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Ranking of researchers and scientists in Greece in 2017 according to Google Scholar database
Scope: The classification of researchers and scientists in Greece in a unified list based on the citation impact and dissemination level of their scientific work according to Google Scholar database Classification criteria: First criterion is h-index. In the case of equal h-index, the following scientometric indicators are used for the classification. The number of total citations, the i10-index, the total impact factor of scientist, the m-index or m-quotient of scientist. Information resource: The h-index, citations and i10-index derived from the public profiles of researchers in the Google Scholar database. In addition, the calculation of total impact factor and m-index of each researcher ...
Designing Faultless Mechanical Products Based on Advanced Reliability Analysis
Serving as a foundational guide to the field, this book is an essential resource for professionals involved in the development of mechanical systems and related industries. It provides a comprehensive introduction to mechanical systems design and offers a detailed overview of the current advancements in mechanical systems design, as well as insights into future trends and applications. Designing Faultless Mechanical Products Based on Advanced Reliability Analysis focuses on the mechanical system based on mechanism and parametric accelerated life testing (ALT). It describes basic reliability concepts, parametric ALT plans, failure mechanism and design, and reliability testing with acceleratio...
Control Charts and Machine Learning for Anomaly Detection in Manufacturing
This book introduces the latest research on advanced control charts and new machine learning approaches to detect abnormalities in the smart manufacturing process. By approaching anomaly detection using both statistics and machine learning, the book promotes interdisciplinary cooperation between the research communities, to jointly develop new anomaly detection approaches that are more suitable for the 4.0 Industrial Revolution. The book provides ready-to-use algorithms and parameter sheets, enabling readers to design advanced control charts and machine learning-based approaches for anomaly detection in manufacturing. Case studies are introduced in each chapter to help practitioners easily apply these tools to real-world manufacturing processes. The book is of interest to researchers, industrial experts, and postgraduate students in the fields of industrial engineering, automation, statistical learning, and manufacturing industries.
Responsible Artificial Intelligence and Data Science
This book constitutes the refereed proceedings of the First EAI International Conference on Responsible Artificial Intelligence and Data Science, RAIDS 2024, held in Danang, Vietnam, during October 22–24, 2024. The 16 full papers presented in this volume were carefully reviewed and selected from 39 submissions. They were organized in the following topical sections: AI for Healthcare and Medical Applications; AI for Human Services and Social Applications; Theorical Contributions for Responsible AI.
Statistical Methods and Applications in Systems Assurance and Quality
In the era of big data and real-time monitoring, vast amounts of information are generated every second through sensors and advanced tracking systems. The information contained in the data needs to be carefully analyzed and accurate results must be delivered to the users as soon as possible. This book explores the critical role of statistics in modern technologies and applied sciences such as health, informatics, and production systems. Statistical Methods and Applications in Systems Assurance and Quality provides a comprehensive overview of statistical methods for ensuring system quality and reliability. It discusses best practices for improving the quality of manufacturing products by usin...
Detection of Non-Random Patterns in Shewhart Control Charts
The main purpose of this article is the development and the study of runs rules applied to a Shewhart type control chart for the mean in order to detect non-random patterns in Phase I. We are interested to conclude if the process is in a stable condition for a specific number of preliminary samples in order to estimate the process' parameters. A characterization scheme such as which rule is better for which pattern, is given, which, may be quite useful to the practitioners, as well as a few applications of the proposed methodology are presented.
