Special issue of JVTSD
An individual's emotions are fundamental to their daily choices and overall wellbeing. One of the key areas of focus for HCI science is creating systems for recognizing and controlling human emotion. However, detecting human emotion in HCI tackles a number of issues, including the natural experimental setup, the interactive non-contact user interface, the induction of genuine emotion, and the real-time recommendation system. When a user engages with a computer, an automated system that detects and reacts to their emotions can improve communication and optimize the user's experience. In the field of simulated reality, crucial input techniques in human-computer interaction (HCI) have been extensively studied. In particular, gesture recognition and speech recognition have made ground-breaking scientific advancements attributable to the quick growth of deep learning, artificial intelligence, and other computer technologies. The final implementation of cognitive and behavioral processes with respect to the dynamics of the neural system is a fundamental premise for conceptual neuroscience. The main goal of an intelligent HCI system is to precisely identify human emotional states in real time. in order for human-computer interaction to be more sophisticated and to recommend pertinent distractions. In order to facilitate harmonious human-computer contact, vocal signals should automatically be recognized by the computer as having emotional content. Using various tools and technologies, human-computer interaction techniques convey information between the human mind and machine intelligence. Most HCI solutions make the assumption that users' physical circumstances are normal, which restricts accessibility for users with limitations. Some products, such as those listed above, are ideal for individuals with particular types of disabilities. But a more all-encompassing HCI approach that disregards users' physical circumstances would improve these technologies' accessibility for people with disabilities. It is better to explicitly model the target dynamical system by determining its joint intrinsic dynamics from various types of observations in order to forecast the future state of the system. However, direct analysis of such intrinsic dynamics is not possible due to their extreme complexity and nonlinearity. One popular method for modelling and simplifying nonlinear dynamics is local or global linearization, as seen through the lens of dynamic systems theory.
Potential topics include but are not limited to the following:
- • Generalized linear integration of nonlinear dynamics by deep learning
- • Simplified order models for realistic simulation based on deep learning
- • Precise responses to nonlinear learning dynamics in deep linear neural network
- • Implementing deep learning for generalized quadratic embeddings in nonlinear dynamics
- • Informative assessment of nonlinear dynamical system models using multilevel deep learning
- • Peak occurrences in a parametrically controlled nonlinear dynamic system
- • Deep learning to solve partial differential equations with second order nonlinear development
- • Leveraging deep learning for architectural dynamic nonlinear prediction in time series prediction
- • Gaining Knowledge of Nonlinear Models of Nonlinear Dynamics using Deep Learning
- • Effective in Nonlinear Structural Dynamics via Deep Learning Capture Generation
- • Deep Learning Data-Driven Identification and Modelling of Nonlinear Dynamical Systems
Submitted papers must be in accordance with the requirements of the Journal of Vibration Testing and System Dynamics (JVTSD). Original manuscripts must be formatted using the JVTSD journal format available for download athttps://www.lhscientificpublishing.com/Journals/JVTSD-Default.aspx.. Authors should indicate to the Guest Editors that they would like the submission to be considered for the special issue “Exploring the Nonlinear Dynamics of Human-Computer Interaction with Deep Learning Techniques.”
Important Dates
| Submission Deadline |
January 30, 2025 |
| Authors Notification |
March 25, 2025 |
| Revised Papers Due |
May 15, 2025 |
| Final notification |
July 25, 2025 |
Guest Editors:
Dr. Aviv Yuniar Rahman,Universitas Widyagama Malang, Malang, Indonesia. E-mail: avivyuniarrahman.id@gmail.com
Dr. April Lia Hananto, Universitas Buana Perjuangan Karawang, Karawang, Indonesia. Email: aprilia@ubpkarawang.ac.id
Dr. Bayu Priyatna, Lublin, Universitas Buana Perjuangan Karawang, Karawang, Indonesia. Email: bayu.priyatna@ubpkarawang.ac.id
There is an increasing demand for complex systems involving dynamic loads in all engineering fields and sciences. These systems may experience unwanted large amplitude nonlinear vibrations, impacting accuracy, operating speed, and safety. Particularly, flexible light-weight structures, such as those used for example in robotics, bioengineering, space, and offshore applications, among others, are liable to such unwanted vibration problems. Vibration control methods including linear control, nonlinear control, intelligent control, MEMS sensors and actuators, artificial intelligence and pattern recognition, among other topics can be used in such cases. They also stimulate the growth of multidisciplinary research in the field of vibrating systems. Since uncertainties and noise are present in all real problems, the development of stochastic methods for nonlinear systems, including topics such as stochastic global dynamics, dynamic integrity, polynomial chaos for sensitivity analysis has been the focus of recent research. Therefore, dynamic modeling of nonlinear systems, including reduced order models (ROMs), nonlinear normal modes and other reduction methods, nonlinear oscillators, modal analyses of multiple-mode systems, synchronization and control applied to chaotic systems becomes important. Another important research area, due to the worsening climate crisis, is research on renewable energy and energy harvesting, where again problems involving nonlinear dynamics and control can be found. Energy harvesting devices converting ambient energy into electrical energy have attracted much interest, including MEMS devices. They convert motion, such as that of ocean waves, into electricity to be used by monitoring sensors for autonomous operation, arrays of high-power output devices, deployable systems, wearable electronics, etc.
Selected papers of the IV Conference on “Dynamics, Control and Applications to Applied Engineering and Life Science” and the Workshop on "Nonlinear Dynamics, Energy Harvesting and Renewable Energy“ (https://dycaels2023.github.io/DYCAELS2023/index.html) will be considered in this special issue.
The aim of this Special Issue is to collate original research articles that focus on the recent theoretical, computational, and experimental results, as well as recent methods and developments in the fields of nonlinear dynamics and control with applications to mechanical, civil, naval, offshore, aeronautical, chemical and electrical engineering, energy harvesting, renewable energy and life sciences. Review articles discussing the current state of the art are also welcoming.
Potential topics include but are not limited to the following:
- • Instrumentation, control, and optimization methods.
- • Fractional order modeling
- • Energy production, renewable energy sources, energy transfer and/or energy harvesting.
- • Dynamics analysis, synchronization and control applied to chaotic systems.
- • Global dynamics and dynamical integrity.
- • Optimal, Robust and Adaptive control.
- • Stochastic Methods for Nonlinear Systems. Polynomial Chaos for sensitivity analysis.
- • Reduced order models (ROMS). Nonlinear normal modes, normal forms, center manifold reduction and other reduction methods.
- • Vehicle dynamics, vehicle drivability, intelligent transportation systems and advanced propulsion control systems. Dynamics of structures/industrial machines/equipment/facilities.
- • Modal analysis and identification, monitoring, diagnostics and related signal processing and computational techniques.
- • Design and analysis of robotic systems and applications in the fields of rehabilitation, soft, and medical robotics, prostheses and exoskeletons. Biomedical Devices.
- • MEMS Sensors and Actuators.
- • Artificial Intelligence and pattern Recognition, Soft Computing.
- • Multi-scale dynamics: coexistence of multiple time/space scales
- • Experimental dynamics: benchmark experiments, experimental methods, instrumentation techniques, measurements in harsh environments, experimental validation of nonlinear models
- • Dynamical problems involving adaptive and multifunctional metamaterials, composites, nanocomposites, and multifunctional structures.
- • Nonsmooth dynamics
- • Vibration control methods including linear control, nonlinear control, intelligent control, MEMS sensors and actuators, artificial intelligence and pattern recognition. Systems with time and/or space delays.
- • Nonlinear interactions: parametric vibrations with single/multi-frequency excitations, multiple external and internal resonances in multi-dof systems.
- • Computational techniques: efficient algorithms, use of symbolic manipulators, integration of symbolic manipulation and numerical methods, use of parallel processors.
Important Dates
| Submission deadline |
January 1, 2024 |
| Acceptance Date |
October 30, 2024 |
| Final version Date |
November 30, 2024 |
| Publication Date |
April 1, 2025 |
Guest Editors:
Prof. Jose Manoel Balthazar, State University of São Paulo at Bauru.(UNESP)and Federal University of Technology of Parana (UTFPR). E-mail: jmbaltha@gmail.com
Prof. Paulo Batista Gonçalves, Pontiofical Catholic University of Rio de Janeiro (PUC-Rio). Email: paulo@puc-rio.br
Prof. G. Litak, Lublin, University of Technology., Lublin. Email: Polandg.litak@pollub.pl
Prof. Angelo Marcelo Tusset, Federal University of Technology of Paraná (UTFPR). Email: a.m.tusset@gmail.com
Fractional-dynamical Systems and Controls detail the use of fractional calculus (calculus of non-integer order) in the description and modeling of systems and in a range of control design and practical applications. It is largely self-contained, covering the fundamentals of fractional calculus together with some analytical and numerical techniques and providing MATLAB® codes for the simulation of fractional-dynamical systems (FDS). The use of fractional calculus can improve and generalize well-established control methods and strategies. Many different fractional-dynamical systems schemes are presented for control and dynamic systems problems. These extend to the challenging control engineering design problems of robust and nonlinear control. Practical material relating to a wide variety of applications including, among others, mechatronics, civil engineering, irrigation and water management, and biological systems is also provided. All the control schemes and applications are presented in the monograph with either system simulation results or real experimental results, or both. Fractional-order Systems and Controls introduces its readers – academic and industrial control researchers interested in mechatronics, nonlinear and robust control, and application fields from civil engineering to biological systems – to the essentials of FDS and imbues them with a basic understanding of FDS concepts and methods. With this knowledge readers can extend their use of FDS in other industrial system applications, thereby expanding their range of disciplines by exploiting this versatile new set of control techniques.
Selected papers of 1st International Conference on “Advanced Mathematics and Artificial Intelligence” (ICAMAI-2023; https://icaai.poornima.edu.in/index.html) are also considered in this special issue.
The aim of this Special Issue is to collate original research articles that focus on the recent results, which can be obtained from the novel methods constructed by many researchers, for all types of these diseases, as well as developments in recent methods with new operators or new approximations. It will also welcome review articles discussing the current state of the art.
Potential topics include but are not limited to the following:
- • Computational Mathematics
- • Fractional Calculus and Artificial Intelligence
- • Fractional Dynamics
- • Fractional Earth Science
- • Fractional Filters
- • Fractional Order Modeling and Control in Biomedical Engineering
- • Fractional Phase-Locked Loops
- • Fractional Variational Principles
- • Fractional Transforms and Their Applications
- • Fractional Wavelet Applications to the Composite Drug Signals
- • Mathematical methods Applied logics, Algorithms and Complexity
- • Artificial Intelligence and pattern Recognition
- • Artificial Intelligence and Soft Computing
- • Artificial Intelligence Theory
- • Advanced Numerical Algorithms
- • Computational Geometry and Computational Mathematics
- • Applied Mathematics and Artificial Intelligence
Important Dates
| Submission deadline |
June 1, 2023 |
| Acceptance Date |
October 30, 2023 |
| Final version Date |
November 30, 2023 |
| Publication Date |
April 1, 2024 |
Guest Editors:
Prof. Dr. Praveen Agarwal, Anand International College of Engineering, Jaipur, India. E-mail: goyal.praveen2011@gmail.com
Prof. (Dr.) Shilpi Jain, Poornima College of Engineering, Jaipur, India. Email: shilpijain1310@gmail.com
All papers submitted to the special volume will be peer-reviewed in accordance with the standard procedures of Journal of Vibration Testing and System Dynamics.
To prepare their manuscripts, authors are asked to closely follow the JVTSD “Guide for Authors” at https://lhscientificpublishing.com/journals/JVTSD-Default.aspx. Authors should submit their papers via the journal's online submission system. Submitted papers should not have been previously published or be currently under consideration for publication elsewhere.
Papers must be written in good English. Authors with limitations in the command of written English are recommended to have their papers edited by a ‘Native English Scientific Editor’ before the first submission to JVTSD because poorly written pieces can compromise the decisions during the review process.
