Chatbot-Based Natural Language Interfaces for Data Visualisation: A Scoping Review

Rapid growth in the generation of data from various sources has made data visualisation a valuable tool for analysing data. However, visual analysis can be a challenging task, not only due to intricate dashboards but also when dealing with complex and multidimensional data. In this context, advances in Natural Language Processing technologies have led to the development of Visualisation-oriented Natural Language Interfaces (V-NLIs). In this paper, we carry out a scoping review that analyses synergies between the fields of Data Visualisation and Natural Language Interaction. Specifically, we focus on chatbot-based V-NLI approaches and explore and discuss three research questions. The first two research questions focus on studying how chatbot-based V-NLIs contribute to interactions with the Data and Visual Spaces of the visualisation pipeline, while the third seeks to know how chatbot-based V-NLIs enhance users' interaction with visualisations. Our findings show that the works in the literature put a strong focus on exploring tabular data with basic visualisations, with visual mapping primarily reliant on fixed layouts. Moreover, V-NLIs provide users with restricted guidance strategies, and few of them support high-level and follow-up queries. We identify challenges and possible research opportunities for the V-NLI community such as supporting high-level queries with complex data, integrating V-NLIs with more advanced systems such as Augmented Reality (AR) or Virtual Reality (VR), particularly for advanced visualisations, expanding guidance strategies beyond current limitations, adopting intelligent visual mapping techniques, and incorporating more sophisticated interaction methods

Fifth Conference on Artificial Intelligence for Space Applications

The Fifth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: automation for Space Station; intelligent control, testing, and fault diagnosis; robotics and vision; planning and scheduling; simulation, modeling, and tutoring; development tools and automatic programming; knowledge representation and acquisition; and knowledge base/data base integration

Non-Contact Sleep Monitoring

"The road ahead for preventive medicine seems clear. It is the delivery of high quality, personalised (as opposed to depersonalised) comprehensive medical care to all." Burney, Steiger, and Georges (1964) This world's population is ageing, and this is set to intensify over the next forty years. This demographic shift will result in signicant economic and societal burdens (partic- ularly on healthcare systems). The instantiation of a proactive, preventative approach to delivering healthcare is long recognised, yet is still proving challenging. Recent work has focussed on enabling older adults to age in place in their own homes. This may be realised through the recent technological advancements of aordable healthcare sen- sors and systems which continuously support independent living, particularly through longitudinally monitoring deviations in behavioural and health metrics. Overall health status is contingent on multiple factors including, but not limited to, physical health, mental health, and social and emotional wellbeing; sleep is implicitly linked to each of these factors. This thesis focusses on the investigation and development of an unobtrusive sleep mon- itoring system, particularly suited towards long-term placement in the homes of older adults. The Under Mattress Bed Sensor (UMBS) is an unobstrusive, pressure sensing grid designed to infer bed times and bed exits, and also for the detection of development of bedsores. This work extends the capacity of this sensor. Specically, the novel contri- butions contained within this thesis focus on an in-depth review of the state-of-the-art advances in sleep monitoring, and the development and validation of algorithms which extract and quantify UMBS-derived sleep metrics. Preliminary experimental and community deployments investigated the suitability of the sensor for long-term monitoring. Rigorous experimental development rened algorithms which extract respiration rate as well as motion metrics which outperform traditional forms of ambulatory sleep monitoring. Spatial, temporal, statistical and spatiotemporal features were derived from UMBS data as a means of describing movement during sleep. These features were compared across experimental, domestic and clinical data sets, and across multiple sleeping episodes. Lastly, the optimal classier (built using a combina- tion of the UMBS-derived features) was shown to infer sleep/wake state accurately and reliably across both younger and older cohorts. Through long-term deployment, it is envisaged that the UMBS-derived features (in- cluding spatial, temporal, statistical and spatiotemporal features, respiration rate, and sleep/wake state) may be used to provide unobtrusive, continuous insights into over- all health status, the progression of the symptoms of chronic conditions, and allow the objective measurement of daily (sleep/wake) patterns and routines

Enabling Context-Awareness in Mobile Systems via Multi-Modal Sensing

<p>The inclusion of rich sensors on modern smartphones has changed mobile phones from simple communication devices to powerful human-centric sensing platforms. Similar trends are influencing other personal gadgets such as the tablets, cameras, and wearable devices like the Google glass. Together, these sensors can provide</p><p>a high-resolution view of the user's context, ranging from simple information like locations and activities, to high-level inferences about the users' intention, behavior, and social interactions. Understanding such context can help solving existing system-side</p><p>challenges and eventually enable a new world of real-life applications. </p><p>In this thesis, we propose to learn human behavior via multi-modal sensing. The intuition is that human behaviors leave footprints on different sensing dimensions - visual, acoustic, motion and in cyber space. By collaboratively analyzing these footprints, the system can obtain valuable insights about the user. We show that the</p><p>analysis results can lead to a series of applications including capturing life-logging videos, tagging user-generated photos and enabling new ways for human-object interactions. Moreover, the same intuition may potentially be applied to enhance existing</p><p>system-side functionalities - offloading, prefetching and compression.</p>Dissertatio

Modélisation d'une interaction système-résident contextuelle, personnalisée et adaptative pour l'assistance cognitive à la réalisation des activités de la vie quotidienne dans les maisons connectées

Alors que le nombre de personnes vivant avec des déficits cognitifs qui découlent d’un traumatisme craniocérébral (TCC) va en croissant, les technologies d’assistance sont de plus en plus développées pour résoudre les problèmes qu’ils induisent dans la réalisation des activités de la vie quotidienne. L’Internet des objets et l’intelligence ambiante offrent un cadre pour fournir des services d’assistance sensibles au contexte, adaptatifs, autonomes et personnalisés pour ces personnes ayant des besoins particuliers. Une revue de la littérature sur le sujet permet de constater que les systèmes existants offrent très souvent une assistance excessive, quand l’aide contient plus d’information que nécessaire ou quand elle est fournie automatiquement à chaque étape de l’activité. Cette assistance, inadaptée aux besoins et aux capacités de la personne, est contraire à certains principes de la réadaptation cognitive qui prônent la fourniture d’une assistance minimale pour encourager la personne à agir au meilleur de ses capacités. Cette thèse propose des modèles pour automatiser l’assistance cognitive sous forme de dialogue contextuel entre une personne ayant des déficits cognitifs dus au TCC et un système lui fournissant l’assistance appropriée qui l’encourage à réaliser ses activités par lui-même. Les principales contributions sont : (1) un modèle ontologique comme support de l’assistance cognitive dans les maisons connectées ; (2) un modèle d’interaction entre l’agent intelligent d’une maison connectée et une personne ayant subi un TCC, dans le cadre de l’assistance cognitive. Le modèle ontologique proposé s’appuie sur les actes de langages et les données probantes de la réadaptation cognitive afin que l’assistance reflète la pratique clinique. Il vise à fournir aux maisons intelligentes la sémantique des données nécessaires pour caractériser les situations où il y a besoin d’assistance, les messages d’assistance de gradations différentes et les réactions de la personne. Informé par le modèle ontologique, le modèle d’interaction basé sur des arbres de comportement (« behaviour trees ») permet alors à un agent intelligent de planifier dynamiquement la diffusion de messages d’assistance progressifs avec des ajustements si nécessaire, en fonction du profil et du comportement du résident de la maison connectée lors de l’accomplissement de ses activités. Une validation préliminaire montre l’applicabilité des modèles dans l’implémentation de scénarios relatifs à l’utilisation sécuritaire d’une cuisinière connectée dédiée aux personnes ayant subi un TCC

Metafore mobilnih komunikacija ; Метафоры мобильной связи.

Mobilne komunikacije su polje informacione i komunikacione tehnologije koje karakteriše brzi razvoj i u kome se istraživanjem u analitičkim okvirima kognitivne lingvistike, zasnovanom na uzorku od 1005 odrednica, otkriva izrazito prisustvo metafore, metonimije, analogije i pojmovnog objedinjavanja. Analiza uzorka reči i izraza iz oblasti mobilnih medija, mobilnih operativnih sistema, dizajna korisničkih interfejsa, terminologije mobilnih mreža, kao i slenga i tekstizama koje upotrebljavaju korisnici mobilnih naprava ukazuje da pomenuti kognitivni mehanizmi imaju ključnu ulogu u olakšavanju interakcije između ljudi i širokog spektra mobilnih uređaja sa računarskim sposobnostima, od prenosivih računara i ličnih digitalnih asistenata (PDA), do mobilnih telefona, tableta i sprava koje se nose na telu. Ti mehanizmi predstavljaju temelj razumevanja i nalaze se u osnovi principa funkcionisanja grafičkih korisničkih interfejsa i direktne manipulacije u računarskim okruženjima. Takođe je analiziran i poseban uzorak od 660 emotikona i emođija koji pokazuju potencijal za proširenje značenja, imajući u vidu značaj piktograma za tekstualnu komunikaciju u vidu SMS poruka i razmenu tekstualnih sadržaja na društvenim mrežama kojima se redovno pristupa putem mobilnih uređaja...Mobile communications are a fast-developing field of information and communication technology whose exploration within the analytical framework of cognitive linguistics, based on a sample of 1005 entries, reveals the pervasive presence of metaphor, metonymy analogy and conceptual integration. The analysis of the sample consisting of words and phrases related to mobile media, mobile operating systems and interface design, the terminology of mobile networking, as well as the slang and textisms employed by mobile gadget users shows that the above cognitive mechanisms play a key role in facilitating interaction between people and a wide range of mobile computing devices from laptops and PDAs to mobile phones, tablets and wearables. They are the cornerstones of comprehension that are behind the principles of functioning of graphical user interfaces and direct manipulation in computing environments. A separate sample, featuring a selection of 660 emoticons and emoji, exhibiting the potential for semantic expansion was also analyzed, in view of the significance of pictograms for text-based communication in the form of text messages or exchanges on social media sites regularly accessed via mobile devices..

Integrating Human Performance Models into Early Design Stages to Support Accessibility

Humans have heterogeneous physical and cognitive capabilities. Engineers must cater to this heterogeneity to minimize opportunities for user error and system failure. Human factors considerations are typically evaluated late in the design process, risking expensive redesign when new human concerns become apparent. Evaluating user capability earlier could mitigate this risk. One critical early-stage design decision is function allocation – assigning system functions to humans and machines. Automating functions can eliminate the need for users to perform risky tasks but increases resource requirements. Engineers require guidance to evaluate and optimize function allocation that acknowledges the trade-offs between user accommodation and system complexity. In this dissertation, a multi-stage design methodology is proposed to facilitate the efficient allocation of system functions to humans and machines in heterogeneous user populations. The first stage of the methodology introduces a process to model population user groups to guide product customization. User characteristics that drive performance of generalized product interaction tasks are identified and corresponding variables from a national population database are clustered. In stage two, expert elicitation is proposed as a cost-effective means to quantify risk of user error for the user group models. Probabilistic estimates of user group performance are elicited from internal medicine physicians for generalized product interaction tasks. In the final stage, the data (user groups, performance estimations) are integrated into a multi-objective optimization model to allocate functions in a product family when considering user accommodation and system complexity. The methodology was demonstrated on a design case study involving self-management technology use by diabetes patients, a heterogeneous population in a safety-critical domain. The population modeling approach produced quantitatively and qualitatively validated clusters. For the expert elicitation, experts provided internally validated, distinct estimates for each user group-task pair. To validate the utility of the proposed method (acquired data, optimization model), engineering students (n=16) performed the function allocation task manually. Results indicated that participants were unable to allocate functions as efficiently as the model despite indicating user capability and cost were priorities. This research demonstrated that the proposed methodology can provide engineers valuable information regarding user capability and system functionality to drive accessible early-stage design decisions

Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space 1994

The Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS 94), held October 18-20, 1994, in Pasadena, California, was jointly sponsored by NASA, ESA, and Japan's National Space Development Agency, and was hosted by the Jet Propulsion Laboratory (JPL) of the California Institute of Technology. i-SAIRAS 94 featured presentations covering a variety of technical and programmatic topics, ranging from underlying basic technology to specific applications of artificial intelligence and robotics to space missions. i-SAIRAS 94 featured a special workshop on planning and scheduling and provided scientists, engineers, and managers with the opportunity to exchange theoretical ideas, practical results, and program plans in such areas as space mission control, space vehicle processing, data analysis, autonomous spacecraft, space robots and rovers, satellite servicing, and intelligent instruments

Electronic Literature as Digital Humanities

This book is available as open access through the Bloomsbury Open programme and is available on www.bloomsburycollections.com. Electronic Literature as Digital Humanities: Contexts, Forms & Practices is a volume of essays that provides a detailed account of born-digital literature by artists and scholars who have contributed to its birth and evolution. Rather than offering a prescriptive definition of electronic literature, this book takes an ontological approach through descriptive exploration, treating electronic literature from the perspective of the digital humanities (DH)––that is, as an area of scholarship and practice that exists at the juncture between the literary and the algorithmic. The domain of DH is typically segmented into the two seemingly disparate strands of criticism and building, with scholars either studying the synthesis between cultural expression and screens or the use of technology to make artifacts in themselves. This book regards electronic literature as fundamentally DH in that it synthesizes these two constituents. Electronic Literature as Digital Humanities provides a context for the development of the field, informed by the forms and practices that have emerged throughout the DH moment, and finally, offers resources for others interested in learning more about electronic literature