Observing Inequality: Can Ergonomic Observations Help Interventions Transform the Role of Gender in Work Activity?

Computer Supported Cooperative Work (CSCW) - Work activity ergonomics (sometimes called francophone ergonomics) draws heavily on observation in order to support transformation of work to arrive at...     

HihO: accelerating artificial intelligence interpretability for medical imaging in IoT applications using hierarchical occlusion

Neural Computing and Applications - In the medical imaging domain, nonlinear warping has enabled pixel-by-pixel mapping of one image dataset to a reference dataset. This co-registration of data...     

Testing usability and trainability of indirect touch interaction: perspective for the next generation of air traffic control systems

This study aims to determine whether indirect touch device can be used to interact with graphical objects displayed on another screen in an air traffic control (ATC) context. The introduction of such a device likely requires an adaptation of the sensory-motor system. The operator has to simultaneously perform movements on the horizontal plane while assessing them on the vertical plane. Thirty-six right-handed participants performed movement training with either constant or variable practice and with or without visual feedback of the displacement of their actions. Participants then performed a test phase without visual feedback. Performance improved in both practice conditions, but accuracy was higher with visual feedback. During the test phase, movement time was longer for those who had practiced with feedback, suggesting an element of dependency. However, this ‘cost’ of feedback did not extend to movement accuracy. Finally, participants who had received variable training performed better in the test phase, but accuracy was still unsatisfactory. We conclude that continuous visual feedback on the stylus position is necessary if tablets are to be introduced in ATC.     

Robust control of variable speed autonomous underwater vehicle

Set point tracking control of autonomous underwater vehicle (AUV) via robust model predictive control (RMPC) is considered. Input-constrained RMPC with integral action, which has been developed in our previous work, is used to control the AUV in this study. In order to derive a RMPC control rule, non-linear dynamics of AUV with six degree of freedom is linearized at certain operating points. So, horizontal and vertical plane dynamics of system are represented by linear models which have polytopic uncertainties. Since the derived control rule will be used in real time, the computation time should be reduced. To overcome this computational time problem and get rid of trial–error step of Algorithm 1, a new algorithm is proposed here. The simulations are carried out using the control rule based on this algorithm and these results are presented.     

Verifying anonymity in voting systems using CSP

We present formal definitions of anonymity properties for voting protocols using the process algebra CSP. We analyse a number of anonymity definitions, and give formal definitions for strong and weak anonymity, highlighting the difference between these definitions. We show that the strong anonymity definition is too strong for practical purposes; the weak anonymity definition, however, turns out to be ideal for analysing voting systems. Two case studies are presented to demonstrate the usefulness of the formal definitions: a conventional voting system, and Prêt à Voter, a paper-based, voter-verifiable scheme. In each case, we give a CSP model of the system, and analyse it against our anonymity definitions by specification checks using the Failures-Divergences Refinement (FDR2) model checker. We give a detailed discussion on the results from the analysis, emphasizing the assumptions that we made in our model as well as the challenges in modelling electronic voting systems using CSP.     

Efficient Binary Tomographic Reconstruction

Tomographic reconstruction of a binary image from few projections is considered. A novel heuristic algorithm is proposed, the central element of which is a nonlinear transformation ψ(p)=log(p/(1?p)) of the probability p that a pixel of the sought image be 1-valued. It consists of backprojections based on ψ(p) and iterative corrections. Application of this algorithm to a series of artificial test cases leads to exact binary reconstructions, (i.e., recovery of the binary image for each single pixel) from the knowledge of projection data over a few directions. Images up to 10⁶ pixels are reconstructed in a few seconds. A series of test cases is performed for comparison with previous methods, showing a better efficiency and reduced computation times.     

Characterization of Maximum Likelihood Solutions to Image Reconstruction in Photon Emission Tomography

For photon emission tomography, the maximum likelihood (ML) estimator for image reconstruction is generally solution to a nonlinear equation involving the vector of measured data. No explicit closed-form solution is known in general for such a nonlinear ML equation, and numerical resolution is usually implemented, with a very popular iterative method formed by the expectation-maximization algorithm. The numerical character of such resolutions usually makes it difficult to obtain a general characterization of the performance of the ML solution. We show that the nonlinear ML equation can be replaced by an equivalent system of two dual linear equations nonlinearly coupled. This formulation allows us to exhibit explicit (to some extent) forms for the solutions to the ML equation, in general conditions corresponding to the various possible configurations of the imaging system, and to characterize their performance with expressions for the mean-squared error, bias and Cramér-Rao bound. The approach especially applies to characterize the ML solutions obtained numerically, and offers a theoretical framework to contribute to better appreciation of the capabilities of ML reconstruction in photon emission tomography.     

Prediction of suspended sediment concentration from water quality variables

This study investigates use of water quality (WQ) variables, namely total chromium concentration, total iron concentration, and turbidity for predicting suspended sediment concentration (SSC). For this purpose, the artificial neural networks (ANNs) and regression analysis (RA) models are employed. Seven different RA models are constructed, considering the functional relation between measured WQ variables and SSC. The WQ and SSC data are fortnightly obtained from six monitoring stations, located on the stream Harsit, Eastern Black Sea Basin, Turkey. A total of 132 water samples are collected from April 2009 to February 2010. Model prediction results reveal that ANN is able to predict SSC from WQ data, with mean absolute error (MAE) of 10.30 mg/L and root mean square error (RMSE) of 13.06 mg/L. Among seven RA models, the best one, which has the form including all independent parameters, produces results comparable to those of ANN, with MAE = 14.28 mg/L and RMSE = 15.35 mg/L. The sensitivity analysis results reveal that the most effective parameter on the SSC is total chromium concentration. These results have time- and cost-saving implications.     

A web-based platform for biosignal visualization and annotation

With the advent of wearable sensing and mobile technologies, biosignals have seen an increasingly growing number of application areas, leading to the collection of large volumes of data. One of the difficulties in dealing with these data sets, and in the development of automated machine learning systems which use them as input, is the lack of reliable ground truth information. In this paper we present a new web-based platform for visualization, retrieval and annotation of biosignals by non-technical users, aimed at improving the process of ground truth collection for biomedical applications. Moreover, a novel extendable and scalable data representation model and persistency framework is presented. The results of the experimental evaluation with possible users has further confirmed the potential of the presented framework.     

Kinetics of non-congruent dissolution of E-glass fiber in saturated calcium hydroxide solution

The kinetics of non-congruent dissolution of long E-glass fiber in saturated calcium hydroxide solution has been investigated at 25°C in a closed reactor adopting the rotating disc method for the sample holder. The fiber dissolution rate (), measured from the relative loss weight of the fiber after selective dissolution of the attack layer in acetic acid, is a linear function of time, what implies an interfacial dissolution process. However, the kinetics does not stay regular for a long time due to local detachment of the attack layer. The comparison between = f (t) and ′ = f (t) curves, where ′ is the formation rate of the attack layer, shows that the formation of the layer does not only imply the deposit of a bad-crystalline hydrated calcium silicate but the nucleation and growth of solid calcium hydroxide and calcium carbonate resulting from the transfert, to the interface, of ions coming from the liquid phase. This phenomenon was precedently observed by some other authors in the case of glass-fiber reinforced cement matrix.