Muhammad Aslam – författare

Cognitive Intelligence with Neutrosophic Statistics in Bioinformatics investigates and presents the many applications that have arisen in the last ten years using neutrosophic statistics in bioinformatics, medicine, agriculture and cognitive science. This book will be very useful to the scientific community, appealing to audiences interested in fuzzy, vague concepts from which uncertain data are collected, including academic researchers, practicing engineers and graduate students. Neutrosophic statistics is a generalization of classical statistics. In classical statistics, the data is known, formed by crisp numbers. In comparison, data in neutrosophic statistics has some indeterminacy. This data may be ambiguous, vague, imprecise, incomplete, and even unknown.

Neutrosophic statistics refers to a set of data, such that the data or a part of it are indeterminate in some degree, and to methods used to analyze the data.

An Introduction to the Fundamentals and History of Control Charts, Applications, and Guidelines for Implementation 

Introduction to Statistical Process Control examines various types of control charts that are typically used by engineering students and practitioners. This book helps readers develop a better understanding of the history, implementation, and use-cases. Students are presented with varying control chart techniques, information, and roadmaps to ensure their control charts are operating efficiently and producing specification-confirming products. This is the essential text on the theories and applications behind statistical methods and control procedures.

This eight-chapter reference breaks information down into digestible sections and covers topics including:

●      An introduction to the basics as well as a background of control charts

●      Widely used and newly researched attributes of control charts, including guidelines for implementation

●      The process capability index for both normal and non-normal distribution via the sampling of multiple dependent states

●      An overview of attribute control charts based on memory statistics

●      The development of control charts using EQMA statistics 

For a solid understanding of control methodologies and the basics of quality assurance, Introduction to Statistical Process Control is a definitive reference designed to be read by practitioners and students alike. It is an essential textbook for those who want to explore quality control and systems design.

An Introduction to the Fundamentals and History of Control Charts, Applications, and Guidelines for Implementation 

Introduction to Statistical Process Control examines various types of control charts that are typically used by engineering students and practitioners. This book helps readers develop a better understanding of the history, implementation, and use-cases. Students are presented with varying control chart techniques, information, and roadmaps to ensure their control charts are operating efficiently and producing specification-confirming products. This is the essential text on the theories and applications behind statistical methods and control procedures.

This eight-chapter reference breaks information down into digestible sections and covers topics including:

●      An introduction to the basics as well as a background of control charts

●      Widely used and newly researched attributes of control charts, including guidelines for implementation

●      The process capability index for both normal and non-normal distribution via the sampling of multiple dependent states

●      An overview of attribute control charts based on memory statistics

●      The development of control charts using EQMA statistics 

For a solid understanding of control methodologies and the basics of quality assurance, Introduction to Statistical Process Control is a definitive reference designed to be read by practitioners and students alike. It is an essential textbook for those who want to explore quality control and systems design.

Develop more nutritious crops to aid in the fight against world hunger with this timely volume

One in nine people worldwide suffer from hunger or food scarcity. Massively increasing food production is one of the most urgent scientific projects in the modern world, particularly as a changing climate places increasing pressure on the global food supply and on sustainable food production processes. Biofortification is a process in which plant breeding, improved agronomic practices, and/or modern biotechnology are employed to increase nutrient density of crops without sacrificing any of their desirable characteristics. It’s an essential tool in the global fight against hunger.

Crop Biofortification offers an up-to-the-minute overview of this essential subject and its recent advances. It covers all the latest methodologies and techniques deployed in biofortification, as well as surveying plant responses to genetically induced biofortification and the effect of climate change on biofortified crops. Designed to allow for the application of these techniques at the field level, it’s a significant contribution towards the search for a sustainable global food supply.

Crop Biofortification readers will also find:

Crop Biofortification is ideal for researchers, policymakers, and professionals interested in the potential biofortification of crop plants, as well as graduate and advanced undergraduate students in agronomy, plant physiology, plant breeding and genetics, agricultural biotechnology, and related fields.

Develop more nutritious crops to aid in the fight against world hunger with this timely volume

One in nine people worldwide suffer from hunger or food scarcity. Massively increasing food production is one of the most urgent scientific projects in the modern world, particularly as a changing climate places increasing pressure on the global food supply and on sustainable food production processes. Biofortification is a process in which plant breeding, improved agronomic practices, and/or modern biotechnology are employed to increase nutrient density of crops without sacrificing any of their desirable characteristics. It’s an essential tool in the global fight against hunger.

Crop Biofortification offers an up-to-the-minute overview of this essential subject and its recent advances. It covers all the latest methodologies and techniques deployed in biofortification, as well as surveying plant responses to genetically induced biofortification and the effect of climate change on biofortified crops. Designed to allow for the application of these techniques at the field level, it’s a significant contribution towards the search for a sustainable global food supply.

Crop Biofortification readers will also find:

Crop Biofortification is ideal for researchers, policymakers, and professionals interested in the potential biofortification of crop plants, as well as graduate and advanced undergraduate students in agronomy, plant physiology, plant breeding and genetics, agricultural biotechnology, and related fields.

This book introduces a number of new sampling plans, such as time truncated life tests, skip sampling plans, resubmitted plans, mixed sampling plans, sampling plans based on the process capability index and plans for big data, which can be used for testing and inspecting products, from the raw-materials stage to the final product, in every industry using statistical process control techniques. It also presents the statistical theory, methodology and applications of acceptance sampling from truncated life tests.

Further, it discusses the latest reliability, quality and risk analysis methods based on acceptance sampling from truncated life, which engineering and statisticians require in order to make decisions, and which are also useful for researchers in the areas of quality control, lifetime analysis, censored data analysis, goodness-of-fit and statistical software applications.

In its nine chapters, the book addresses a wide range of testing/inspection sampling schemes for discrete and continuous data collected in various production processes. It includes a chapter on sampling plans for big data and offers several illustrative examples of the procedures presented. Requiring a basic knowledge of probability distributions, inference and estimation, and lifetime and quality analysis, it is a valuable resource for graduate and senior undergraduate engineering students, and practicing engineers, more specifically it is useful for quality engineers, reliability engineers, consultants, black belts, master black belts, students and researchers interested in applying reliability and risk and quality methods.

This book is designed to provide a comprehensive introduction to R programming for data analysis, manipulation and presentation. It covers fundamental data structures such as vectors, matrices, arrays and lists, along with techniques for exploratory data analysis, data transformation and manipulation. The book explains basic statistical concepts and demonstrates their implementation using R, including descriptive statistics, graphical representation of data, probability, popular probability distributions and hypothesis testing. It also explores linear and non-linear modeling, model selection and diagnostic tools in R.

The book also covers flow control and conditional calculations by using ‘‘if’’ conditions and loops and discusses useful functions and resources for further learning. It provides an extensive list of functions grouped according to statistics classification, which can be helpful for both statisticians and R programmers. The use of different graphic devices, high-level and low-level graphical functions and adjustment of parameters are also explained. Throughout the book, R commands, functions and objects are printed in a different font for easy identification. Common errors, warnings and mistakes in R are also discussed and classified with explanations on how to prevent them.