How do you say ‘hello’? Personality impressions from brief novel voices

On hearing a novel voice, listeners readily form personality impressions of that speaker. Accurate or not, these impressions are known to affect subsequent interactions; yet the underlying psychological and acoustical bases remain poorly understood. Furthermore, hitherto studies have focussed on extended speech as opposed to analysing the instantaneous impressions we obtain from first experience. In this paper, through a mass online rating experiment, 320 participants rated 64 sub-second vocal utterances of the word ‘hello’ on one of 10 personality traits. We show that: (1) personality judgements of brief utterances from unfamiliar speakers are consistent across listeners; (2) a two-dimensional ‘social voice space’ with axes mapping Valence (Trust, Likeability) and Dominance, each driven by differing combinations of vocal acoustics, adequately summarises ratings in both male and female voices; and (3) a positive combination of Valence and Dominance results in increased perceived male vocal Attractiveness, whereas perceived female vocal Attractiveness is largely controlled by increasing Valence. Results are discussed in relation to the rapid evaluation of personality and, in turn, the intent of others, as being driven by survival mechanisms via approach or avoidance behaviours. These findings provide empirical bases for predicting personality impressions from acoustical analyses of short utterances and for generating desired personality impressions in artificial voices

An information security model based on trustworthiness for enhancing security in on-line collaborative learning

L'objectiu principal d'aquesta tesi és incorporar propietats i serveis de la seguretat en sistemes d'informació en l'aprenentatge col·laboratiu en línia, seguint un model funcional basat en la valoració i predicció de la confiança. Aquesta tesi estableix com a punt de partença el disseny d'una solució de seguretat innovadora, basada en una metodologia pròpia per a oferir als dissenyadors i gestors de l'e-learning les línies mestres per a incorporar mesures de seguretat en l'aprenentatge col·laboratiu en línia. Aquestes guies cobreixen tots els aspectes sobre el disseny i la gestió que s'han de considerar en els processos relatius a l'e-learning, entre altres l'anàlisi de seguretat, el disseny d'activitats d'aprenentatge, la detecció d'accions anòmales o el processament de dades sobre confiança. La temàtica d'aquesta tesi té una naturalesa multidisciplinària i, al seu torn, les diferents disciplines que la formen estan íntimament relacionades. Les principals disciplines de què es tracta en aquesta tesi són l'aprenentatge col·laboratiu en línia, la seguretat en sistemes d'informació, els entorns virtuals d'aprenentatge (EVA) i la valoració i predicció de la confiança. Tenint en compte aquest àmbit d'aplicació, el problema de garantir la seguretat en els processos d'aprenentatge col·laboratiu en línia es resol amb un model híbrid construït sobre la base de solucions funcionals i tecnològiques, concretament modelatge de la confiança i solucions tecnològiques per a la seguretat en sistemes d'informació.El principal objetivo de esta tesis es incorporar propiedades y servicios de la seguridad en sistemas de información en el aprendizaje colaborativo en línea, siguiendo un modelo funcional basado en la valoración y predicción de la confianza. Esta tesis establece como punto de partida el diseño de una solución de seguridad innovadora, basada en una metodología propia para ofrecer a los diseñadores y gestores del e-learning las líneas maestras para incorporar medidas de seguridad en el aprendizaje colaborativo en línea. Estas guías cubren todos los aspectos sobre el diseño y la gestión que hay que considerar en los procesos relativos al e-learning, entre otros el análisis de la seguridad, el diseño de actividades de aprendizaje, la detección de acciones anómalas o el procesamiento de datos sobre confianza. La temática de esta tesis tiene una naturaleza multidisciplinar y, a su vez, las diferentes disciplinas que la forman están íntimamente relacionadas. Las principales disciplinas tratadas en esta tesis son el aprendizaje colaborativo en línea, la seguridad en sistemas de información, los entornos virtuales de aprendizaje (EVA) y la valoración y predicción de la confianza. Teniendo en cuenta este ámbito de aplicación, el problema de garantizar la seguridad en los procesos de aprendizaje colaborativo en línea se resuelve con un modelo híbrido construido en base a soluciones funcionales y tecnológicas, concretamente modelado de la confianza y soluciones tecnológicas para la seguridad en sistemas de información.This thesis' main goal is to incorporate information security properties and services into online collaborative learning using a functional approach based on trustworthiness assessment and prediction. As a result, this thesis aims to design an innovative security solution, based on methodological approaches, to provide e-learning designers and managers with guidelines for incorporating security into online collaborative learning. These guidelines include all processes involved in e-learning design and management, such as security analysis, learning activity design, detection of anomalous actions, trustworthiness data processing, and so on. The subject of this research is multidisciplinary in nature, with the different disciplines comprising it being closely related. The most significant ones are online collaborative learning, information security, learning management systems (LMS), and trustworthiness assessment and prediction models. Against this backdrop, the problem of securing collaborative online learning activities is tackled by a hybrid model based on functional and technological solutions, namely, trustworthiness modelling and information security technologies

IoT trust and reputation: a survey and taxonomy

IoT is one of the fastest-growing technologies and it is estimated that more than a billion devices would be utilized across the globe by the end of 2030. To maximize the capability of these connected entities, trust and reputation among IoT entities is essential. Several trust management models have been proposed in the IoT environment; however, these schemes have not fully addressed the IoT devices features, such as devices role, device type and its dynamic behavior in a smart environment. As a result, traditional trust and reputation models are insufficient to tackle these characteristics and uncertainty risks while connecting nodes to the network. Whilst continuous study has been carried out and various articles suggest promising solutions in constrained environments, research on trust and reputation is still at its infancy. In this paper, we carry out a comprehensive literature review on state-of-the-art research on the trust and reputation of IoT devices and systems. Specifically, we first propose a new structure, namely a new taxonomy, to organize the trust and reputation models based on the ways trust is managed. The proposed taxonomy comprises of traditional trust management-based systems and artificial intelligence-based systems, and combine both the classes which encourage the existing schemes to adapt these emerging concepts. This collaboration between the conventional mathematical and the advanced ML models result in design schemes that are more robust and efficient. Then we drill down to compare and analyse the methods and applications of these systems based on community-accepted performance metrics, e.g. scalability, delay, cooperativeness and efficiency. Finally, built upon the findings of the analysis, we identify and discuss open research issues and challenges, and further speculate and point out future research directions.Comment: 20 pages, 5 Figures, 3 tables, Journal of cloud computin

IoT trust and reputation: a survey and taxonomy

IoT is one of the fastest-growing technologies and it is estimated that more than a billion devices would be utilized across the globe by the end of 2030. To maximize the capability of these connected entities, trust and reputation among IoT entities is essential. Several trust management models have been proposed in the IoT environment; however, these schemes have not fully addressed the IoT devices features, such as devices role, device type and its dynamic behavior in a smart environment. As a result, traditional trust and reputation models are insufficient to tackle these characteristics and uncertainty risks while connecting nodes to the network. Whilst continuous study has been carried out and various articles suggest promising solutions in constrained environments, research on trust and reputation is still at its infancy. In this paper, we carry out a comprehensive literature review on state-of-the-art research on the trust and reputation of IoT devices and systems. Specifically, we first propose a new structure, namely a new taxonomy, to organize the trust and reputation models based on the ways trust is managed. The proposed taxonomy comprises of traditional trust management-based systems and artificial intelligence-based systems, and combine both the classes which encourage the existing schemes to adapt these emerging concepts. This collaboration between the conventional mathematical and the advanced ML models result in design schemes that are more robust and efficient. Then we drill down to compare and analyse the methods and applications of these systems based on community-accepted performance metrics, e.g. scalability, delay, cooperativeness and efficiency. Finally, built upon the findings of the analysis, we identify and discuss open research issues and challenges, and further speculate and point out future research directions.Comment: 20 pages, 5 Figures, 3 tables, Journal of cloud computin

DevOps for Trustworthy Smart IoT Systems

ENACT is a research project funded by the European Commission under its H2020 program. The project consortium consists of twelve industry and research member organisations spread across the whole EU. The overall goal of the ENACT project was to provide a novel set of solutions to enable DevOps in the realm of trustworthy Smart IoT Systems. Smart IoT Systems (SIS) are complex systems involving not only sensors but also actuators with control loops distributed all across the IoT, Edge and Cloud infrastructure. Since smart IoT systems typically operate in a changing and often unpredictable environment, the ability of these systems to continuously evolve and adapt to their new environment is decisive to ensure and increase their trustworthiness, quality and user experience. DevOps has established itself as a software development life-cycle model that encourages developers to continuously bring new features to the system under operation without sacrificing quality. This book reports on the ENACT work to empower the development and operation as well as the continuous and agile evolution of SIS, which is necessary to adapt the system to changes in its environment, such as newly appearing trustworthiness threats

Considering Human Aspects on Strategies for Designing and Managing Distributed Human Computation

A human computation system can be viewed as a distributed system in which the processors are humans, called workers. Such systems harness the cognitive power of a group of workers connected to the Internet to execute relatively simple tasks, whose solutions, once grouped, solve a problem that systems equipped with only machines could not solve satisfactorily. Examples of such systems are Amazon Mechanical Turk and the Zooniverse platform. A human computation application comprises a group of tasks, each of them can be performed by one worker. Tasks might have dependencies among each other. In this study, we propose a theoretical framework to analyze such type of application from a distributed systems point of view. Our framework is established on three dimensions that represent different perspectives in which human computation applications can be approached: quality-of-service requirements, design and management strategies, and human aspects. By using this framework, we review human computation in the perspective of programmers seeking to improve the design of human computation applications and managers seeking to increase the effectiveness of human computation infrastructures in running such applications. In doing so, besides integrating and organizing what has been done in this direction, we also put into perspective the fact that the human aspects of the workers in such systems introduce new challenges in terms of, for example, task assignment, dependency management, and fault prevention and tolerance. We discuss how they are related to distributed systems and other areas of knowledge.Comment: 3 figures, 1 tabl

Trustworthiness of statistical inference

We examine the role of trustworthiness and trust in statistical inference, arguing that it is the extent of trustworthiness in inferential statistical tools which enables trust in the conclusions. Certain tools, such as the p‐value and significance test, have recently come under renewed criticism, with some arguing that they damage trust in statistics. We argue the contrary, beginning from the position that the central role of these methods is to form the basis for trusted conclusions in the face of uncertainty in the data, and noting that it is the misuse and misunderstanding of these tools which damages trustworthiness and hence trust. We go on to argue that recent calls to ban these tools would tackle the symptom, not the cause, and themselves risk damaging the capability of science to advance, as well as risking feeding into public suspicion of the discipline of statistics. The consequence could be aggravated mistrust of our discipline and of science more generally. In short, the very proposals could work in quite the contrary direction from that intended. We make some alternative proposals for tackling the misuse and misunderstanding of these methods, and for how trust in our discipline might be promoted

3R Evokes Ecodesign Identity in Ecological System of Green Manufacturing

For the past few decades to the era of industry 4.0, young practising designers have been enduring environmental communication challenges in the green manufacturing context. The problems stem from their failure to comprehend the pattern of environment communication phenomenally. The objective of this study is to address the environmentally-driven elements of recycling methodology along with the product’s form development via “re-think waste†of the environmental communications concept; screened by the bubbling model of intangible ecological form theory. In the realm of industrial design, it is implicitly visualised by the common Mobius loop cycle method of the green manufacturing paradigm. Under the Descriptive Study I of design research methodology framework, the goal-setting participation from Malaysian manufacturers sample using two methodologies concurrently; (1) the cluster sampling that measured the designs perception as the quantitative structure by statistic values and (2) the purposive sampling interpreted the design behaviors of the subject as the qualitative structure by first cycle coding. Consequently, the heuristic evaluation is used to triangulate the two methodologies. For the finding, an intangible ecological form model formulated the change for environmental communication to digitise and screen an intangible ecological form according to extrapolative strategy morphing