Traditional Visual Approaches Research Articles

Enhanced Visualization and Interpretation of XMCD‐PEEM Data Using SOM‐RPM Machine Learning

AbstractPhotoemission electron microscopy (PEEM) is a powerful technique for surface characterization that provides detailed information on the chemical and structural properties of materials at the nanoscale. In this study, the potential is explored using a machine learning algorithm called self‐organizing map with a relational perspective map (SOM‐RPM) for visualizing and analyzing complex PEEM‐generated datasets. The application of SOM‐RPM is demonstrated using synchrotron‐based X‐ray magnetic circular dichroism (XMCD)‐PEEM data acquired from a pyrrhotite sample. Traditional visualization approaches for XMCD‐PEEM data may not fully capture the complexity of the sample, especially in the case of heterogeneous materials. By applying SOM‐RPM to the XMCD‐PEEM data, a colored topographic map is created that represents the spectral similarities and dissimilarities among the pixels. This approach allows for a more intuitive and easily interpretable representation of the data without the need of data binning or spectral smoothing. The results of the SOM‐RPM analysis are compared to the conventional visualization approach, highlighting the advantages of SOM‐RPM in revealing features that are not readily observable in the conventional method. This study suggests that the SOM‐RPM approach can be used complimentarily for other PEEM‐based measurements, such as core level and valence band X‐ray photoelectron spectroscopy.

Redirected walking in virtual reality with auditory step feedback

We present a novel approach of redirected walking (RDW) based on step feedback sounds to redirect users in virtual reality. The main idea is to achieve path manipulation by changing step noises to deviate the users, who still believe that they are walking a straight line. Our approach can be combined with traditional visual approaches for RDW based on eye-blinking. Moreover, we have conducted a user study in a large area (10times 20m) using a within-subject design. We achieved a translational redirection of 1.7m in average with pure audio feedback. Moreover, our results show that visual methods can amplify the deviation of our new auditory approach by 80cm in average at the distance of 20 m.

Secondary predation constrains DNA-based diet reconstruction in two threatened shark species

Increasing fishing effort, including bycatch and discard practices, are impacting marine biodiversity, particularly among slow-to-reproduce taxa such as elasmobranchs, and specifically sharks. While some fisheries involving sharks are sustainably managed, collateral mortalities continue, contributing towards > 35% of species being threatened with extinction. To effectively manage shark stocks, life-history information, including resource use and feeding ecologies is pivotal, especially among those species with wide-ranging distributions. Two cosmopolitan sharks bycaught off eastern Australia are the common blacktip shark (Carcharhinus limbatus; globally classified as Near Threatened) and great hammerhead (Sphyrna mokarran; Critically Endangered). We opportunistically sampled the digestive tracts of these two species (and also any whole prey; termed the ‘Russian-doll’ approach), caught in bather-protection gillnets off northern New South Wales, to investigate the capacity for DNA metabarcoding to simultaneously determine predator and prey regional feeding ecologies. While sample sizes were small, S. mokkaran fed predominantly on stingrays and skates (Myliobatiformes and Rajiformes), but also teleosts, while C. limbatus mostly consumed teleosts. Metabarcoding assays showed extensive intermixing of taxa from the digestive tracts of predators and their whole prey, likely via the predator’s stomach chyme, negating the opportunity to distinguish between primary and secondary predation. This Russian-doll effect requires further investigation in DNA metabarcoding studies focussing on dietary preferences and implies that any outcomes will need to be interpreted concomitant with traditional visual approaches.

DIRECT SPARSE VISUAL ODOMETRY WITH STRUCTURAL REGULARITIES FOR LONG CORRIDOR ENVIRONMENTS

Abstract. Simultaneous Localization and Mapping are the key requirements for many practical applications of robotics. However, traditional visual approaches rely on features extracted from textured surfaces, so they barely work well in indoor scenes (e.g. long corridors containing large proportions of smooth walls). In this work, we propose a novel visual odometry method to overcome these limitations, which integrates structural regularities of man-made environments in a direct sparse visual odometry system. By fully exploiting structural lines that align with the dominant direction in the Manhattan world, our approach becomes more accurate and robust to texture-less indoor environments, specially, long corridors. Given a series of image inputs, we first use the direct sparse method to obtain the coarse relative pose between camera frames, and then calculate vanishing points on each frame. Secondly, we use structural lines as rotation constraints, and perform a sliding window optimization to reduce both photometric and rotation errors, to further improve the trajectory accuracy. Through the benchmark test, it is proved that our method performs better than that of the existing visual odometry approach in long corridor environments.

Cost savings from a teledentistry model for school dental screening: an Australian health system perspective.

Objective The aim of the present study was to compare the costs of teledentistry and traditional dental screening approaches in Australian school children. Methods A cost-minimisation analysis was performed from the perspective of the oral health system, comparing the cost of dental screening in school children using a traditional visual examination approach with the cost of mid-level dental practitioners (MLDPs), such as dental therapists, screening the same cohort of children remotely using teledentistry. A model was developed to simulate the costs (over a 12-month period) of the two models of dental screening for all school children (2.7million children) aged 5-14 years across all Australian states and territories. The fixed costs and the variable costs, including staff salary, travel and accommodation costs, and cost of supply were calculated. All costs are given in Australian dollars. Results The total estimated cost of the teledentistry model was $50million. The fixed cost of teledentistry was $1million and that of staff salaries (tele-assistants, charters and their supervisors, as well as information technology support was estimated to be $49million. The estimated staff salary saved with the teledentistry model was $56million, and the estimated travel allowance and supply expenses avoided were $16million and $14million respectively; an annual reduction of $85million in total. Conclusions The present study shows that the teledentistry model of dental screening can minimise costs. The estimated savings were due primarily to the low salaries of dental therapists and the avoidance of travel and accommodation costs. Such savings could be redistributed to improve infrastructure and oral health services in rural or other underserved areas. What is known about the topic? Caries is a preventable disease, which, if it remains untreated, can cause significant morbidity requiring costly treatment. Regular dental screening and oral health education have the great potential to improve oral health and save significant resources. The use of role substitution, such as using MLDPs to provide oral care has been well acknowledged worldwide because of their ability to provide safe and effective care. The teledentistry approach for dental screening offers a comparable diagnostic performance to the traditional visual approach. What does this paper add? The results of the present study suggest that teledentistry is a practical and economically viable approach for mass dental screening not only for isolated communities, but also for underserved urban communities. The costs of the teledentistry model were substantially lower than the costs associated with a conventional, face-to-face approach to dental screening in both remote and urban areas. The primary driver of net savings is the low salary of MLDPs and avoidance of travel and overnight accommodation by MLDPs. What are the implications for practitioners? The use of lower-cost MLDPs and a teledentistry model for dental screening has the potential to save significant economic and human resources that can be redirected to improve infrastructure and oral care services in underserved regions. In the absence of evidence of the economic usefulness of teledentistry, studies such as the present one can increase the acceptance of this technology among dental care providers and guide future decisions on whether or not to implement teledentistry services.

Evaluation of a Novel Computer Color Matching System Based on the Improved Back-Propagation Neural Network Model.

To explore the feasibility of a novel computer color-matching (CCM) system based on the improved back-propagation neural network (BPNN) model by comparing it with the traditional visual method. Forty-three metal-ceramic specimens were fabricated by proportionally mixing porcelain powders. Thirty-nine specimens were randomly selected to train the BPNN model, while the remaining four specimens were used to test and calibrate the model. A CCM system based on the improved BPNN model was constructed using MATLAB software. A comparison of the novel CCM system and the traditional visual method was conducted by evaluating the color reproduction results of 10 maxillary central incisors. Metal-ceramic specimens were fabricated using two color reproduction approaches. Color distributions (L*, a*, and b*) of the target teeth and of the corresponding metal-ceramic specimens were measured using a spectroradiometer. Color differences (ΔE) and color distributions (ΔL*, Δa*, and Δb*) between the teeth and their corresponding specimens were calculated. The average ΔE value of the CCM system was 1.89 ± 0.75, which was lower than that of the visual approach (3.54 ± 1.11, p < 0.01). With respect to color distributions, substantial differences were found between the two color-matching systems, except for ΔL* (p > 0.05). The novel CCM system produced greater accuracy in color reproduction within the given color space than the traditional visual approach.

An investigation on the role of multimodal metaphors in e‐feedback interfaces

PurposeThe purpose of this paper is to investigate the usability (effectiveness, efficiency and user satisfaction) of e‐feedback interfaces. The experiment compares a traditional visual approach with a multimodal approach in order to determine the impact of multimodal metaphors upon the user's understanding, reasoning and engagement with the e‐feedback.Design/methodology/approachThe empirical investigation involved visual (text with graphical illustrations) and multimodal (audio‐visual with expressive avatars and recorded speech) experimental e‐feedback platforms. Both experimental platforms provided the same e‐feedback but used different interaction metaphors to convey the information. The evaluation approach measured effectiveness, efficiency and user satisfaction.FindingsThe results showed that the multimodal approach increased usability in terms of effectiveness, efficiency and engagement of users with the e‐feedback. There is a very clear prima facie case that combining different communication metaphors to convey information involved in the e‐feedback simultaneously does not increase the information overload on users. This however was observed to be the case when the visual channel was used.Originality/valueThis paper introduces a unique approach that uses specific combinations of multimodal metaphors to communicate information about e‐feedback simultaneously. This approach increased the usability of e‐feedback and user's engagement in interfaces for e‐learning applications.

Comparison of computer ST criteria for diagnosis of severe coronary artery disease

To determine which computer ST criteria are superior for predicting patterns and severity of coronary artery disease during exercise testing, 230 male veterans were studied who had both coronary angiography and a treadmill exercise test. Significant (p ≤0.05) differences in computer-scored ST criteria were observed among patients with progressively increasing disease severity. Three-vessel/left main disease produced responses significantly different from 1and 2-vessel disease or those with < 70% occlusion. Discriminant function analysis revealed that horizontal or downsloping ST depression measured at the J junction during exercise or recovery, or both, was the most powerful predictor of severe disease. With use of a cut point of 0.075 mV ST depression, horizontal or downsloping ST depression alone yielded a sensitivity of 50% (95% confidence interval = 35 to 65%) and specificity of 71% for prediction of severe disease; the only additional variable that added significantly to the prediction was exercise capacity, which improved sensitivity to 57% (95% confidence interval = 41 to 72%) with no change in specificity. Measurements of ST amplitude at the J junction and at 60 ms after the J point without slope considered and other scores, including the Treadmill Exercise Score, ST Integral, and ST/heart rate index, had a lower but comparable predictive accuracy when compared with horizontal or downsloping ST depression. Prediction of coronary artery disease severity can be achieved using computerized electrocardiographic measurements obtained during exercise testing. The most powerful marker for severe coronary artery disease is the amount of horizontal or downsloping ST-segment depression during exercise or recovery, or both, a measurement that simulates the traditional visual approach.