Playing Pairs with Pepper

As robots become increasingly prevalent in almost all areas of society, the factors affecting humans trust in those robots becomes increasingly important. This paper is intended to investigate the factor of robot attributes, looking specifically at the relationship between anthropomorphism and human development of trust. To achieve this, an interaction game, Matching the Pairs, was designed and implemented on two robots of varying levels of anthropomorphism, Pepper and Husky. Participants completed both pre- and post-test questionnaires that were compared and analyzed predominantly with the use of quantitative methods, such as paired sample t-tests. Post-test analyses suggested a positive relationship between trust and anthropomorphism with $80\%$ of participants confirming that the robots' adoption of facial features assisted in establishing trust. The results also indicated a positive relationship between interaction and trust with $90\%$ of participants confirming this for both robots post-testComment: Presented at AI-HRI AAAI-FSS, 2018 (arXiv:1809.06606

Non-adherence to cardiovascular pharmacotherapy in Iraq assessed using 8-items Morisky questionnaire and analysis of dried blood spot samples

open access journalThe study evaluated the non-adherence to selected cardiovascular medications, atenolol, atorvastatin, bisoprolol, diltiazem, lisinopril, simvastatin and valsartan in Iraqi patients by applying a standardized Morisky questionnaire (8-MMAS) and by measuring therapeutic drug concentrations in dried blood spots (DBS) analyzed by liquid chromatography - high resolution mass spectrometry (LC-HRMS). Sixty-nine patients, on continued use of one or more of the selected drugs, were evaluated. The questionnaire showed that 21.7% of participants were non-adherent whereas DBS analysis showed that 49.3% were non-adherent to their medications. No significant correlation between medication non-adherence and gender was detected, but adherence was negatively correlated with the number of medications in the regimen. The 8-items questionnaire was unable to differentiate non-adherence to multiple medications in the prescribed pharmacotherapy regimens. DBS is an alternative to conventional methods to monitor non-adherence objectively. Agreement between the two approaches was weak (Kappa =0.269, p-value 0.05)

Underlying trends in employment-output equation: the case of Jordan

The underlying employment trend (UET) is investigated in Jordanian economy over the period 1989- 2004 using structural time series model (STSM). This approach allows to modelling the trend in its stochastic form introduced by Harvey (1989). The results show that a stochastic trend is preferred to deterministic trend. In addition, the inclusion or exclusion of the conventional deterministic trend leads to overestimated output elasticity. Furthermore, the UET is found to be non-linear, down downward sloping.Employment, stochastic trend, structural time series modelling, Research and Development/Tech Change/Emerging Technologies, J20,

Student-generated animations and the teaching and learning of chemistry

University of Technology Sydney. Faculty of Arts and Social Sciences.This study investigates the use of student-generated animations in the teaching and learning of chemistry. Previous research has identified the potential for animations to contribute to student learning in science. In particular, animations have the capacity to represent the dynamic processes and motions that may be inherent in some chemical concepts. This study focuses on animations that students produced with the support of their teacher and their fellow students. The literature review brings ideas together from social constructivism, representational pedagogy and analogical reasoning to highlight the implications of this research. The research investigated a teaching intervention that was designed to investigate the following conjecture: That students working in groups to create their own animations to represent their conceptions, when supported by their teacher to analyse the animations in group discussions, develop their understanding of science concepts. The participants in the study were 28 Year 11 Science students and their science teacher. The concept the students were learning was states of matter. The teaching intervention included training the students in the use of animation software, followed by the students working in pairs or groups of three to create animations representing their conceptions of solid, liquid and gaseous states of matter. Students were supported by their teacher and encouraged to discuss ideas as they constructed their animations. After completion of the animations, the teacher facilitated the students to analyse and discuss their own animations as well as animations that had been produced by experts. Data collection included pre- and post-tests, classroom observation, videorecording of lessons, collection of artefacts (the students’ animations) and interviews with the teacher and students. Use of the student-generated animations created an opportunity to represent and discuss conceptions of the states of matters, including dynamic elements of their conceptualisations. The teacher’s scaffolding of the groups during their animating, helped them to accurately represent their conceptions. The teacher became aware of her students’ misconceptions and otherwise hidden understandings as they created their animations. In their analysis of the various animations, students identified differences and similarities among their animations. As well, by comparing attributes of their conceptions of states of matter with attributes shown in their animations, they identified those that were matching and mismatching. They also critiqued expert animations of states of matter. Data from pre/post-tests, observations and interviews indicate that the students improved their understanding of states of matter through the teaching/learning process that occurred during the intervention

A hybrid technique using minimal spanning tree and analytic hierarchical process to improve functional requirements prioritization

Software for large enterprises such as the Enterprise Resource Planning (ERP) is more likely to be developed by a team of software developers where the functional requirements (FRs) are distributed in parallel developers. Therefore, development of pre-requisite FRs must be carefully timed to see which requirement is to be implemented first by assigning priority to some FRs over others, so that FRs can be made available on time to parallel developers. Well-known prioritization technique such as the Analytic Hierarchical Process (AHP), although accurate, is not scalable for large set of FRs as in ERP due to high number of pairwise comparisons when the size of FRs is more than ten or twelve. To address this issue, this research proposes a hybrid prioritization technique of Minimal Spanning Trees (MST) and AHP called the Spanning Analytic Hierarchical Process (SAHP) for FRs prioritization by exploiting MST capability to prioritize large size software FRs with smaller pairwise comparisons but with more consistent results. Using Numerical Assignment (NA) technique, prioritized FRs from SAHP are assigned to priority groups such that top priority groups contain high priority FRs and low priority groups contain low priority FRs. Low priority group of FRs are dependent on high priority groups. As a result, within each priority group, inter-dependencies in FRs are reduced for parallel developers. Implementing high priority groups will reduce number of dependencies in FRs among the lower priority groups. The proposed technique is evaluated based on ERP case study and the results showed that SAHP reduces estimation time of parallel developers as compared to AHP and other techniques. This shows that SAHP is scalable to cater large number of pairwise comparisons for large systems like ERP