the following items, and submissions may be returned to authors that do not adhere to these guidelines.
  • The submission has been prepared in accordance with the journal's Instructions for Authors and follows all the journals' policy requirements.
  • The submission file is in Microsoft Word format.
  • All co-authors must be included at the time of submission with valid e-mail addresses.
  • No part of the manuscript has been, or will be, published elsewhere nor is under consideration for publication elsewhere.
  • The submitted paper contains no proprietary material unprotected by patent or patent application.
  • The submitted paper contains no plagiarism/copying and fraudulent data.

Author Guidelines

We welcome the following types of contributions:

1. Full-length and letter-length papers describing original research and/or novel applications
2. Well researched review/survey articles
3. Work-in-progress reports on promising developments
4. Case studies and best practice articles prepared by industry experts
5. Tutorials on up-and-coming technological breakthroughs

It is expected that 80% of published contents would fall under categories 1) and 2). Although categories 3)-5) should make up only 20% of published contents, category 3) is intended to be an important feature of the journal. It will be a venue for publishing ‘spot the trend’ or ‘you saw it here first’ types of contributions. This reinforces the forward looking nature of the journal

We expect readers and contributors to come from the wide spectrum of computing/IT communities including academic and industrial researchers, industrial managers and practitioners, IT consultants, educators, and employees of related government agencies, as well as policy makers in the public and private sectors.

Submitted papers are assumed to contain no proprietary material unprotected by patent or patent application; responsibility for technical content and for protection of proprietary material rests solely with the author(s) and their organizations and is not the responsibility of JAIT or its Editorial Staff. The main author is responsible for ensuring that the article has been seen and approved by all the other authors. It is the responsibility of the author to obtain all necessary copyright release permissions for the use of any copyrighted materials in the manuscript prior to the submission.

Special Issue: Synergies of Neural Networks, Neurorobotics, and Brain-Computer

Special Issue: Synergies of Neural Networks, Neurorobotics, and Brain-Computer Interface Technology: Advancements and Applications
This special issue is dedicated to exploring the dynamic intersection of Neural Networks, Neurorobotics, and Brain-Computer Interface (BCI) technology. This issue aims to provide an in-depth technical platform for researchers and practitioners to share their latest findings, methodologies, and applications related to the symbiotic evolution of these fields. The special issue seeks to delve into the integration of neural networks, neurorobotics, and BCIs, unraveling their potential for enhancing human-machine interactions, healthcare, assistive technologies, and beyond.
Topics of Interest: Contributions to this special issue should address, but are not limited to, the following technically oriented subjects:
Bio-Inspired Neural Architectures: Novel neural network models and architectures inspired by the structure and functioning of the human brain, advancing learning and adaptability in AI systems.
Neurorobotics for Autonomous Systems: Innovations in neurorobotics that empower robots to perceive, interact with, and navigate the environment autonomously through bio-inspired algorithms.
BCI-Driven Prosthetics and Assistive Devices: Applications of BCI technology in developing advanced prosthetics, exoskeletons, and assistive devices that restore mobility and functionality for individuals with motor impairments.
Cognitive Neuroscience and AI Fusion: Exploration of the synergy between cognitive neuroscience findings and AI techniques, unraveling insights into human cognition and enhancing AI system performance.
Neuro feedback and Neuro rehabilitation: Utilizing BCI-enabled neurofeedback for cognitive training, neurorehabilitation, and treating neurological disorders.
Ethical and Privacy Considerations: Addressing the ethical implications of neural network technologies, neurorobotics, and BCIs, including privacy, security, and neuroethics.
Neural Control of Robotic Systems: Investigating neural control paradigms for real-time interaction and control of robotic systems, enabling intuitive and natural human-machine interfaces.
BCI-Enhanced Virtual and Augmented Reality: Integration of BCI technology with virtual and augmented reality environments for immersive experiences and therapeutic applications.
Neural Interfaces and Implants: Advancements in neural interface technologies, including brain implants and neurostimulation techniques, for seamless integration with AI systems and robots.
Neural Networks in Brain Signal Analysis: Leveraging neural networks for processing and analyzing brain signals, enhancing the accuracy and speed of BCI systems.

Special Issue: Federated Learning for the Internet of Things and Machine Learnin

Submission Deadline: December 31, 2023
Special Issue Information
Internet of Things (IoT) applications such as intelligent transportation and remote health monitoring have resulted in incredible advances in the quality of life. Massive devices and massive amounts of data necessitate the deployment of machine learning approaches in the IoT era to provide high-quality smart services. However, because of the risk of data misuse and leakage, IoT devices should not share personal data. Federated Learning (FL) has gained popularity in IoT applications in recent years as a distributed machine learning approach with data privacy. As FL technologies evolve, new challenges emerge, such as convergence rate analysis, device selection, resource allocation, and so on. To address these challenges, various theories, optimization algorithms, and sophisticated schemes have been proposed.
Furthermore, IoT applications can benefit from FL, and IoT systems can provide effective security. However, more research is needed to enable FL for IoT.
This Special Issue aims to bring together leading researchers and developers from industry and academia to present their research on FL for IoT and to promote the development of IoT. We welcome both original research and review papers.
Potential topics include but are not limited to the following:
• Architecture and protocol design in FL for IoT
• Machine Learning
• Applications and services in FL for IoT
• Convergence rate analysis for FL
• Advanced federated optimization algorithms for enabling FL in IoT
• Artificial intelligence empowered FL for IoT
• Blockchain empowered FL for IoT
• Communication, computation, and cache resource management in FL for IoT
• Intelligent resource allocation in FL for IoT
• Security and privacy issues in FL for IoT
• Implementation/testbed/deployment for FL
• Personalized FL for IoT

Special Issue: Toward an Intelligent Edge in the Internet of Things Era

The advent of fifth generation communication systems, known as the 5G reality Internet of Things (IoT) concept. Consequently, a series of smart applications are forming based on the integrating of IoT technology, smart sensors, and different computing schemes and such as smart agriculture, smart healthcare, smart homes/cities, smart retail, etc. to enhance the quality of life for humanity. However, these applications are facing several issues such as service response time, quality of service (QoS) guarantees, energy consumption, privacy, and security. To address these problems, some recent studies have proposed implementing artificial intelligence (AI) at the edge of networks and forming the Intelligent Edge concept. As a result, this helps reduce service response time, saving energy, and computing costs and improving overall performance. However, it's still several problems when integrating AI into the edge of the network. Traditional AI techniques are deployed on powerful servers with centralized training data while Edge devices with resources-constrained. 

Therefore, this Special Issue (SI) is dedicated to IoT-based smart applications and/or advanced computing technologies such as Cloud/Fog/Edge, and Big Data analysis, modern AI techniques. The topics include but are not limited to: 
- Smart IoT ecosystems such as smart healthcare, smart grids, smart agriculture, smart homes/cities to enhance the quality of life for humanity. 
- Modern AI Techniques 
- Internet of Vehicles/Intelligent Transportation Systems 
- Edge/Fog/Cloud Computing Schemes for IoT systems 
- Ad Hoc Communication Technologies 
- Big Data Analytic Techniques 
- IoT-based Applications 
- Smart Healthcare/Smart Agriculture 
- Security and Privacy of Advanced Networks 

Topic: Machine Learning in Computer and Information Systems

Machine learning is the process of a computer modeling human intelligence, and autonomously improving over time. Machines are able to make predictions about the future based on what they have observed and learned in the past. The topics include but are not limited to:

Logistic Regression   Decision Tree
k-Means       Nearest Neighbors
Principal Component Analysis   Hierarchical Naïve Bayes
Random Forest   Support Vector Machine
Reinforcement learning   Unsupervised learning
Supervised learning   Deep learning
Self-Organizing Maps   Topic model
Dimensionality reduction   Artificial Neural Networks
Deep Neural Network   K-nearest neighbor
Linear regression   Canonical correlation analysis


Topic: Application of Virtual Reality and Augmented Reality Technologies in Inte

Virtual reality is an advanced computer simulation experience technology that uses posture tracking and 3D computer drawing technology and various intelligent virtual display devices to provide users with an immersive feeling of the virtual world and allow users to interact with each other in a manually created real world. The main features of virtual reality are identified as spatial conception, perception comprehensiveness, and information interaction. Virtual reality typically incorporates auditory and video feedback, but may also allow other types of sensory and force feedback through haptic technology.  These features are generally applied across different fields, such as environmental design, architecture, public art design, and other industries.  a wide range of topics including, but not limited to:

♦ Original research studies of Virtual Reality, Augmented Reality, Mixed Reality, extended reality and Computer vision techniques, Computer graphics techniques, Immersive analytics and visualization techniques, and applications

♦ Development and evaluation of systems, tools, techniques, and software that advance the field, including display technologies, Head Mounted Displays, simulators, and immersive displays.

♦ Haptic technologies, including novel devices, interaction, and rendering, Haptic and tactile interfaces, wearable haptics, passive haptics, pseudo haptics

♦ Interaction management, including gesture control, eye gaze, biosensors, biofeedback, Human-computer interaction for VR/AR/MR/ER, Audio interfaces, Brain interface, Multimodal/cross-modal interaction, and perception and wearables

♦ Tracking technologies, motion capture, 3D spatial sound, virtual smell, Tracking and sensing, and virtual taste

♦ VR/AR/MR/ER in medicine, including training, surgical simulation, rehabilitation, and tissue/organ modeling.

♦ Impactful and original applications and studies of VR/AR/MR/ER’s utility in areas such as manufacturing, business, telecommunications, arts, education, design, entertainment, and defense

♦ Research demonstrating new techniques and approaches to designing, building, and evaluating virtual and augmented reality systems

♦ Original research studies assessing the social, ethical, data, or legal aspects of VR/AR/MR/ER

Topic: Software Design and Program Development

Software Design and Program Development play a key role in the software development process. Different methods are used for architecture design and detailed design evaluation. The topics include but are not limited to:

Computer programming languages and programming          Parallel programming
Software structure design   Software quality assessment
Software analysis methods and tools   Debugging
Software requirements analysis   Application Testing and Design
Test case design and execution   Testing Application Vulnerabilities
Software modeling and analysis   Software testing in IoT (Internet of Things)
Software design and estimation   Importance of agile and DevOps principles
Software frameworks and architectural   Security testing tool
Architectural and design patterns   Software testing, diagnosis, and validation
Software process models   Design principles
Project management   Software performance
Software testing to combat cybersecurity and risk compliance   Machine learning and artificial intelligence to enhance automated software testing

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Permissions for Reproducing Published Material in Your Work

Authors are responsible for obtaining permission to reproduce any published material (figures, schemes, tables or any extract of a text) which does not fall into the public domain, or for which they do not hold the copyright. Permission should be requested by the authors from the copyright holder (usually the Publisher, please refer to the imprint of the individual publications to identify the copyright holder). The copyright holder may give you instructions on the form of acknowledgment to be followed; otherwise, follow the style: "Reproduced with permission from [author], [journal title]; published by [publisher], [year], [reference number].” at the end of the caption of the Table or Figure.

In order to avoid unnecessary delays if the publication process, authors should start obtaining permission as early as possible. When submitting your article, please upload the permission together with the rest of your files.