Abstract
Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases. (C) 2021 The Author( s). Published by Elsevier B.V. on behalf of International Institute of Forecasters.

Abstract
Based on many years of experience as a management consultant in different industries and corporate structures and cultures, the motivation to use digital transformation in connection with variable corporate goals-such as fluctuating workloads, agile response to customer inquiries, and ecological and economic sustainability-results in a process or a product to be developed that intelligently adapts to market requirements and requires forward-looking leadership. Using an AI-based methodical analysis and synthesis approach, the high consumption of economic and human resources is to be continuously monitored and optimization measures initiated at an early stage. The necessary information technology with its infrastructure and architecture is the starting point to accompany the agility and changeability of corporate goals. Researching the relevant documents begins with writing the panorama or the state of knowledge on the topic. This article is about the IT infrastructure based on the requirements for an architecture and behavior that a versatile, agile company needs to accompany the constantly changing framework conditions of the market. The technology used and the available resources, including the human resources, need to be adapted as early as possible. Data now represent the most valuable asset on Earth and future industrial manufacturing systems must maximize the opportunity of data usage. Low-level data must be transformed to make them useful in supporting intelligent decision-making, for example. Furthermore, future manufacturing systems must be highly productive, adaptable, absent of error, and kind to the environment and to local communities. The all-important design should minimize the waste of material, capital, energy, and media. Herein, we discuss the fulfilling of agile customer requirements involving adaptable and modulated production processes (related to the 'agile manufacturing' and 'digital transformation' perspectives).

Abstract

Abstract
Gamification has been growing at a meteoric rate. Such growth is because this is a valid mechanism to add desirable behaviors in an organizational process or even in an educational process. In fact, these are the two major contexts where gamification has been applied. In organizations, gamification is applied in various business contexts from recruitment, through onboarding, training, talent retention, customer service, sales, and marketing. In education, gamification is used essentially in contexts of promoting student involvement in existing training offers. This chapter presents a gamification design framework called GAFRHE aimed to be used in all domains, but with extensive facets for the healthcare domain. Unlike other frameworks, it is a concrete framework that not only presents the basic concepts that must be followed by the gamified strategy, but also presents a system architecture that must be instantiated, and a set of components already coded and that can be used. The framework is mostly based on existing standards promoting reusability and interoperability.

Abstract
Ester-based dielectric fluids have now been on the market for several decades, providing fire-safe and environmentally friendly alternatives to mineral oils, which have traditionally been used in transformers and other electrical equipment. This opens the door to innovation in power transformers. However, the use of esters-based dielectrics in power transformers is still very limited, especially for the higher voltage levels. The usage of these esters-based dielectrics in higher voltage power transformers is not yet consensual. this work present results with the use of natural esters in power distribution transformers. Tests carried out on mineral oil and natural ester oil found that the ester-based dielectric can withstand higher voltage thresholds for AC and Impulses tests, mainly within the specs of destructive tests, e.g., the natural ester was able to withstand a 185kV impulse without registering dielectric rupture while the natural oil registered a dielectric rupture with a 160kV impulse. Heating and mechanical tests demonstrated that ester-based dielectric oils for power transformers lead to a flow reduction between 16,8% and 18,2% in the cooling system that was design for mineral oils but they achieve a higher heat transfer coefficient, between 0,5% to 5% depending on the location of measurement. © Published under licence by IOP Publishing Ltd.

Abstract
Tampered multimedia content is increasingly being used in a broad range of cybercrime activities. The spread of fake news, misinformation, digital kidnapping, and ransomware-related crimes are among the most recurrent crimes in which manipulated digital photos are being used as an attacking vector. One of the linchpins of accurately detecting manipulated multimedia content is the use of machine learning and deep learning algorithms. This work proposed a dataset of photos and videos suitable for digital forensics, which has been used to benchmark Support Vector Machines (SVM) and Convolution Neural Networks algorithms (CNN). An SVM-based module for the Autopsy digital forensics open-source application has also been developed. This was evaluated as a very capable and useful forensic tool, winning second place on the OSDFCon international Autopsy modules competition.