66 research outputs found
Exploring miscommunication and collaborative behaviour in human-robot interaction
This paper presents the first step in designing a speech-enabled robot that is capable of natural management of miscommunication. It describes the methods
and results of two WOz studies, in which
dyads of naĂŻve participants interacted in a
collaborative task. The first WOz study
explored human miscommunication
management. The second study investigated
how shared visual space and monitoring
shape the processes of feedback and communication in task-oriented interactions.
The results provide insights for the development of human-inspired and
robust natural language interfaces in robots
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A corpus-based analysis of route instructions in human-robot interaction
This paper investigates how users employ spatial descriptions to navigate a speech-enabled robot. We created a simulated environment in which users gave route instructions in a dialogic real-time interaction with a robot, which was
operated by naĂŻve participants. The ability of robot monitoring was also manipulated in two experimental conditions. The results provide evidence that the content of the instructions and strategies of the users vary depending on the conditions and
demands of the interaction. As expected, the route instructions frequently were underspecified and arbitrary. The findings of
this study elucidate the complexity in interpreting spatial language in HRI. However, they also point to the need for
endowing mobile robots with richer dialogue resources to compensate for the uncertainties arising from language as well
as the environment
A Systematic Review on the Detection of Fake News Articles
Currently submitted to ACM Transactions on Intelligent Systems and Technology. Awaiting peer-review.It has been argued that fake news and the spread of false information pose a threat to societies throughout the world, from influencing the results of elections to hindering the efforts to manage the COVID-19 pandemic. To combat this threat, a number of Natural Language Processing (NLP) approaches have been developed. These leverage a number of datasets, feature extraction/selection techniques and machine learning (ML) algorithms to detect fake news before it spreads. While these methods are well-documented, there is less evidence regarding their efficacy in this domain. By systematically reviewing the literature, this paper aims to delineate the approaches for fake news detection that are most performant, identify limitations with existing approaches, and suggest ways these can be mitigated. The analysis of the results indicates that Ensemble Methods using a combination of news content and socially-based features are currently the most effective. Finally, it is proposed that future research should focus on developing approaches that address generalisability issues (which, in part, arise from limitations with current datasets), explainability and bias
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The effect of organisational absorptive capacity on business intelligence systems efficiency and organisational efficiency
Purpose: Business intelligence (BI) systems (i.e. technology and procedures that transform raw data into useful information for managers to enable them to make better and faster decisions) have enormous potential to improve organisational efficiency. However, given the high expenditure involved in the deployment of these systems, the factors that will enable their successful integration should be thoroughly considered and assessed before these systems are adopted. Absorptive capacity (ACAP) is the ability of organisations to gather, absorb and strategically influence new external information, and as such, there is a strong theoretical connection between ACAP and BI systems. This research aims to empirically investigate the relationship between the dimensions underpinning ACAP (i.e. acquisition, assimilation, transformation and exploitation) and whether and how they affect the efficiency of BI systems, which, in turn, can enhance organisational efficiency. Design/methodology/approach: This study formulates five hypotheses addressing the effect of ACAP dimensions on BI systems efficiency and the effect of BI systems efficiency on organisational efficiency. It synthesises previous qualitative work and current research to derive sets of measures for each of the key constructs of the study. It follows a quantitative methodology, which involves the collection of survey data from senior managers in the telecommunications industry and the analysis of the data using partial least squares â structural equation modelling (PLS-SEM). Findings: The results of the analysis confirmed the validity of the constructs and proposed measures and supported all five hypotheses suggesting a strong positive relationship between the ACAP dimensions, acquisition, assimilation, transformation and exploitation and the efficiency of BI systems and a strong effect of BI systems efficiency on organisational efficiency. Practical implications: The study offers a comprehensive model of ACAP and BI systems efficiency. The set of measures that underpin these constructs could help researchers understand how ACAP dimensions are practically implemented and could contribute to their efforts to develop ACAP measurement instruments. At the same time, the model can help managers assess the readiness of their firms to adopt BI systems and identify which areas should be further developed, before committing to the substantial financial investment associated with BI systems. It also provides a set of practical solutions that could be implemented to enable a more robust ACAP and support a better integration of BI systems. Originality/value: Following an empirical approach, this study refines oneâs theoretical and practical understanding of ACAP as an organisational dynamic capability and its dimensions; it provides an account on how each dimension affects different aspects of BI systems efficiency, which, in turn, may contribute to the improvement of organisational efficiency. Moreover, the study reframes ACAP measures as a set of requirements that can be practically assessed and followed before attempting to purchase BI systems
Size-segregated mass distributions of aerosols over Eastern Mediterranean: seasonal variability and comparison with AERONET columnar size-distributions
International audienceThis work provides long-term (2004?2006) size segregated measurements of aerosol mass at a remote coastal station in the southern Europe, with the use of size-selective samplings (SDI impactor). Seven distinct modes were identified in the range 0?10 ”m and the dominant were the "Accumulation 1" (0.25?0.55 ”m) and the "Coarse 2" (3?7 ”m) modes. The seasonal characteristics of each mode were thoroughly studied and different sources for submicron and supermicron particles were identified, the first being related to local/regional and transported pollution with maximum in summer and the latter to dust from deserted areas in Northern Africa maximizing in spring. On average, PM2.5 and PM1 accounted for 60% and 40% of PM10 mass, respectively.The representativity of the ground-based measurements for the total column was also investigated by comparing the measured aerosol mass distributions with the AERONET volume size distribution data. Similar seasonal patterns were revealed and AERONET was found adequate for the estimation of background levels of both fine and coarse particles near surface, with certain limitations in the case of pollution or dust abrupt episodes due to its low temporal coverage
Do (and say) as I say: Linguistic adaptation in human-computer dialogs
© Theodora Koulouri, Stanislao Lauria, and Robert D. Macredie. This article has been made available through the Brunel Open Access Publishing Fund.There is strong research evidence showing that people naturally align to each otherâs vocabulary, sentence structure, and acoustic features in dialog, yet little is known about how the alignment mechanism operates in the interaction between users and computer systems let alone how it may be exploited to improve the efficiency of the interaction. This article provides an account of lexical alignment in humanâcomputer dialogs, based on empirical data collected in a simulated humanâcomputer interaction scenario. The results indicate that alignment is present, resulting in the gradual reduction and stabilization of the vocabulary-in-use, and that it is also reciprocal. Further, the results suggest that when system and user errors occur, the development of alignment is temporarily disrupted and users tend to introduce novel words to the dialog. The results also indicate that alignment in humanâcomputer interaction may have a strong strategic component and is used as a resource to compensate for less optimal (visually impoverished) interaction conditions. Moreover, lower alignment is associated with less successful interaction, as measured by user perceptions. The article distills the results of the study into design recommendations for humanâcomputer dialog systems and uses them to outline a model of dialog management that supports and exploits alignment through mechanisms for in-use adaptation of the systemâs grammar and lexicon
Toward Predicting Success and Failure in CS2: A Mixed-Method Analysis
Factors driving success and failure in CS1 are the subject of much study but
less so for CS2. This paper investigates the transition from CS1 to CS2 in
search of leading indicators of success in CS2. Both CS1 and CS2 at the
University of North Carolina Wilmington (UNCW) are taught in Python with annual
enrollments of 300 and 150 respectively. In this paper, we report on the
following research questions: 1) Are CS1 grades indicators of CS2 grades? 2)
Does a quantitative relationship exist between CS2 course grade and a modified
version of the SCS1 concept inventory? 3) What are the most challenging aspects
of CS2, and how well does CS1 prepare students for CS2 from the student's
perspective? We provide a quantitative analysis of 2300 CS1 and CS2 course
grades from 2013--2019. In Spring 2019, we administered a modified version of
the SCS1 concept inventory to 44 students in the first week of CS2. Further, 69
students completed an exit questionnaire at the conclusion of CS2 to gain
qualitative student feedback on their challenges in CS2 and on how well CS1
prepared them for CS2. We find that 56% of students' grades were lower in CS2
than CS1, 18% improved their grades, and 26% earned the same grade. Of the
changes, 62% were within one grade point. We find a statistically significant
correlation between the modified SCS1 score and CS2 grade points. Students
identify linked lists and class/object concepts among the most challenging.
Student feedback on CS2 challenges and the adequacy of their CS1 preparations
identify possible avenues for improving the CS1-CS2 transition.Comment: The definitive Version of Record was published in 2020 ACM Southeast
Conference (ACMSE 2020), April 2-4, 2020, Tampa, FL, USA. 8 page
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