The Value-Sensitive Conversational Agent Co-Design Framework

Conversational agents (CAs) are gaining traction in both industry and academia, especially with the advent of generative AI and large language models. As these agents are used more broadly by members of the general public and take on a number of critical use cases and social roles, it becomes important to consider the values embedded in these systems. This consideration includes answering questions such as 'whose values get embedded in these agents?' and 'how do those values manifest in the agents being designed?' Accordingly, the aim of this paper is to present the Value-Sensitive Conversational Agent (VSCA) Framework for enabling the collaborative design (co-design) of value-sensitive CAs with relevant stakeholders. Firstly, requirements for co-designing value-sensitive CAs which were identified in previous works are summarised here. Secondly, the practical framework is presented and discussed, including its operationalisation into a design toolkit. The framework facilitates the co-design of three artefacts that elicit stakeholder values and have a technical utility to CA teams to guide CA implementation, enabling the creation of value-embodied CA prototypes. Finally, an evaluation protocol for the framework is proposed where the effects of the framework and toolkit are explored in a design workshop setting to evaluate both the process followed and the outcomes produced.Comment: 23 pages, 8 figure

G-Asks: An Intelligent Automatic Question Generation System for Academic Writing Support

Many electronic feedback systems have been proposed for writing support. However, most of these systems only aim at supporting writing to communicate instead of writing to learn, as in the case of literature review writing. Trigger questions are potentially forms of support for writing to learn, but current automatic question generation approaches focus on factual question generation for reading comprehension or vocabulary assessment. This article presents a novel Automatic Question Generation (AQG) system, called G-Asks, which generates specific trigger questions as a form of support for students' learning through writing. We conducted a large-scale case study, including 24 human supervisors and 33 research students, in an Engineering Research Method course at The University of Sydney and compared questions generated by G-Asks with human generated question. The results indicate that G-Asks can generate questions as useful as human supervisors (`useful' is one of five question quality measures) while significantly outperforming Human Peer and Generic Questions in most quality measures after filtering out questions with grammatical and semantic errors. Furthermore, we identified the most frequent question types, derived from the human supervisors' questions and discussed how the human supervisors generate such questions from the source text

A method for daily normalization in emotion recognition

A ffects carry important information in human communication and decision making, and their use in technology have grown in the past years. Particularly, emotions have a strong e ect on physiology, which can be assessed by biomedical signals. This signals have the advantage that can be recorded continuously, but also can become intrusive. The present work introduce an emotion recognition scheme based only in photoplethysmography, aimed to lower invasiveness. The feature extraction method was developed for a realistic real-time context. Furthermore, a feature normalization procedure was proposed to reduce the daily variability. For classi cation, two well-known models were compared. The proposed algorithms were tested on a public database, which consist of 8 emotions expressed continuously by a single subject along diff erent days. Recognition tasks were performed for several number of emotional categories and groupings. Preliminary results shows a promising performance with up to 3 emotion categories. Moreover, the recognition of arousal and emotional events was improved for larger emotion sets.Sociedad Argentina de Informática e Investigación Operativa (SADIO

A method for daily normalization in emotion recognition

A ffects carry important information in human communication and decision making, and their use in technology have grown in the past years. Particularly, emotions have a strong e ect on physiology, which can be assessed by biomedical signals. This signals have the advantage that can be recorded continuously, but also can become intrusive. The present work introduce an emotion recognition scheme based only in photoplethysmography, aimed to lower invasiveness. The feature extraction method was developed for a realistic real-time context. Furthermore, a feature normalization procedure was proposed to reduce the daily variability. For classi cation, two well-known models were compared. The proposed algorithms were tested on a public database, which consist of 8 emotions expressed continuously by a single subject along diff erent days. Recognition tasks were performed for several number of emotional categories and groupings. Preliminary results shows a promising performance with up to 3 emotion categories. Moreover, the recognition of arousal and emotional events was improved for larger emotion sets.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Designing for Motivation, Engagement and Wellbeing in Digital Experience.

Research in psychology has shown that both motivation and wellbeing are contingent on the satisfaction of certain psychological needs. Yet, despite a long-standing pursuit in human-computer interaction (HCI) for design strategies that foster sustained engagement, behavior change and wellbeing, the basic psychological needs shown to mediate these outcomes are rarely taken into account. This is possibly due to the lack of a clear model to explain these needs in the context of HCI. Herein we introduce such a model: Motivation, Engagement and Thriving in User Experience (METUX). The model provides a framework grounded in psychological research that can allow HCI researchers and practitioners to form actionable insights with respect to how technology designs support or undermine basic psychological needs, thereby increasing motivation and engagement, and ultimately, improving user wellbeing. We propose that in order to address wellbeing, psychological needs must be considered within five different spheres of analysis including: at the point of technology adoption, during interaction with the interface, as a result of engagement with technology-specific tasks, as part of the technology-supported behavior, and as part of an individual's life overall. These five spheres of experience sit within a sixth, society, which encompasses both direct and collateral effects of technology use as well as non-user experiences. We build this model based on existing evidence for basic psychological need satisfaction, including evidence within the context of the workplace, computer games, and health. We extend and hone these ideas to provide practical advice for designers along with real world examples of how to apply the model to design practice

Public Health and Risk Communication During COVID-19—Enhancing Psychological Needs to Promote Sustainable Behavior Change

Background: The current COVID-19 pandemic requires sustainable behavior change to mitigate the impact of the virus. A phenomenon which has arisen in parallel with this pandemic is an infodemic—an over-abundance of information, of which some is accurate and some is not, making it hard for people to find trustworthy and reliable guidance to make informed decisions. This infodemic has also been found to create distress and increase risks for mental health disorders, such as depression and anxiety. Aim: To propose practical guidelines for public health and risk communication that will enhance current recommendations and will cut through the infodemic, supporting accessible, reliable, actionable, and inclusive communication. The guidelines aim to support basic human psychological needs of autonomy, competence, and relatedness to support well-being and sustainable behavior change. Method: We applied the Self-Determination Theory (SDT) and concepts from psychology, philosophy and human computer interaction to better understand human behaviors and motivations and propose practical guidelines for public health communication focusing on well-being and sustainable behavior change. We then systematically searched the literature for research on health communication strategies during COVID-19 to discuss our proposed guidelines in light of the emerging literature. We illustrate the guidelines in a communication case study: wearing face-coverings. Findings: We propose five practical guidelines for public health and risk communication that will cut through the infodemic and support well-being and sustainable behavior change: (1) create an autonomy-supportive health care climate; (2) provide choice; (3) apply a bottom-up approach to communication; (4) create solidarity; (5) be transparent and acknowledge uncertainty. Conclusion: Health communication that starts by fostering well-being and basic human psychological needs has the potential to cut through the infodemic and promote effective and sustainable behavior change during such pandemics. Our guidelines provide a starting point for developing a concrete public health communication strategy

Automatic classification of new articles in Spanish

We apply machine learning techniques to the automatic classification of news articles from the local newspaper La Capital of Rosario, Argentina. The corpus (LCC) is an archive of approximately 75,000 manually categorized articles in Spanish published in 1991. We benchmark on LCC three widely used supervised learning methods: k-Nearest Neighbors, Na¨ ve Bayes and Arti ficial Neural Networks, illustrating the corpus properties.Eje: V - Workshop de agentes y sistemas inteligentesRed de Universidades con Carreras en Informátic

Automatic classification of new articles in Spanish

We apply machine learning techniques to the automatic classification of news articles from the local newspaper La Capital of Rosario, Argentina. The corpus (LCC) is an archive of approximately 75,000 manually categorized articles in Spanish published in 1991. We benchmark on LCC three widely used supervised learning methods: k-Nearest Neighbors, Na¨ ve Bayes and Arti ficial Neural Networks, illustrating the corpus properties.Eje: V - Workshop de agentes y sistemas inteligentesRed de Universidades con Carreras en Informátic

Gaining deep knowledge of Android malware families through dimensionality reduction techniques

[Abstract] This research proposes the analysis and subsequent characterisation of Android malware families by means of low dimensional visualisations using dimensional reduction techniques. The well-known Malgenome data set, coming from the Android Malware Genome Project, has been thoroughly analysed through the following six dimensionality reduction techniques: Principal Component Analysis, Maximum Likelihood Hebbian Learning, Cooperative Maximum Likelihood Hebbian Learning, Curvilinear Component Analysis, Isomap and Self Organizing Map. Results obtained enable a clear visual analysis of the structure of this high-dimensionality data set, letting us gain deep knowledge about the nature of such Android malware families. Interesting conclusions are obtained from the real-life data set under analysis

Provenance of quartz grains from soils over Quaternary terraces along the Guadalquivir River, Spain

This work was supported by a grant from the Ministerio de Economía, Industria y Competitividad de España (“Mediterranean Soil Typologies versus Quartz. At the frontier of pedogenic knowledge”; Ref. CGL2016-80308-P). Alberto Molinero-García acknowledges the PhD funding (BES-2017-080078) provided by MCIN/AEI /10.13039/501100011033 and FSE “El FSE invierte en tu futuro”. This work is part of the Doctoral Dissertation of Alberto Molinero-García. We thank Dr. Mathieu Duval and an anonymous reviewer for their constructive criticism of the script and their valuable suggestions. We also acknowledge Tanya Shew for English proofreading. Funding for open access charge: Universidad de Granada / CBUA.The characterisation of quartz grains’ chemical and mineralogical properties in sediments and sedimentary rocks is widely used in provenance studies. This paper analyses quartz grains from the coarse sand fraction in soils in Quaternary fluvial terraces (Guadalquivir River, southern Spain). The tentative soil ages are 0.3 ka (Haplic Fluvisol), 7 ka (Haplic Calcisol), 70 ka (Cutanic Luvisol), 300 ka (Lixic Calcisol) and 600 ka (Cutanic Luvisol). The quartz grains analyses shed light on the sedimentological history of these terraces. Scanning electron microscope cathodoluminescence (SEM-CL) characteristics, micro inclusion inventory established by Energy-dispersive X-ray spectroscopy (SEM-EDX) and trace element contents determined with laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) of quartz grains permitted distinguishing six types of grains in the soils studied: metamorphic quartz (type 1), undeformed granitic quartz (type 2), strongly altered granitic quartz (type 3), recrystallised (deformed) granitic quartz (type 4), sandstone-derived quartz (type 5) and hydrothermal quartz grains (type 6). Metamorphic quartz grains (type 1) come from the Sierra Morena (Iberian Massif) and Sierra Nevada (Internal Betic Zone). Granitic quartz grains (types 2 to 4) come from Los Pedroches batholith and its associated plutons (Santa Elena and Linares). The sandstone-derived quartz type 5 comes from the numerous sandstone outcrops scattered in the central catchment area of the Guadalquivir River. Finally, hydrothermal quartz grains (type 6) originate from hydrothermal veins associated with subvolcanic rocks of the Los Pedroches batholith. Variations were noted in the proportions of quartz types in soils of different ages, attributed to spatial and temporal changes in the catchment area. The most remarkable change occurred between 500 and 240 ka ago when the catchment area extended into Sierra Nevadás metamorphic rocks, well reflected in type 1 content (lower in P2, P4, P5 and PM) and their characteristics (quartz with less healed fractures, less Al content, bigger mica microinclusions, smaller Al/Ti ratio) in the post-500–240 ka soils. Our study shows that the combined study of SEM-CL characteristics, micro inclusions (SEM-EDX), and trace element contents (LA-ICP-MS) of quartz grains is an efficient approach for characterising the provenance of quartz grains in the sand fraction of soils.CBUAMCINMediterranean Soil Typologies versus Quartz BES-2017-080078Faculty of Science and Engineering, University of ManchesterUniversidad de GranadaMinisterio de Economía, Industria y Competitividad, Gobierno de EspañaAgencia Estatal de Investigació