Machine learning (ML) and artificial intelligence (AI) are among the best transformative technologies which have huge potential to bring a powerful impact in various industries of engineering and research. This special issue provides in detailed view of the different techniques of AI and ML for managing complex problems and enhancing productivity in the field of engineering and technical applications. Explicitly, engineering is utilizing AI and ML techniques for the betterment and progress of operation management, designing, and manufacturing. Machine learning engineers firstly design software, predictive models, algorithms which aids machines simplify and identify data-based patterns and take immediate actions independently and that to before getting directions for performing specific responsibilities. Obviously, with the use of these AI and ML paradigms, ML engineers can make data-driven decisions, and raise their dependability on their products. AI and ML technologies not only enhance the system’s overall performance across the board but also improve computer-aided designs to predictive maintenance to quality assurance.
Moreover, with autonomous operations and real-time monitoring, the combination of AI and ML with IoT devices is bringing a revolution in smart systems. AI and ML are accelerating scientific advancement by simplifying the process of data analysis and by finding patterns in huge databases. Basically, automation lessens subjective errors and increases system efficiency and operation productivity, which makes ML engineers to do complex and time-consuming tasks easily and make critical and strategic decisions earlier.
These technological developments are prime for advancing research in an array of scientific fields such as genetics, pharmaceutical innovations, climate modelling, and particle physics. Recently, progress in several scientific fields is being facilitated by AI-powered simulations that assist scientists to better understanding complex processes and to predict outcomes efficiently.
This special issue also discusses the difficulties and constraints of using AI and ML paradigms in engineering and scientific applications. Data privacy, bias, and interpretability are serious challenges that will be addressed, as these technologies are to be used ethically and responsibly. Furthermore, to keep up with the changing nature of engineering and scientific fields, strong algorithms, scalable infrastructure, and continuous learning are addressed. Finally, AI and ML paradigms are ready to transform engineering and scientific landscapes by providing fresh solutions and boosting human skills. Researchers, engineers, and scientists may use an interdisciplinary approach to harness the power of AI and ML to enable revolutionary discoveries, improved problem-solving, and long-term innovation across a wide range of applications.
This special issue intends to bring together academics, practitioners, and experts from academia and industry to present their original research work, exchange ideas, and explore the possibilities of AI and ML paradigms in engineering and scientific applications going forward. The integration of AI and ML in various fields has faced many obstacles, hence we want original research articles, reviews, and case studies that highlight these issues. Topics may include but are not limited to:
Articles have to be prepared carefully according to the guide For Authors at the journal website https://ijmems.in/forauthors.php, and to be submitted through online IJMEMS Submission System at https://submission.ijmems.in . On the first page of the manuscript, before the title of the article, kindly write as “AI and Machine Learning Paradigms for Engineering and Science: Advances in Signal, Machines, Automation, and Algorithm (SIGMAA)”.
Authors should note that all articles submitted should be original and should not have been submitted anywhere else for consideration for publication. All articles will be reviewed in double blind review process as per the journal policy. More information can be found at the journal website at https://ijmems.in Or https://ijmems.in/ethicalissues.php
In today's world, modeling techniques and 3D Simulation play a significant role in engineering, sciences, and real-world scenarios. Modeling is a crucial tool used to predict, analyze, and optimize the behavior of complex systems. Modeling techniques have evolved over time, and new methods and tools are emerging to address the needs of different domains. This special issue aims to present the latest advances in modeling techniques, their applications in various fields, and their potential impact on real-world problems. The primary research findings in the domains of engineering, bioinformatics, medical imaging, ecology, and epidemiology are published in this special issue of Modeling Techniques in Engineering and Real-World Scenarios (MTERWS). The primary goal of MTERWS is to present and make available high-caliber papers in engineering, bioinformatics, medical imaging, ecology, and epidemiology that are grounded on sound mathematical theories and incorporate novel elements. To promote quick and accurate scientific research dissemination, we will ensure a thorough peer review process. In order to disseminate, share, and discuss concerns and developments in various fields, MTERWS intends to provide scientists, academics, and researchers with a communication platform on a global scale. We hope that working with us will be enjoyable for you.
The special issue focuses on the following topics, but is not limited to:
Articles have to be prepared carefully according to the guide For Authors at the journal website https://ijmems.in/forauthors.php, and to be submitted through online IJMEMS Submission System at https://submission.ijmems.in . On the first page of the manuscript, before the title of the article, kindly write as “Article for the Special Issue on Modeling Techniques in Engineering and Real-World Scenarios”.
Authors should note that all articles submitted should be original and should not have been submitted anywhere else for consideration for publication. All articles will be reviewed in double blind review process as per the journal policy. More information can be found at the journal website at https://ijmems.in Or https://ijmems.in/ethicalissues.php
System reliability optimization is a live problem, with solutions methodologies that have evolved in tandem with mathematical advances, the introduction of new engineering technology, and shifts in managerial viewpoints. Due of the evolution of the most recent technological systems, the configuration of a system is extremely dependent on the selection of components, and thus system reliability is a critical factor to consider in system management. While putting together a desirable system, one concern that arises is how to strike a compromise between system reliability and other physical factors such as cost, volume, weight, etc. Such type of optimization problem generally falls into the NP hard problem category, which are solvable by implementation of metaheuristics.
This special issue aims to collect articles that have theoretical studies and applications on system reliability optimization and application of advanced metaheuristics. The scope of this special issues covers following research areas, but not limited to:
Articles have to be prepared carefully according to the guide For Authors at the journal website https://ijmems.in/forauthors.php, and to be submitted through online IJMEMS Submission System at https://submission.ijmems.in . On the first page of the manuscript, before the title of the article, kindly write as “Article for the Special Issue on Reliability Optimization for System Designing by Implementing Advanced Techniques and Metaheuristics”.
Authors should note that all articles submitted should be original and should not have been submitted anywhere else for consideration for publication. All articles will be reviewed in double blind review process as per the journal policy. More information can be found at the journal website at https://ijmems.in Or https://ijmems.in/ethicalissues.php
Many technologies have emerged recently and that too within a short span of time. These technologies have emerged to overcome the need for growing data on the Internet. Such emerging technologies are more approachable to cyber-attacks, as numerous amounts of vulnerabilities can emerge during the integration and consolidation of devices within technologies. With the sudden emergence of worldwide Covid-19 (coronavirus disease), these technologies are providing great support to patients. Technologies like the Internet of Things (IoT), artificial intelligence, deep learning, machine learning, osmotic computing, and even more are playing an important role in data communication. The use of these technologies leads to the expansion of robots and humanoids across the globe. In present times, robots are working in a large number of hospitals for fighting against Covid-19 deadly diseases. Delivery drones are also an effective technology working during this pandemic times. Thus, modelling and control of the cyber-physical world need to be managed securely with full privacy concerns. Many different solutions in modelling and controlling the cyber-physical world have been proposed to address the issues and challenges to overcome the battle of networks, optimization in distributed environments, distributed learning, and other aspects using the Internet of Things (IoT). However, they are not properly designed to address the emerging needs of society. Many service parameters have yet uncovered that need to be focused on for the enhancement of the quality of services like scalability issues, secure migration issues, intelligent systems, issues arising during resource allocation and scheduling, manufacturing issues, authentication and authorization issues, minimization of energy efficiency and reduction of computational costs. Therefore, the use of appropriate IoT devices for effective modelling and control of the cyber-physical world is the key factor, especially for emerging factories in the world of “smart” devices. We solicit original contributions on novel cyber-physical world modelling and control methods, enhancing security and privacy, use of artificial intelligence, and applications of AI-based technology for effective modelling and control towards the cyber-physical world using the Internet of Things (IoT). We also seek contributions motivated by taking real-world society and deployment problems and theoretical works that have a clear intention for practical applications towards cyber-physical world modelling and control using the Internet of Things (IoT). To meet the requirements of emerging Internet of Things (IoT) techniques and the innovation in cyber-physical world modelling and control processes using IoT etc. should be an efficient and safe way out to pursue with optimized and enhanced network. This special issue seeks to bring researchers, scholars, and participators towards technology factors to govern, model, and control cyber-physical worlds using the Internet of Things (IoT) as well as to address challenges and present effective solutions in the growing technological world.
The list of topics includes but is not limited to:
Articles have to be prepared carefully according to the guide For Authors at the journal website https://ijmems.in/forauthors.php, and to be submitted through online IJMEMS Submission System at https://submission.ijmems.in . On the first page of the manuscript, before the title of the article, kindly write as “Article for the Special Issue on Modelling and Control of Cyber-Physical World Using Internet of Things (IoT)”.
Authors should note that all articles submitted should be original and should not have been submitted anywhere else for consideration for publication. All articles will be reviewed in double blind review process as per the journal policy. More information can be found at the journal website at https://ijmems.in Or https://ijmems.in/ethicalissues.php
The reliability management and resilience optimization, primarily including complex systems, mechanical systems, infrastructure systems, etc., has been one of the most important concerns of society. Recently, the issue of resilience has attracted increasing attention from academia and industry, given that disruptive events are more frequent than ever before on a global scale. Resilience quantifies the ability of a system to react, absorb, adapt, and recover from disruptive events. In addition, with the accelerated pace of digital transformation and intelligent upgrading of the economy and society, the Internet of Things (IoT) has become an important part of the new systems. Sensor technologies, transmission technologies, and information fusion technologies have been implemented. The application of these IoT technologies has provided new ideas for reliability management and resilience optimization.
This special issue aims to collect articles that have theoretical studies and applications on resilience management and reliability optimization. The scope of this special issues covers following research areas, but not limited to:
Articles have to be prepared carefully according to the guide For Authors at the journal website https://ijmems.in/forauthors.php, and to be submitted through online IJMEMS Submission System at https://submission.ijmems.in . On the first page of the manuscript, before the title of the article, kindly write as “Article for the Special Issue on Reliability Management and Resilience Optimization with IoT Technologies”.
Authors should note that all articles submitted should be original and should not have been submitted anywhere else for consideration for publication. All articles will be reviewed in double blind review process as per the journal policy. More information can be found at the journal website at https://ijmems.in Or https://ijmems.in/ethicalissues.php
Hydrodynamic instabilities are of great interest in many fields of industrial and scientific domains, with applications in astrophysics, inertial confinement fusion, supersonic combustion, combustion, lithotripsy, fragmentation of cancer cells, cooling of lightening channels and many more. The research of hydrodynamic instabilities establishes whether a flow is stable or unstable, and if so, how these instabilities produce turbulent mixing. There are various hydrodynamic instability types in fluid mechanics, such as Rayleigh-Taylor instability (RTI), Richtmyer-Meshkov instability (RMI), and Kelvin-Helmholtz instability (KHI). For instance, the RMI is a shock-accelerated hydrodynamic instability that occurs in combination with the KHI when an initially perturbed surface separating by distinct fluid properties is driven by an incident shock wave. This type of instability can be considered as the impulsive limit of RTI, where primary perturbations expand across the surface and ultimately emerge into a turbulent fluid mixing as the uniform gravitational acceleration increases. This Special Issue focuses on the most recent developments in theoretical, computational, and experimental contributions to all aspects of hydrodynamic instabilities.
Topics covered include, but are not limited to:
Articles have to be prepared carefully according to the guide For Authors at the journal website https://ijmems.in/forauthors.php, and to be submitted through online IJMEMS Submission System at https://submission.ijmems.in . On the first page of the manuscript, before the title of the article, kindly write as "Article for the Special Issue on Recent Advances in Hydrodynamic Instabilities”.
Authors should note that all articles submitted should be original and should not have been submitted anywhere else for consideration for publication. All articles will be reviewed in double blind review process as per the journal policy. More information can be found at the journal website at https://ijmems.in Or https://ijmems.in/ethicalissues.php
