Handbook of AI in Engineering Applications
Tools, Techniques, and Algorithms
Herausgeber: Kumar, Ajay; Rani, Sangeeta; Jain, Manish; Kumar, Krishna Dev
Handbook of AI in Engineering Applications
Tools, Techniques, and Algorithms
Herausgeber: Kumar, Ajay; Rani, Sangeeta; Jain, Manish; Kumar, Krishna Dev
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There is a need to categorize AI applications, tools, techniques, and algorithms based on their intended use in various design stages. This handbook explores various categories with compatible AI techniques, tools, and algorithms together in one place.
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There is a need to categorize AI applications, tools, techniques, and algorithms based on their intended use in various design stages. This handbook explores various categories with compatible AI techniques, tools, and algorithms together in one place.
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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 336
- Erscheinungstermin: 12. August 2025
- Englisch
- Abmessung: 234mm x 156mm
- ISBN-13: 9781032723150
- ISBN-10: 1032723157
- Artikelnr.: 73533540
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- gpsr@libri.de
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 336
- Erscheinungstermin: 12. August 2025
- Englisch
- Abmessung: 234mm x 156mm
- ISBN-13: 9781032723150
- ISBN-10: 1032723157
- Artikelnr.: 73533540
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- gpsr@libri.de
Ajay Kumar is a Professor in the School of Engineering and Technology, JECRC University, Jaipur, Rajasthan, India. He received his Ph.D. in the field of Advanced Manufacturing from Guru Jambheshwar University of Science & Technology, Hisar, India after B.Tech. (Hons.) in mechanical engineering and M.Tech. (Distinction) in manufacturing and automation. Dr. Kumar's areas of research include Incremental Sheet Forming, Artificial Intelligence, Sustainable Materials, Additive Manufacturing, Mechatronics, Smart Manufacturing, Industry 4.0, Waste Management, and Optimization Techniques. He has over 120 publications in international journals of repute including SCOPUS, Web of Science and SCI indexed database and refereed international conferences. Dr. Kumar has also co-authored and co-edited many books with ELSEVIER, CRC Press, WILEY, De Gruyter and IGI Global and conference proceedings with IOP. He has organized various national and international events including an International conference on Mechatronics and Artificial Intelligence (ICMAI-2021), International conference on Artificial Intelligence, Advanced Materials, and Mechatronics Systems (AIAMMS-2023) as conference chair. Dr. Kumar is credited with more than 20 national and international patents, and has supervised more than 8 M.Tech, Ph.D scholars and numerous undergraduate projects/thesis. He has a total of 15 years of experience in teaching and research and is a Guest Editors and Review Editor of several reputed journals, including Frontiers in Sustainability. Dr. Kumar has contributed to many international conferences/symposiums as a session chair, expert speaker, and member of the editorial board. Throughout his career, Dr. Kumar has won several proficiency awards, including merit awards and best teacher awards. He is adviser of QCFI, Delhi Chapter student cell at JECRC University and has also authored many in-house course notes, lab manuals, monographs and invited chapters in books. Dr. Kumar has organized a series of Faculty Development Programs, International Conferences, workshops, and seminars for researchers, PhD, UG and PG level students, and is associated with many research, academic, and professional societies in various capacities. Sangeeta Rani is an Assistant Professor in the Department of Computer Science and Engineering, World College of Technology & Management, Gurgaon, India. She is pursuing her Ph.D. from Amity University, Manesar, Gurugram, and completed her M. Tech. from Maharshi Dayanand University, Rohtak, India. Dr. Rani's areas of research include Cloud Computing and Machine Learning. Dr. Rani has over 20 research publications in international journals of repute, refereed international conferences, and co-authored more than 5 book chapters. She has a total of 14 years of teaching experience, won the best paper awards at various international conferences, and has more than 5 national and international patents in her credit. Krishna D. Kumar is a Professor of Aerospace Engineering and the Director of the Artificial Intelligence for Aerospace Systems (AIAS) Laboratory at Toronto Metropolitan University, Canada. He is also the Founder and President of iSAC Systems Inc., a leader in Artificial Intelligence, Internet of Things, and Automation since 2010. Dr. Kumar received his Ph.D. degree in aerospace engineering from the Indian Institute of Technology, Kanpur, India, in 1998 and his experience in academia spans more than two and half decades at various premier institutions in Canada, Japan, South Korea, and India (including Toronto Metropolitan University (formerly Ryerson University), Canada; National Aerospace Laboratory, Japan; Kyushu University, Japan; Korea Advanced Institute of Science and Technology, South Korea; Defense Research and Development Organization, India; and Birla Institute of Science and Technology, Pilani, India). Dr. Kumar has made significant contributions with major impact in the areas of autonomous systems, fault diagnosis and prognosis, big data, predictive analytics, and artificial intelligence with over 220 publications in high-ranking journals (100 papers) and conference proceedings (125), 5 books, 14 intellectual properties, and four patents (two granted; two provisional). His internet-of-things devices and artificial intelligence software have been deployed in several industries including aerospace, manufacturing, transportation, and waste management. Manish Jain is a Professor in the Computer Science and Engineering Department, School of Engineering and Technology, JECRC University, Jaipur, Rajasthan, India. He received his Ph.D. from Malaviya National Institute of Technology, Jaipur, India, after his B.Tech. (Hons.) in Computer Science and Engineering from Govt. Engineering College, Bikaner, and his M. Tech. in Computer Science and Engineering from Malaviya National Institute of Technology, Jaipur. Dr. Jain's areas of research include Artificial Intelligence, Machine Learning, Natural Language Processing, Software Testing, Aspect Oriented Programming, and Generative Adversarial Networks. He has over 15 publications in international journals of repute including SCOPUS, Web of Science, and SCIE indexed database and refereed international conferences. Dr. Jain has a unique patent on "Smart Library Management System" to his credit, which proposes the use of Machine Learning for increasing the efficiency of an institution's library. He has a total of 18 years of experience in teaching and research, and has made significant contributions to international conferences/symposiums as an expert speaker and spearheads the Industry Interface cell at JECRC University.
Section One: Integrating AI Tools, Techniques, and Algorithms. 1.A
Comparative Analysis of Symbolic And Subsymbolic Approaches In Artificial
Intelligence. 2. Revisiting the Impact of AI-Driven Feature Selection
Approaches in Software Fault Prediction. 3. Advancing Depression Detection:
Insights from Standard Datasets and Multimodal Approaches. 4. Machine
Learning and Natural Language Processing Strategies for Fake News
Detection: An Empirical Study. 5. Exploring the Nexus of AI, the Metaverse
and Quality of Life. 6. A Literature Survey on AI-Driven Code-Mixed Text
Analysis and Normalization. 7. Reviewing Different Artificial Intelligence
Algorithms For Sarcasm Detection. 8. Advances in Automatic Question
Generation by AI based Algorithms: A Review. 9. Hands on Practices,
Reflection on Data Wisdom with AI Principles: A Review. Section Two:
Harnessing the Applications of AI. 10. FPGA Accelerated Deep Learning
Network For Liver Tumor Segmentation in 3D CT Images. 11. Deep Learning
Enhanced Restaurant Recommendations: Leveraging Artificial Neural Networks.
12. AI-Driven Solutions for Career Counselling Based on the Personality of
an . 13. Exploration of Machine Learning Enabled Automated Crop-Disease
Detection, Segmentation and Classification Techniques. 14. Digital
Camouflage Generation by AI Based Methods: A Survey of Recent Techniques.
15. Plant Disease Detection Using Deep Learning Techniques: A Comprehensive
Review and Comparative Analysis. 16. AI for disaster prediction and
Management. 17. Investigation of Stress Among University Students using PSS
and AI Based Analysis. 18. An Experimental Overview of Assessment of
Authenticity of Face Recognition by AI Techniques in Smart Phones.
Comparative Analysis of Symbolic And Subsymbolic Approaches In Artificial
Intelligence. 2. Revisiting the Impact of AI-Driven Feature Selection
Approaches in Software Fault Prediction. 3. Advancing Depression Detection:
Insights from Standard Datasets and Multimodal Approaches. 4. Machine
Learning and Natural Language Processing Strategies for Fake News
Detection: An Empirical Study. 5. Exploring the Nexus of AI, the Metaverse
and Quality of Life. 6. A Literature Survey on AI-Driven Code-Mixed Text
Analysis and Normalization. 7. Reviewing Different Artificial Intelligence
Algorithms For Sarcasm Detection. 8. Advances in Automatic Question
Generation by AI based Algorithms: A Review. 9. Hands on Practices,
Reflection on Data Wisdom with AI Principles: A Review. Section Two:
Harnessing the Applications of AI. 10. FPGA Accelerated Deep Learning
Network For Liver Tumor Segmentation in 3D CT Images. 11. Deep Learning
Enhanced Restaurant Recommendations: Leveraging Artificial Neural Networks.
12. AI-Driven Solutions for Career Counselling Based on the Personality of
an . 13. Exploration of Machine Learning Enabled Automated Crop-Disease
Detection, Segmentation and Classification Techniques. 14. Digital
Camouflage Generation by AI Based Methods: A Survey of Recent Techniques.
15. Plant Disease Detection Using Deep Learning Techniques: A Comprehensive
Review and Comparative Analysis. 16. AI for disaster prediction and
Management. 17. Investigation of Stress Among University Students using PSS
and AI Based Analysis. 18. An Experimental Overview of Assessment of
Authenticity of Face Recognition by AI Techniques in Smart Phones.
Section One: Integrating AI Tools, Techniques, and Algorithms. 1.A
Comparative Analysis of Symbolic And Subsymbolic Approaches In Artificial
Intelligence. 2. Revisiting the Impact of AI-Driven Feature Selection
Approaches in Software Fault Prediction. 3. Advancing Depression Detection:
Insights from Standard Datasets and Multimodal Approaches. 4. Machine
Learning and Natural Language Processing Strategies for Fake News
Detection: An Empirical Study. 5. Exploring the Nexus of AI, the Metaverse
and Quality of Life. 6. A Literature Survey on AI-Driven Code-Mixed Text
Analysis and Normalization. 7. Reviewing Different Artificial Intelligence
Algorithms For Sarcasm Detection. 8. Advances in Automatic Question
Generation by AI based Algorithms: A Review. 9. Hands on Practices,
Reflection on Data Wisdom with AI Principles: A Review. Section Two:
Harnessing the Applications of AI. 10. FPGA Accelerated Deep Learning
Network For Liver Tumor Segmentation in 3D CT Images. 11. Deep Learning
Enhanced Restaurant Recommendations: Leveraging Artificial Neural Networks.
12. AI-Driven Solutions for Career Counselling Based on the Personality of
an . 13. Exploration of Machine Learning Enabled Automated Crop-Disease
Detection, Segmentation and Classification Techniques. 14. Digital
Camouflage Generation by AI Based Methods: A Survey of Recent Techniques.
15. Plant Disease Detection Using Deep Learning Techniques: A Comprehensive
Review and Comparative Analysis. 16. AI for disaster prediction and
Management. 17. Investigation of Stress Among University Students using PSS
and AI Based Analysis. 18. An Experimental Overview of Assessment of
Authenticity of Face Recognition by AI Techniques in Smart Phones.
Comparative Analysis of Symbolic And Subsymbolic Approaches In Artificial
Intelligence. 2. Revisiting the Impact of AI-Driven Feature Selection
Approaches in Software Fault Prediction. 3. Advancing Depression Detection:
Insights from Standard Datasets and Multimodal Approaches. 4. Machine
Learning and Natural Language Processing Strategies for Fake News
Detection: An Empirical Study. 5. Exploring the Nexus of AI, the Metaverse
and Quality of Life. 6. A Literature Survey on AI-Driven Code-Mixed Text
Analysis and Normalization. 7. Reviewing Different Artificial Intelligence
Algorithms For Sarcasm Detection. 8. Advances in Automatic Question
Generation by AI based Algorithms: A Review. 9. Hands on Practices,
Reflection on Data Wisdom with AI Principles: A Review. Section Two:
Harnessing the Applications of AI. 10. FPGA Accelerated Deep Learning
Network For Liver Tumor Segmentation in 3D CT Images. 11. Deep Learning
Enhanced Restaurant Recommendations: Leveraging Artificial Neural Networks.
12. AI-Driven Solutions for Career Counselling Based on the Personality of
an . 13. Exploration of Machine Learning Enabled Automated Crop-Disease
Detection, Segmentation and Classification Techniques. 14. Digital
Camouflage Generation by AI Based Methods: A Survey of Recent Techniques.
15. Plant Disease Detection Using Deep Learning Techniques: A Comprehensive
Review and Comparative Analysis. 16. AI for disaster prediction and
Management. 17. Investigation of Stress Among University Students using PSS
and AI Based Analysis. 18. An Experimental Overview of Assessment of
Authenticity of Face Recognition by AI Techniques in Smart Phones.