Abstract
This paper develops a novel short-term load forecasting technique to predict the demanding power for the next hour. In this study, a linear equation-error Auto Regressive Auto Regressive Moving Average Exogenous (ARARMAX) model is trained to specify power consumption as a function of a few past hours. The parameters of the candidate mathematical model are estimated by using two least squares-based iterative algorithms. The main difference with these algorithms is the total number of past data involved in the modeling. Whereas practical data are always subject to noise and un-accurate measuring, a wavelet de-noising technique is utilized to reduce the effect of noise on forecasting which leads to more precise predictions. The superiority of the proposed approach is validated by utilizing practical data from a power utility in Canada in January 1995. The first three days' data are utilized to train the selected model and the fourth-day data are dedicated to test the prediction of the provided model. The L-2 and L-infinity norms error and MAPE, MAE, and RMSE are selected as criteria to show the merits of the proposed approach.

Abstract
The use of Educational Software (ES) in education has become essential for teachers and students. On the one hand, the effectiveness of its use may facilitate the acquisition of learning and on the other hand, it may enable a better transmission of the contents. In this sense, it is necessary to provide teachers with tools that allow them to develop successful pedagogical actions with appealing and innovative resources, capable of stimulating creativity and motivating students for learning. The aim of this study is to ascertain the knowledge and the use by teachers of ES Kahoot, GeoGebra and Texas Ti-Nspire, in what type of content, activities and what is the impact of their use in the teaching of Geometry and Measurement (GM), whether in teaching practice of teachers, or in the learning of students. The adopted method has a qualitative nature, with characteristics of a case study. Fourteen teachers who teach Mathematics at various schools in Portugal participated. Two questionnaires and a challenge that consisted of the elaboration of tasks were used as instruments. Data analysis was performed using Excel (Office 2016) and content analysis of the answers given, and the tasks developed. The results suggest that of the three ES, Kahoot was the most unknown and was the most chosen by teachers to develop different GM content. The reasons are also described as to why these ES may cause an improvement in the teaching practices of teachers, as well as motivation and student learning.

Abstract
Family businesses (FBs) are central to economies: in Portugal the impact of these structures reaches 2/3 of the GDP, 1/2 of the labour force, and 4/5 of the firms in operation, most of them being SMEs. These organisations play a central role in terms of job creation, local development, knowledge transfer, and territorial cohesion. Innovative activities are key factors for competitive economies; yet innovation increases risk exposure and FBs are conservative and risk adverse, resisting change, relying on internal factors rather than opening to the external environment, consequently postponing innovation and thus pledging their future. Their embedded culture reduces innovative propensity; still, the existence loyalty trust and informal networks enhance individual or collective innovation processes. Using a dataset of 110 FBs innovation and internationalization along with other structural characteristics are connected to their economic performance, shedding light on the determinants FB economic efficiency. Given their importance, made-to-measure policy schemes should be designed.

Abstract
In this work, a long-period fiber grating (LPG) based sensor was evaluated as a sensing device for micro-force measurement, in the order of micro Newtons. It was used an LPG fabricated by arc-inducted technique in a SMF-28 standard optical fiber. The optical fiber was fixed between two clamps with a separation of 150 mm with the middle of the LPG located at the center. Characterizations were performed in terms of temperature, curvature and strain. The grating was then used as a micro-force sensor by means of both curvature and strain, induced by a hung mass in a stretched fiber. Furthermore, the evaluation of a precurvature LPG was performed to assess if an increase of sensitivity is achieved. Micro-force sensitivity achieved with the stretched LPG was 1.41 nm/mN and it was demonstrated that its sensitivity can be enhanced to 5.14 nm/mN with a pre-curvature of 2.2 m–1 applied to the LPG, achieving a spectral resolution of at least 15.6 µN.

Abstract
Although the relationship between supply chain (SC) and innovation has attracted attention from researchers in recent years, the relationship between innovation capabilities and SC strategies is a subject that has not yet been explored extensively. The main objective of this paper is to examine how SC strategies affect the relationship between innovation capabilities and business performance. The paper, characterised as a conceptual paper with the aim of contributing to theory building, is based on the concept of fit and on the principles of the contingency theory and the resource-based view. Further, a literature review and a theoretical discussion, a theoretical model and a set of research propositions are presented. The theoretical rationale shows the potential for improvement in performance through the relationship between innovation and SC and can be used to boost empirical research on the topic. Copyright © 2020 Inderscience Enterprises Ltd.

Abstract
Many undergraduate engineering students have just a single introductory feedback control course in their study list. Often the curricula found in such courses is totally based on continuous time-domain classic control techniques. However, currently most control design techniques are implemented in digital machines. Thus, digital control concepts should be covered in introductory control courses. In this paper, the issue of how to implement and test digital industrial controllers is addressed. Teaching experiments based on the APMonitor temperature control lab (TCLab) are proposed. It will be shown that TCLab as an Arduino based portable kit, provides an excellent means to test digital controllers, as it is a compact and portable lab to be used by lecturers and students. While there are many low-cost and portable hardware options for teaching dynamics and control, a novel aspect of this paper is the digital control education methods that are validated with classroom experience, particularly with Biomedical and Bioengineering students. Preliminary results are presented. Copyright (C) 2020 The Authors.