Abstract

Abstract
The rapid proliferation of human population and the growth of consumption leaded to an increase of hazardous waste. This becomes a worldwide ecological and environmental challenge. According to last available statistics the estimated global municipal solid waste reached 2.02 billion tons. Unfortunately there is not only solid waste: vegetable oil, one kind of liquid waste, used in food manufacturing, is responsible for serious contamination of water resources. Its collection is profitable by recycling into biodiesel and is already regulated in some countries. However it faces several logistic issues. Major issues are related to collection delays, which lead to oil giveaway, and reduced collection [1,2]. This paper proposes a solution to some of these logistic problems introducing a system to manage cooking oil collection in order to increase collection profits. The developed system follows a defined oil collection plan in order to optimize collection routes, introducing a sensor network that triggers collection events to a central system overcoming the current collection delays and wastes. The system is being tested in a real scenario with a Portuguese cooking oil collection company.

Abstract
With the increase of distance learning, in general, and e-learning, in particular, having a system capable of determining the engagement of students is of primordial importance, and one of the biggest challenges, both for teachers, researchers and policymakers. Here, we present a system to detect the engagement level of the students. It uses only information provided by the typical built-in web-camera present in a laptop computer, and was designed to work in real time. We combine information about the movements of the eyes and head, and facial emotions to produce a concentration indexwith three classes of engagement: very engaged, nominally engaged and not engaged at all. The system was tested in a typical e-learning scenario, and the results show that it correctly identifies each period of time where students were very engaged, nominally engaged and not engaged at all. Additionally, the results also show that the students with best scores also have higher concentration indexes.

Abstract
When crowd workers provide their contributions in a shared working environment, they may be influenced by the inputs of other contributors in implicit ways. Stigmergy in crowdsourcing consists of tracking changes in work activities to guide crowd workers based on the digital traces left by other workers. In such scenarios, there is no direct communication between the contributors. Still, the traceable changes they left during their actions act as a mediating element that clearly affects the final work product. From a behavior analysis perspective, the properties recorded in event logs can be of practical value in observing the behavioral traces produced by crowd workers when performing microtasks. This form of task fingerprinting has been explored for over a decade to better understand performance-related data and user navigational behavior in crowdsourcing markets. In line with this, the goal of this paper is to study the feasibility of task fingerprinting alongside the stigmergic effect occurring in a crowdsourcing setting through a user event logger. To this end, a case study was conducted using a real-world scenario of extreme weather phenomena represented on interactive maps. Each user could observe the traces of other crowd members while providing annotations. Twelve experts in weather forecasting were recruited to participate in this study to annotate extreme weather events. The results indicate that it is possible to use task fingerprinting for tracking the stigmergic effect in such activities with gains in terms of implicit coordination. Furthermore, the task fingerprinting allowed to map participants with similar behavioral traces, suggesting an increase in the accuracy of annotation clusters.

Abstract
Our study provides valuable insights into the relationship between artificial intelligence (AI) and Human Resource Management (HRM). We have minimised bias and ensured reliable findings by employing a systematic literature review and the PRISMA statement. Our comprehensive syn-thesis of the studies included in this research, along with a bibliometric analysis of articles, journals, indexes, authors' affiliations, citations, keyword co-occurrences, and co-authorship analysis, has produced robust results. The discussion of our findings focuses on critical areas of interest, such as AI and Talent, AI Bias, Ethics and Law, and their impact on Human Resource (HR) management. Our research highlights the recognition by organisations of the importance of talent management in achieving a competitive advantage as higher-level skills become increas-ingly necessary. Although some HR managers have adopted AI technology for talent acquisition, our study reveals that there is still room for improvement. Our study is in line with previous research that acknowledges the potential for AI to revolutionise HR management and the future of work. Our findings emphasise the need for HR managers to be proactive in embracing technology and bridging the technological, human, societal, and governmental gaps. Our study contributes to the growing body of AI and HR management knowledge, providing essential insights and rec-ommendations for future research. The importance of our study lies in its focus on the role of HR in promoting the benefits of AI-based applications, thereby creating a larger body of knowledge from an organisational perspective.

Abstract
This paper presents an educational resource to support the teaching of Portuguese sign language. This educational resource emerges in response to the significant needs for the development of adequate digital tools to support deaf people in different tasks, especially in the language learning process. This work is motivated by the results and conclusions from previous studies that identify augmented reality as one of the promising solutions to improve the learning and teaching processes, and benefits from the advances already accomplished in the development and application of augmented reality solutions in several domains of the educational environment. The educational resource presented in this work is an augmented reality solution that enables associating hand gestures, representative of Portuguese sign language, to different cards, which represent different letters of the alphabet. In this way, it is possible to associate the alphabet letters with the respective gestures in a visual and straightforward way, facilitating the learning process.