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Gamification is a potential approach to foster motivation and engagement in different contexts which popularity in recent years has encouraged its application in a diversity of domains, including health, education, business, society, or tourism. However, although all their promising benefits and rapidly developing, the gamification community should face a variety of theoretical, empirical, and technological challenges. Focusing on technological challenges, we can observe a need that claims for suitable gamification software tools that offer system-independence and flexibility, support the gamification design, implementation, and monitoring activities, and experiment with more game elements than only points, badges, and leaderboards. For that reason, this paper deals with the identified technological challenges by introducing a gamification software tool to cover the main lacks found. An analysis of the advances in gamification domain and their recent literature was conducted to identify the strengths and weaknesses of the most popular gamification software tools in order to design and develop a flexible system-independent gamification software solution that goes beyond the implementation of the classic game elements. As a result, we created GoRace, a multi-context and narrative-based gamification suite that supports the entire gamification process, provides flexible and system-independent gamification solutions, and allows the creation of tailored and reusable gamification solutions that go beyond the classic game elements to immerse participants in a fun, engaging, and challenging narrative-based gamification experience.

Precision Agriculture (PA) and Agriculture 4.0 (A4.0) have been widely discussed as a medium to address the challenges related to agricultural production. In this research, we present a Systematic Literature Review (SLR) supported by a Bibliometric Performance and Network Analysis (BPNA) of the use of A4.0 technologies and PA techniques in the coffee sector. To perform the SLR, 87 documents published since 2011 were extracted from the Scopus and Web of Science databases and processed through the Preferred Reporting Items for Systematic reviews and Meta-Analyzes (PRISMA) protocol. The BPNA was carried out to identify the strategic themes in the field of study. The results present 23 clusters with different levels of development and maturity. We also discovered and presented the thematic network structure of the most used A4.0 technologies in the coffee sector. Our findings shows that Internet of Things, Machine Learning and geostatistics are the most used technologies in the coffee sector, we also present the main challenges and trends related to technological adoption in coffee systems. We believe that the demonstrated results have the potential to be considered by researchers in future works and decision making related to the field of study.

The detection of performance bugs, like those causing an unexpected execution time, has gained much attention in the last years due to their potential impact in safety-critical and resource-constrained applications. Much effort has been put on trying to understand the nature of performance bugs in different domains as a starting point for the development of effective testing techniques. However, the lack of a widely accepted classification scheme of performance faults and, more importantly, the lack of well-documented and understandable datasets makes it difficult to draw rigorous and verifiable conclusions widely accepted by the community. In this paper, we present TANDEM, a dual contribution related to real-world performance bugs. Firstly, we propose a taxonomy of performance bugs based on a thorough systematic review of the related literature, divided into three main categories: effects, causes and contexts of bugs. Secondly, we provide a complete collection of fully documented real-world performance bugs. Together, these contributions pave the way for the development of stronger and reproducible research results on performance testing.

In the last decade, the advertising industry has experienced a quantum leap, powered by recent advances in neuroscience, a large investment in artificial intelligence, and a high degree of consumer expertise. Within this context, opinion mining, sentiment analysis, and emotion understanding bring us closer to one of the most sought-after objectives of advertising: to offer relevant ads at scale. The importance of studies about opinion mining, sentiment analysis, and emotion understanding in advertising has been rising exponentially over the last years. The peak of this new situation has been the interest of the research community in studying the relationship between such innovations and the spread of smart and contextual advertising. This article analyzes those works that address the relationship between sentiment analysis, opinion mining, and emotion understanding in advertising. The main objective is to clarify the current state of these studies, explore issues, methods, findings, themes, and gaps as well as to define their significance within the current convergence advertising research scenario. To reach such objectives, a bibliometric analysis was conducted, retrieving and analyzing 919 research works published between 2010 and 2019 based on results from Web of Science (WoS)., Programa Operativo FEDER Andalucia UMA 18-FEDERJA-148

Falls can have serious consequences for people, leading to restrictions in mobility or, in the worst case, to traumatic-based cases of death. To provide rapid assistance, a portable fall detection system has been developed that is capable of detecting fall situations and, if necessary, alerting emergency services without any user interaction. The prototype is designed to facilitate reliable fall detection and to classify several fall types and human activities. This solution represents a life-saving service for every person that will significantly improve assistance in the case of fall events, which are a part of daily life. Additionally, this approach facilitates independent system operation, since the system does not depend on sensor or network units located within a building structure. This article also introduces fall analysis. To guarantee functional safety, a hazard analysis method named system-theoretic accident model and processes (STAMP) is applied.

In the recent years, the use of Information and Communication Technologies (ICTs) to enhance the educational and developmental interventions of individuals with intellectual disabilities has increased drastically. Current literature about the efficacy of assistive technologies for people with intellectual disabilities includes numerous examples of co-design and research involving people with intellectual disabilities and their stakeholders. However, literature regarding the challenges and opportunities presented by this research is scarce. The discussion and reflection presented in this work is based on the authors' previous experience and ground-breaking literature in the field. After a review of relevant work, the the authors' research is described in detail, in order to reflect on the challenges encountered, and on opportunities for new researchers and open questions. The paper concludes with a reflection on the use of technologies to support people with intellectual disabilities, adopted strategies and limitations., This work was supported in part by the Tenure of an ERCIM Alain Bensoussan Postdoctoral Fellowship, and in part by the Project e-Madrid under Grant P2018/TCS-4307

Over the last years, the Internet of Things has fostered a growing interest in context-aware mobile applications; this fact is mainly due to highly favoring information provision from multiple Internetconnected devices. To identify user context, these applications collect information from the user and his/her environment and typically lter app information, so that the user receives only the interesting and relevant information. However, such a task usually implies further resource consumption on user mobile devices, not only regarding battery usage but also in terms of network traf c. Accordingly, although context-aware applications can improve user experiences in their daily lives, they must ensure the maintenance of lowlevel resource consumption; otherwise, the applications are promptly replaced by less consuming ones, and therefore, removed from the mobile market. In this paper, we evaluate and discuss several architectural styles for context-aware mobile applications, as well as, providing a set of guidelines to decide on the right architecture for a particular app depending on its characteristics. The use of such guidelines when choosing the right architectural style can strongly in uence the resource consumption of context-aware mobile applications. Following these guidelines, user satisfaction of a context-aware mobile application may be improved, thus guaranteeing the app success.

A visual programming language allows users and developers to create programs by manipulating program elements graphically. Several studies have shown the bene ts of visual languages for learning purposes and their applicability to robot programming. However, at present, there are not enough comparative studies on the suitability of textual and visual languages for this purpose. In this paper, we study if, as with a textual language, the use of a visual language could also be suitable in the context of robot programming and, if so, what the main advantages of using a visual language would be. For our experiments, we selected a sample of 60 individuals among students with adequate knowledge of procedural programming, that was divided into three groups. For the rst group of 20 students, a learning scenario based on a textual objectoriented language was used for programming a speci c commercial robotic ball with sensing, wireless communication, and output capabilities, whereas for the second and the third group, two learning scenarios based on visual languages were used for programming the robot. After taking a course for programming the robot in the corresponding learning scenario, each group was evaluated by completing three programming exercises related to the robot features (i.e. motion, lighting, and collision detection). Our results show that the students that worked with visual languages perceived a higher clarity level in their understanding of the course exposition, and a higher enjoyment level in the use of the programming environment. Moreover, they also achieved an overall better mark. Agencia Española de Investigación (AEI) TIN2017-85797-R