Abstract
Authenticity, traceability and certification are key to assure both quality and confidence to wine consumers and an added commercial value to farmers and winemakers. Grapevine variety stands out as one of the most relevant factors to be considered in wine identification within the whole wine sector value chain. Ampelography is the science responsible for grapevine varieties identification based on (i) in-situ visual inspection of grapevine mature leaves and (ii) on the ampelographer experience. Laboratorial analysis is a costly and time-consuming alternative. Both the lack of experienced professionals and context-induced error can severely hinder official regulatory authorities’ role and therefore bring about a significant impact in the value chain. The purpose of this paper is to assess deep learning potential to classify grapevine varieties through the ampelometric analysis of leaves. Three convolutional neural networks architectures performance are evaluated using a dataset composed of six different grapevine varieties leaves. This preliminary approach identified Xception architecture as very promising to classify grapevine varieties and therefore support a future autonomous tool that assists the wine sector stakeholders, particularly the official regulatory authorities.

Abstract
Counting subgraph occurrences is a hard but very important task in complex network analysis, with applications in concepts such as network motifs or graphlet degree distributions. In this paper we present a novel approach for this task that takes advantage of knowing that a large fraction of subgraph types does not appear at all on real-world networks. We describe a pattern-growth methodology that is able to iteratively build subgraph patterns that do not contain smaller non-occurring subgraphs, significantly pruning the search space. By using the g-trie data structure, we are able to efficiently only count those subgraphs that we are interested in, reducing the total computation time. The obtained experimental results are very promising allowing us to avoid the computation of up to 99.78% of all possible subgraph patterns. This showcases the potential of this approach and paves the way for reaching previously unattainable subgraph sizes. © Springer Nature Switzerland AG 2019.

Abstract
In the world of mobile robot navigation, the ultrasonic sensors stand out for presenting attractive features at an affordable cost. The main problem in the use of these devices lies in the difficulty of correctly interpreting the obtained data, which means that their efficiency is limited. This paper focuses on the improvement and implementation of a low cost location system based on ultrasonic sensors. Through the combination of mathematical techniques and signal processing it is possible to make the system more accurate and reliable. The developed system includes the data acquisition, the signal filtering, and the trigonometric methods to estimate the coordinates of a target and can be assembled in a mobile robot.

Abstract
Communication among the different actors present in the school ecosystem is an essential issue. However, in a hectic world where parents do not have much time to visit schools regularly, it is crucial to create mechanisms to better monitor student's success and school demands. The interaction among school, students and parents presents a growing complex challenge. Technology has, in recent years, shaped the concepts of learning support and monitoring - both in school and out of school - as well as the way information flows among all actors in the school ecosystem. Emergently, the evolution of mobile applications, coupled with the evolution of mobile device capabilities, has made possible to create new and more effective intercommunication mechanisms, with ubiquitous approaches and in a predictable scenario of less willingness to physically interaction of the different actors. Based on these assumptions, this paper reflects on the potential of mobile devices and their applications to support new models of intercommunication among parents or school sponsors, students and teachers. Accordingly, a conceptual model is proposed that represents a work in progress that aims the creation and evaluation of a prototype system capable of improve de intercommunication and the overall success of the school learning system societal challenges.

Abstract
Purpose: This paper aims to examine the mediating role of brand satisfaction and brand trust in brand equity antecedents and outcomes through an empirical investigation of brand equity elements. Design/methodology/approach: A survey was conducted in Pune and Mumbai, two prominent cities of India. A structured questionnaire focussed on garnering responses on measuring brand equity antecedents and outcomes was circulated to the cell phone users. The questionnaire aimed to assess the role of two additional variables, namely, brand satisfaction and brand trust, in the existing and the conceptual model of brand equity (Keller, 2001). Based on the data analysis, a structural equations path and the mediating model were developed. Findings: The findings of this study show that the new brand equity model is highly relevant in predicting brand equity as compared to the existing brand equity model (Keller, 2001). The brand equity mediation model clearly elucidates the role of brand trust and brand satisfaction. Research limitations/implications: With reference to a theoretical contribution, the study broadens the existing hypothetical model of brand equity. The findings of this research provide a strategic and analytical model for brand managers to build brand relationships among their consumers. Originality/value: The present study challenges the existing model of brand equity (Keller, 2001) and further makes an effort to fill in the gaps in the existing theoretical model of brand equity. © 2019, Umesh Ramchandra Raut, Prafulla Arjun Pawar, Pedro Quelhas Brito and Gyanendra Singh Sisodia.

Abstract
Enterprises have been challenged to adopt practices of sustainability to benefit shareholders and society with goods standing much beyond monetary profit or required by law. In combination with environmental and economic concerns, Corporate Social Responsibility (CSR) has become an option to leverage businesses with good reputation and to attract sustainability-aware market segments. In line with such a demand, this paper presents a systematic literature review of conceptual modeling studies referring explicitly to certifications, laws or norms of CSR. The more specific research goal of this work is to discover ontologies for representing CSR best practices, design patterns or policies. In total, 921 peer-reviewed papers were analyzed, from which only 17 were considered relevant for data extraction. The main result of this work is the identification of a research gap in explicit knowledge representation of CSR practices for Information Systems design, which ought to be filled to complement the (dominant) economic perspective on sustainability.