Samira Hosseini – författare

This book presents commonly applied characterization techniques in material science, their brief history and origins, mechanism of operation, advantages and disadvantages, their biosensing applications, and troubleshooting for each technique, while addressing the challenges researchers face when working with these techniques. The book dedicates its focus to identifying physicochemical and electrochemical nature of materials including analyses of morphology, mass spectrometry, and topography, as well as the characterization of elemental, structural, thermal, wettability, electrochemical, and chromatography properties. Additionally, the main features and benefits of using coupled characterization techniques are discussed in this book.

This book contains peer-reviewed selected papers of the 7th International Conference on Educational Innovation (CIIE 2020). It presents excellent educational practices and technologies complemented by various innovative approaches that enhance educational outcomes. In line with the Sustainable Development Goal 4 of UNESCO in the 2030 agenda, CIIE 2020 has attempted to “ensure inclusive and equitable quality education and promote lifelong learning opportunities for all.” The CIIE 2020 proceeding offers diverse dissemination of innovations, knowledge, and lessons learned to familiarize readership with new pedagogical-oriented, technology-driven educational strategies along with their applications to emphasize their impact on a large spectrum of stakeholders including students, teachers and professors, administrators, policymakers, entrepreneurs, governments, international organizations, and NGOs.

This book is written for statisticians, data analysts, programmers, researchers, professionals, and general consumers on how to perform different types of statistical data analysis for research purposes using R object-oriented programming language and RStudio integrated development environment (IDE). R is an open-source software with a development environment (RStudio) for computing statistics and graphical displays through data manipulation, modeling, and calculation. R packages and supported libraries provide a wide range of functions for programming and analyzing of data. Unlike many of the existing statistical software, R has the added benefit of allowing the users to write more efficient codes by using command-line scripting and vectors. It has several built-in functions and libraries that are extensible and allows the users to define their own (customized) functions on how they expect the program to behave while handling the data, which can also be stored in the simple object system. Therefore, this book serves as both textbook and manual for R statistics particularly in academic research, data analytics, and computer programming targeted to help inform and guide the work of the users. It provides information about different types of statistical data analysis and methods, and the best scenarios for use of each case in R. It gives a hands-on step-by-step practical guide on how to identify and conduct the different parametric and nonparametric procedures. This includes a description of the different conditions or assumptions that are necessary for performing the various statistical methods or tests, and how to understand the results of the methods. The book also covers the different data formats and sources, and how to test for the reliability and validity of the available datasets. Different research experiments, case scenarios, and examples are explained in this book. The book provides a comprehensive description and step-by-step practical hands-on guide to carrying out the different types of statistical analysis in R particularly for research purposes with examples. Ranging from how to import and store datasets in R as objects, how to code and call the methods or functions for manipulating the datasets or objects, factorization, and vectorization, to better reasoning, interpretation, and storage of the results for future use, and graphical visualizations and representations thus congruence of Statistics and Computer programming in Research.

This book contains peer-reviewed selected papers from the 6th International Conference on the Future of Education (FOE 2023). It presents excellent educational practices and technologies complemented by various innovative approaches that enhance educational outcomes. The conference, in particular, places great attention on solutions to educational problems that are highly aligned with four Sustainable Development Goals from the seventeen goals designed by UNESCO. The book focuses on quality education, industry, innovation, and infrastructure, reduced inequalities, etc. The FOE 2023 proceedings offer contributions covering a diverse range of innovations and technology in education and how they may facilitate the current stages of education and shape future avenues for offering quality and accessible education. Moreover, the articles presented in this book present dynamic computing and pedagogical approaches to empower learners and educators across the globe. As our planet continues to tackle international crises including poverty, climate change, limited access to technological tools, and global pandemics, remote and/or online teaching and learning find paramount importance, which has also been considered a powerful theme in the presented articles. These essential components highly contribute to reduced inequalities serving learners from higher education levels to lifelong learners while playing a crucial role in closing the gap between the skill set obtained by the graduates and those demanded by the job market.