In information technology, the concepts of cost, time, delivery, space, quality, durability, and price have gained greater importance in solving managerial decision-making problems in supply chain models, transportation problems, and inventory control problems. Moreover, competition is becoming tougher in imprecise environments. Neutrosophic sets and logic are gaining significant attention in solving real-life problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistency, and indeterminacy. Neutrosophic Sets in Decision Analysis and Operations Research is a critical, scholarly publication that examines various aspects of organizational research through mathematical equations and algorithms and presents neutrosophic theories and their applications in various optimization fields. Featuring a wide range of topics such as information retrieval, decision making, and matrices, this book is ideal for engineers, technicians, designers, mathematicians, practitioners of mathematics in economy and technology, scientists, academicians, professionals, managers, researchers, and students.

Aligning Enterprise, System, and Software Architectures covers both theoretical approaches and practical solutions in the processes for aligning enterprise, systems, and software architectures. This book aims to provide architects and researchers with a clear understanding of all three types of architectures.

This book discusses quantum theory as the theory of random (Brownian) motion of small particles (electrons etc.) under external forces. Implying that the Schroedinger equation is a complex-valued evolution equation and the Schroedinger function is a complex-valued evolution function, important applications are given. Readers will learn about new mathematical methods (theory of stochastic processes) in solving problems of quantum phenomena. Readers will also learn how to handle stochastic processes in analyzing physical phenomena.

Modeling techniques provide ample opportunities for progress across numerous fields. When analyzing complex systems, new methods allow for a deeper understanding of system dynamics. Method of Systems Potential (MSP) Applications in Economics: Emerging Research and Opportunities is an innovative source of academic research that examines the Method of Systems Potential for complex systems analysis in economical contexts. Highlighting critical perspectives on topics such as system efficiency, adaptive algorithms, and variable parameters, this book is ideally designed for researchers, academics, graduate students, and practitioners interested in the latest uses and applications of modeling techniques.

Throughout the past decade, the notion of ontologies has influenced research in many application areas including databases, information retrieval, electronic commerce, natural language processing, knowledge management, enterprise systems, systems analysis and design, the Web, and more.Ontology-Based Applications for Enterprise Systems and Knowledge Management provides an opportunity for readers to clearly understand the notion of ontology engineering and the practical aspects of this approach in the domains of two interest areas: Knowledge Management Systems and Enterprise Systems. A perfect reference for researchers, scholars, postgraduate students, and practitioners, this book aims to gather the recent advances and research findings of various topics in ontology use for these application areas.

Learn how to design and develop robotic process automation solutions with Blue Prism to perform important tasks that enable value creation in your work Key Features Develop robots with Blue Prism Automate your work processes with Blue Prism Learn basic skills required to train a robot for process automation Book DescriptionRobotic process automation is a form of business process automation where user-configured robots can emulate the actions of users. Blue Prism is a pioneer of robotic process automation software, and this book gives you a solid foundation to programming robots with Blue Prism. If you've been tasked with automating work processes, but don't know where to start, this is the book for you! You begin with the business case for robotic process automation, and then move to implementation techniques with the leading software for enterprise automation, Blue Prism. You will become familiar with the Blue Prism Studio by creating your first process. You will build upon this by adding pages, data items, blocks, collections, and loops. You will build more complex processes by learning about actions, decisions, choices, and calculations. You will move on to teach your robot to interact with applications such as Internet Explorer. This can be used for spying elements that identify what your robot needs to interact with on the screen. You will build the logic behind a business objects by using read, write, and wait stages. You will then enable your robot to read and write to Excel and CSV files. This will finally lead you to train your robot to read and send emails in Outlook. You will learn about the Control Room, where you will practice adding items to a queue, processing the items and updating the work status. Towards the end of this book you will also teach your robot to handle errors and deal with exceptions. The book concludes with tips and coding best practices for Blue Prism. What you will learn Learn why and when to introduce robotic automation into your business processes Work with Blue Prism Studio Create automation processes in Blue Prism Make use of decisions and choices in your robots Use UI Automation mode, HTML mode, Region mode, and spying Learn how to raise exceptions Get the robot to deal with errors Learn Blue Prism coding best practices Who this book is forThe book is aimed at end users such as citizen developers who create business processes, but may not have the basic programming skills required to train a robot. No experience of BluePrism is required.

This book chronicles a 10-year introduction of blended learning into the delivery at a leading technological university, with a longstanding tradition of technology-enabled teaching and learning, and state-of-the-art infrastructure. Hence, both teachers and students were familiar with the idea of online courses. Despite this, the longitudinal experiment did not proceed as expected. Though few technical problems, it required behavioural changes from teachers and learners, thus unearthing a host of socio-technical issues, challenges, and conundrums. With the undercurrent of design ideals such as "tech for good", any industrial sector must examine whether digital platforms are credible substitutes or at best complementary. In this era of Industry 4.0, higher education, like any other industry, should not be about the creative destruction of what we value in universities, but their digital transformation. The book concludes with an agenda for large, repeatable Randomised Controlled Trials (RCTs) to validate digital platforms that could fulfil the aspirations of the key stakeholder groups - students, faculty, and regulators as well as delving into the role of Massive Open Online Courses (MOOCs) as surrogates for "fees-free" higher education and whether the design of such a HiEd 4.0 platform is even a credible proposition. Specifically, the book examines the data-driven evidence within a design-based research methodology to present outcomes of two alternative instructional designs evaluated - traditional lecturing and blended learning. Based on the research findings and statistical analysis, it concludes that the inexorable shift to online delivery of education must be guided by informed educational management and innovation.

This book provides a concise point of reference for the most commonly used regression methods. It begins with linear and nonlinear regression for normally distributed data, logistic regression for binomially distributed data, and Poisson regression and negative-binomial regression for count data. It then progresses to these regression models that work with longitudinal and multi-level data structures. The volume is designed to guide the transition from classical to more advanced regression modeling, as well as to contribute to the rapid development of statistics and data science. With data and computing programs available to facilitate readers' learning experience, Statistical Regression Modeling promotes the applications of R in linear, nonlinear, longitudinal and multi-level regression. All included datasets, as well as the associated R program in packages nlme and lme4 for multi-level regression, are detailed in Appendix A. This book will be valuable in graduate courses on applied regression, as well as for practitioners and researchers in the fields of data science, statistical analytics, public health, and related fields.

Inverse problems such as imaging or parameter identification deal with the recovery of unknown quantities from indirect observations, connected via a model describing the underlying context. While traditionally inverse problems are formulated and investigated in a static setting, we observe a significant increase of interest in time-dependence in a growing number of important applications over the last few years. Here, time-dependence affects a) the unknown function to be recovered and / or b) the observed data and / or c) the underlying process. Challenging applications in the field of imaging and parameter identification are techniques such as photoacoustic tomography, elastography, dynamic computerized or emission tomography, dynamic magnetic resonance imaging, super-resolution in image sequences and videos, health monitoring of elastic structures, optical flow problems or magnetic particle imaging to name only a few. Such problems demand for innovation concerning their mathematical description and analysis as well as computational approaches for their solution.

The nonequilibrium behavior of nanoscopic and biological systems, which are typically strongly fluctuating, is a major focus of current research. Lately, much progress has been made in understanding such systems from a thermodynamic perspective. However, new theoretical challenges emerge when the fluctuating system is additionally subject to time delay, e.g. due to the presence of feedback loops. This thesis advances this young and vibrant research field in several directions. The first main contribution concerns the probabilistic description of time-delayed systems; e.g. by introducing a versatile approximation scheme for nonlinear delay systems. Second, it reveals that delay can induce intriguing thermodynamic properties such as anomalous (reversed) heat flow. More generally, the thesis shows how to treat the thermodynamics of non-Markovian systems by introducing auxiliary variables. It turns out that delayed feedback is inextricably linked to nonreciprocal coupling, information flow, and to net energy input on the fluctuating level.

Kansei Engineering and Soft Computing: Theory and Practice offers readers a comprehensive review of kansei engineering, soft computing techniques, and the fusion of these two fields from a variety of viewpoints. It explores traditional technologies, as well as solutions to real-world problems through the concept of kansei and the effective utilization of soft computing techniques. This publication is an essential read for professionals, researchers, and students in the field of kansei information processing and soft computing providing both theoretical and practical viewpoints of research in humanized technology.

This book presents theoretical modeling and numerical simulations applied to drive several applications towards Industrial Revolution 4.0 (IR 4.0). The topics discussed range from theoretical parts to extensive simulations involving many efficient algorithms as well as various statistical techniques. This book is suitable for postgraduate students, researchers as well as other scientists who are working in mathematics, statistics and numerical modeling and simulation.

This book shows how information theory, probability, statistics, mathematics and personal computers can be applied to the exploration of numbers and proportions in music. It brings the methods of scientific and quantitative thinking to questions like: What are the ways of encoding a message in music and how can we be sure of the correct decoding? How do claims of names hidden in the notes of a score stand up to scientific analysis? How many ways are there of obtaining proportions and are they due to chance? After thoroughly exploring the ways of encoding information in music, the ambiguities of numerical alphabets and the words to be found "hidden" in a score, the book presents a novel way of exploring the proportions in a composition with a purpose-built computer program and gives example results from the application of the techniques. These include information theory, combinatorics, probability, hypothesis testing, Monte Carlo simulation and Bayesian networks, presented in an easily understandable form including their development from ancient history through the life and times of J. S. Bach, making connections between science, philosophy, art, architecture, particle physics, calculating machines and artificial intelligence. For the practitioner the book points out the pitfalls of various psychological fallacies and biases and includes succinct points of guidance for anyone involved in this type of research. This book will be useful to anyone who intends to use a scientific approach to the humanities, particularly music, and will appeal to anyone who is interested in the intersection between the arts and science.With a foreword by Ruth Tatlow (Uppsala University), award winning author of Bach's Numbers: Compositional Proportion and Significance and Bach and the Riddle of the Number Alphabet."With this study Alan Shepherd opens a much-needed examination of the wide range of mathematical claims that have been made about J. S. Bach's music, offering both tools and methodological cautions with the potential to help clarify old problems." Daniel R. Melamed, Professor of Music in Musicology, Indiana University

Free/Open Source Enterprise Resource Planning systems (FOS-ERP) are gaining popularity and acceptance due to two main factors: their lack of licensing fees and customizability. Given this, organizations are able to easily adopt and manipulate these systems to meet their individual needs. Free and Open Source Enterprise Resource Planning: Systems and Strategies unites research on FOS-ERP, comparing differences with proprietary Enterprise Resource Planning products, and demonstrating key research factors. It includes cases demonstrating how small enterprises have benefited from FOS-ERP in Spain and in Belgium, along with difficulties encountered and solutions developed. This essential reference addresses key issues such as security and legal risks, as well as challenges, opportunities, and barriers to adoption.