Nature-Inspired Intelligent Techniques for Solving Biomedical Engineering Problems


Book Description

Technological tools and computational techniques have enhanced the healthcare industry. These advancements have led to significant progress and novel opportunities for biomedical engineering. Nature-Inspired Intelligent Techniques for Solving Biomedical Engineering Problems is a pivotal reference source for emerging scholarly research on trends and techniques in the utilization of nature-inspired approaches in biomedical engineering. Featuring extensive coverage on relevant areas such as artificial intelligence, clinical decision support systems, and swarm intelligence, this publication is an ideal resource for medical practitioners, professionals, students, engineers, and researchers interested in the latest developments in biomedical technologies.




Nature-Inspired Optimization Methodologies in Biomedical and Healthcare


Book Description

This book introduces a variety of well-proven and newly developed nature-inspired optimization algorithms solving a wide range of real-life biomedical and healthcare problems. Few solo and hybrid approaches are demonstrated in a lucid manner for the effective integration and finding solution for a large-scale complex healthcare problem. In the present bigdata-based computing scenario, nature-inspired optimization techniques present adaptive mechanisms that permit the understanding of complex data and altering environments. This book is a voluminous collection for the confront faced by the healthcare institutions and hospitals for practical analysis, storage, and data analysis. It explores the distinct nature-inspired optimization-based approaches that are able to handle more accurate outcomes for the current biomedical and healthcare problems. In addition to providing a state-of-the-art and advanced intelligent methods, it also enlightens an insight for solving diversified healthcare problems such as cancer and diabetes.




Nature-Inspired Optimization Algorithms


Book Description

This book will focus on the involvement of data mining and intelligent computing methods for recent advances in Biomedical applications and algorithms of nature-inspired computing for Biomedical systems. The proposed meta heuristic or nature-inspired techniques should be an enhanced, hybrid, adaptive or improved version of basic algorithms in terms of performance and convergence metrics. In this exciting and emerging interdisciplinary area a wide range of theory and methodologies are being investigated and developed to tackle complex and challenging problems. Today, analysis and processing of data is one of big focuses among researchers community and information society. Due to evolution and knowledge discovery of natural computing, related meta heuristic or bio-inspired algorithms have gained increasing popularity in the recent decade because of their significant potential to tackle computationally intractable optimization dilemma in medical, engineering, military, space and industry fields. The main reason behind the success rate of nature inspired algorithms is their capability to solve problems. The nature inspired optimization techniques provide adaptive computational tools for the complex optimization problems and diversified engineering applications. Tentative Table of Contents/Topic Coverage: - Neural Computation - Evolutionary Computing Methods - Neuroscience driven AI Inspired Algorithms - Biological System based algorithms - Hybrid and Intelligent Computing Algorithms - Application of Natural Computing - Review and State of art analysis of Optimization algorithms - Molecular and Quantum computing applications - Swarm Intelligence - Population based algorithm and other optimizations




Machine Learning and Data Science Techniques for Effective Government Service Delivery


Book Description

In our data-rich era, extracting meaningful insights from the vast amount of information has become a crucial challenge, especially in government service delivery where informed decisions are paramount. Traditional approaches struggle with the enormity of data, highlighting the need for a new approach that integrates data science and machine learning. The book, Machine Learning and Data Science Techniques for Effective Government Service Delivery, becomes a vital resource in this transformation, offering a deep understanding of these technologies and their applications. Within the complex landscape of modern governance, this book stands as a solution-oriented guide. Recognizing data's value in the 21st century, it navigates the world of data science and machine learning, enhancing the mechanics of government service. By addressing citizens' evolving needs, these advanced methods counter inefficiencies in traditional systems. Tailored for experts across technology, academia, and government, the book bridges theory and practicality. Covering foundational concepts and innovative applications, it explores the potential of data-driven decision-making for a more efficient and citizen-centric government future.




Optimization of Design for Better Structural Capacity


Book Description

Despite the development of advanced methods, models, and algorithms, optimization within structural engineering remains a primary method for overcoming potential structural failures. With the overarching goal to improve capacity, limit structural damage, and assess the structural dynamic response, further improvements to these methods must be entertained. Optimization of Design for Better Structural Capacity is an essential reference source that discusses the advancement and augmentation of optimization designs for better behavior of structure under different types of loads, as well as the use of these advanced designs in combination with other methods in civil engineering. Featuring research on topics such as industrial software, geotechnical engineering, and systems optimization, this book is ideally designed for architects, professionals, researchers, engineers, and academicians seeking coverage on advanced designs for use in civil engineering environments.




Machining Polymer Matrix Composites: Tools, Techniques, and Sustainability


Book Description

Academic scholars engaged in machining polymer matrix composites face challenges due to material property variations, complex structures, and the pursuit of high surface quality. The lack of comprehensive resources further hampers their ability to develop efficient and sustainable machining techniques. Machining Polymer Matrix Composites: Tools, Techniques, and Sustainability, edited by Francisco Mata Cabrera and Issam Hanafi, offers a comprehensive solution. This book provides practical knowledge on tool selection, cutting parameters, surface quality, and tool wear, empowering scholars to overcome the intricacies of machining these materials. With insights into turning, milling, drilling, grinding, and advancements in high-speed and ultrasonic machining, the book equips scholars with a comprehensive toolbox for optimizing their machining techniques. The book goes beyond technique to address environmental impact, covering topics such as energy consumption, waste generation, and emissions. Through case studies, it offers practical applications and valuable insights into the challenges and opportunities of machining polymer matrix composites. This comprehensive solution, encompassing knowledge, practical guidance, and sustainability considerations, empowers academic scholars to achieve high-quality machined components while minimizing their environmental footprint. Regardless of their expertise level, whether beginners seeking fundamental understanding or experienced professionals in need of advanced insights, scholars will find this book an indispensable resource. By covering tool selection, cutting parameters, surface quality, and environmental impact, Machining Polymer Matrix Composites: Tools, Techniques, and Sustainability equips scholars with the necessary tools to excel in machining polymer matrix composites.




Application and Adoption of Robotic Process Automation for Smart Cities


Book Description

In the present era, technological developments are increasing the efficiency and potential of each stakeholder in a business. Robotic process automation is one of the key areas that can be applied in business organizations and corporate sectors to enhance productivity and show a path to success. Application and Adoption of Robotic Process Automation for Smart Cities provides relevant theoretical frameworks and various developments in the area of robotic process automation. Covering topics such as banking and financial services, public engagement, and smart cities, this premier reference source is a valuable resource for business leaders, IT managers, government officials, engineers, students and educators of higher education, researchers, and academicians.




Natural Resource Management Issues in Human-Influenced Landscapes


Book Description

Researchers working on natural resource management issues in human-influenced landscapes need to be able to elicit both biophysical and socio-economic information and explore the interactions between these realms to identify appropriate management options. Biophysical scientists are increasingly interested in researching natural resource management. This, however, requires a sensitivity to the socio-ecological dimensions in a landscape and at least a basic understanding of how to incorporate such in the research designing phase. Natural Resource Management Issues in Human-Influenced Landscapes documents the firsthand research designing experience of prolific researchers for the knowledge of budding researchers, which is not usually shared in journal publications. The chapters showcase cases narrated by the authors about their field experiences and cross-country comparisons. Covering topics such as biodiversity, plant genetic resources, and sustainable production, this premier reference source is an essential resource for ecologists, government officials, students and educators of higher education, librarians, researchers, and academicians.




Emerging Applications and Implementations of Metal-Organic Frameworks


Book Description

Metal-organic frameworks (MOFs) are some of the most discussed materials of the last decade. Their extraordinary porosity and functionality from metals and organic linkers make them one of the most promising materials for a vast array of applications. The easy tunability of their pore size and shape from the micro- to meso-scale by changing the connectivity of the inorganic moiety and the nature of the organic linkers makes these materials special. Moreover, by combining with other suitable materials, the properties of MOFs can be improved further for enhanced functionality/stability, ease of preparation, and selectivity of operation. Emerging Applications and Implementations of Metal-Organic Frameworks combines the latest empirical research findings with relevant theoretical frameworks in this area in order to improve the reader’s understanding of MOFs and their different applications in areas that include drug delivery, heavy metal removal from water, and gas storage. The design and synthesis of MOFs are also investigated along with the preparation of composites of MOFs. While covering applications that include water defluoridation, rechargeable batteries, and pharmaceutically adapted drug delivery systems, the book’s target audience is comprised of professionals, researchers, academicians, and students working in the field of physical and polymer chemistry, physics, engineering science, and environmental science.




Optimal Planning of Smart Grid With Renewable Energy Resources


Book Description

Understanding the recent developments in renewable energy is crucial for a range of fields in today’s society. As environmental awareness and the need for a more sustainable future continues to grow, the uses of renewable energy, particularly in areas such as smart grid, must be considered and studied thoroughly to be implemented successfully and move society toward a more sustainable future. Optimal Planning of Smart Grid With Renewable Energy Resources offers a detailed guide to the new problems and opportunities for sustainable growth in engineering by focusing on modeling diverse problems occurring in science and engineering as well as novel effective theoretical methods and robust optimization theories, which can be used to analyze and solve multiple types of problems. Covering topics such as electric drives and energy systems, this publication is ideal for researchers, academicians, industry professionals, engineers, scholars, instructors, and students.