Psychometric Evaluation of the PSSUQ Using Data from Five Years of Usability Studies

Factor analysis of Post Study System Usability Questionnaire (PSSUQ) data from 5 years of usability studies (with a heavy emphasis on speech dictation systems) indicated a 3-factor structure consistent with that initially described 10 years ago: factors for System Usefulness, Information Quality, and Interface Quality. Estimated reliabilities (ranging from .83-.96) were also consistent with earlier estimates. Analyses of variance indicated that variables such as the study, developer, stage of development, type of product, and type of evaluation significantly affected PSSUQ scores. Other variables, such as gender and completeness of responses to the questionnaire, did not. Norms derived from this data correlated strongly with norms derived from the original PSSUQ data. The similarity of psychometric properties between the original and this PSSUQ data, despite the passage of time and differences in the types of systems studied, provide evidence of significant generalizability for the questionnaire, supporting its use by practitioners for measuring participant satisfaction with the usability of tested systems.     

The influence of conformity and group identity on drink walking intentions: Comparing intentions to drink walk across risky pedestrian crossing scenarios

Despite the dangers associated with drink walking, limited research is currently available regarding the factors which influence individuals to engage in this risky behaviour. This study examined the influence of psychosocial factors upon individuals’ intentions to drink walk across four experimental scenarios (and a control condition). Specifically, a 2 × 2 repeated measures design was utilised in which all of the scenarios incorporated a risky pedestrian crossing situation (i.e., a pedestrian crossing against a red man signal) but differed according to the level of group identity (i.e., low/strangers and high/friends) and conformity (low and high). Individuals were assessed for their intentions to drink walk within each of these different scenarios. Undergraduate students (N = 151), aged 17–30 years, completed a questionnaire. Overall, most of the study's hypotheses were supported with individuals reporting the highest intentions to drink walk when in the presence of friends (i.e., high group identity) and their friends were said to be also crossing against the red man signal (i.e., high conformity). The findings may have significant implications for the design of countermeasures to reduce drink walking. For instance, the current findings would suggest that potentially effective strategies may be to promote resilience to peer influence as well as highlight the negative consequences associated with following the behaviour of other intoxicated pedestrians who are crossing against a red signal.     

Estimating maize production in Kenya using NDVI: Some statistical considerations

A regression model approach using a normalized difference vegetation index (NDVI) has the potential for estimating crop production in East Africa. However, before production estimation can become a reality, the underlying model assumptions and statistical nature of the sample data (NDVI and crop production) must be examined rigorously. Annual maize production statistics from 1982-90 for 36 agricultural districts within Kenya were used as the dependent variable; median area NDVI (independent variable) values from each agricultural district and year were extracted from the annual maximum NDVI data set. The input data and the statistical association of NDVI with maize production for Kenya were tested systematically for the following items: (1) homogeneity of the data when pooling the sample, (2) gross data errors and influence points, (3) serial (time) correlation, (4) spatial autocorrelation and (5) stability of the regression coefficients. The results of using a simple regression model with NDVI as the only independent variable are encouraging (r 0.75, p 0.05) and illustrate that NDVI can be a responsive indicator of maize production, especially in areas of high NDVI spatial variability, which coincide with areas of production variability in Kenya.     

A 10 year installation program for wave energy in Ireland: A case study sensitivity analysis on financial returns

This paper is a case study which examines the finances of a proposed installation schedule of 500 MW of a wave energy device type in Ireland. The novel aspects of the analysis were the modelling of the combined influence of learning curves, supply and demand rates as well as future cost of cash on the phased deployment over the 10 years. There are many studies which have examined the economics of renewable energy project installations, including wave energy. However, there is lack of research in the impact and implications of phased installations over time, especially when using a feed-in tariff (FIT) revenue mechanism. The goal of the study was twofold. The first goal was to assess the viability of the current Irish feed-in tariff within the context of a phased installation program for the wave energy device chosen for the study, and measures required to produce a positive rate of return. The second aim was to assess the impact of learning curve, supply/demand curves and future cost of cash on phased project installations. The wave energy device chosen for the study was the Pelamis P1 and the economic model used was NAVITAS, created by HMRC. The assessment was based on net present value and internal rate of return. The wave energy data for the study was 2007 from M4 of the west coast of Ireland, obtained from Marine Institute, Ireland. Results from the case study indicated that the high initial costs for the case study wave energy device had a significant impact on financial returns. Results of the case study indicate that higher tariffs may be required than the current Irish, static, nonindex linked, FIT to foster positive returns for future wave energy projects, especially if phased installations are considered, which are susceptible to future cash and supply/demand factors. The large range of sensitivity factors assessed in the case study demonstrates the vulnerable nature of these large scale projects when estimating financial returns. Further studies will be required to assess multiple device types, update initial costs for wave energy devices, provide reliable power matrices, as well as appropriate learning curve and supply demand rates.     

Differential graphical games for H∞ control of linear heterogeneous multiagent systems

Differential graphical games have been introduced in the literature to solve state synchronization problem for linear homogeneous agents. When the agents are heterogeneous, the previous notion of graphical games cannot be used anymore and a new definition is required. In this paper, we define a novel concept of differential graphical games for linear heterogeneous agents subject to external unmodeled disturbances, which contain the previously introduced graphical game for homogeneous agents as a special case. Using our new formulation, we can solve both the output regulation and H_∞ output regulation problems. Our graphical game framework yields coupled Hamilton‐Jacobi‐Bellman equations, which are, in general, impossible to solve analytically. Therefore, we propose a new actor‐critic algorithm to solve these coupled equations numerically in real time. Moreover, we find an explicit upper bound for the overall ‐gain of the output synchronization error with respect to disturbance. We demonstrate our developments by a simulation example.     

Using conscious reflection,group processes,and AI to facilitate development of expertise

Three experiments investigated procedures derived from research on knowledge acquisition, group processes, and artificial intelligence for facilitating the development of expertise. In each experimental session, subjects learned to control a simulated sugar production factory. Then they formulated written policies for controlling sugar production either alone as individuals or in small groups. An adaptive AI system provided feedback on policy quality. The research also investigated the use of forced reflective practice in which learners attempted to predict what their policy would do while performing the task. The AI system provided feedback about what their policy would have done in each situation and the outcome based on their policy's response or their suggested alternative response. Results indicated that group interaction and feedback from the AI system improved policy quality. However, only when all three procedures were employed, group interaction, AI feedback, and forced reflective practice, was the development of individual expertise on the task enhanced.     

High-Temperature Decomposition of Fe- and Cr-Doped NiO Produced by a Novel Flame Spray Technique

A novel thick film technology has been developed for the manufacture of electric heating elements from partially oxidised Ni–Cr–Fe alloy powder. The sprayed films were a mixture of metallic alloys and Ni-based oxides. Electron microscopy and analysis were used to monitor the transformations in the films during subsequent heat treatment. In particular, it was found that homogeneous grains of Cr- and Fe-doped Ni-based oxides transformed into NiO grains containing numerous Ni-, Cr- and Fe-rich spinel particles with a typical size of 40 nm.     

Hierarchical visibility for guaranteed search in large-scale outdoor terrain

Searching for moving targets in large environments is a challenging task that is relevant in several problem domains, such as capturing an invader in a camp, guarding security facilities, and searching for victims in large-scale search and rescue scenarios. The guaranteed search problem is to coordinate the search of a team of agents to guarantee the discovery of all targets. In this paper we present a self-contained solution to this problem in 2.5D real-world domains represented by digital elevation models (DEMs). We introduce hierarchical sampling on DEMs for selecting heuristically the close to minimal set of locations from which the entire surface of the DEM can be guarded. Locations are utilized to form a search graph on which search strategies for mobile agents are computed. For these strategies schedules are derived which include agent paths that are directly executable in the terrain. Presented experimental results demonstrate the performance of the method. The practical feasibility of our approach has been validated during a field experiment at the Gascola robot training site where teams of humans equipped with iPads successfully searched for adversarial and omniscient evaders. The field demonstration is the largest-scale implementation of a guaranteed search algorithm to date.     

Investigation of the mechanisms governing doxorubicin and irinotecan release from drug-eluting beads: mathematical modeling and experimental verification

Drug-eluting beads (DEBs) are embolising devices in clinical use for the treatment of liver cancer by transarterial chemoembolisation. In this study, release kinetics of doxorubicin (DOX) and irinotecan (IRI) were investigated by experimental evaluations and mathematical modeling, based on Langmuir isotherm and two phenomenological models (Boyd/Bhaskar) developed to determine the actual mechanisms controlling drug release rate. The model was validated through release studies, in particular by assessing how drug loading, ionic strength of the release medium and device swelling during release influence drug release kinetics. Results demonstrated that IRI is released much faster than DOX, and that DEB volume strongly depends upon drug loading and fractional release. This effect was properly taken into account in developing the mathematical model. Experimental results were well fit by numerical simulations, and two different rate-controlling mechanisms were found to govern DOX and IRI delivery.     

Electrostatic dust collectors compared to inhalable samplers for measuring endotoxin concentrations in farm homes

Paired electrostatic dust collectors (EDCs) and daily, inhalable button samplers (BS) were used concurrently to sample endotoxin in 10 farm homes during 7‐day periods in summer and winter. Winter sampling included an optical particle counter (OPC) to measure PM_2.5 and PM_2.5–10. Electrostatic dust collectors and BS filters were analyzed for endotoxin using the kinetic chromogenic Limulus amebocyte lysate assay. Optical particle counter particulate matter (PM) data were divided into two PM categories. In summer, geometric mean (geometric standard deviation) endotoxin concentrations were 0.82 EU/m³ (2.7) measured with the BS and 737 EU/m² (1.9) measured with the EDC. Winter values were 0.52 EU/m³ (3.1) for BS and 538 EU/m² (3.0) for EDCs. Seven‐day endotoxin values of EDCs were highly correlated with the 7‐day BS sampling averages (r = 0.70; P < 0.001). Analysis of variance indicated a 2.4‐fold increase in EDC endotoxin concentrations for each unit increase of the ratio of PM_2.5 to PM_2.5–10. There was also a significant correlation between BS and EDCs endotoxin concentrations for winter (r = 0.67; P < 0.05) and summer (r = 0.75; P < 0.05). Thus, EDCs sample comparable endotoxin concentrations to BS, making EDCs a feasible, easy to use alternative to BS for endotoxin sampling.