Voice Versus Keyboard and Mouse for Text Creation on Arabic User Interfaces

Voice User Interfaces (VUIs) are increasingly popular owing to improvements in automatic speech recognition. However, the understanding of user interaction with VUIs, particularly Arabic VUIs, remains limited. Hence, this research compared user performance, learnability, and satisfaction when using voice and keyboard-and-mouse input modalities for text creation on Arabic user interfaces. A Voice-enabled Email Interface (VEI) and a Traditional Email Interface (TEI) were developed. Forty participants attempted pre-prepared and self-generated message creation tasks using voice on the VEI, and the keyboard-and-mouse modal on the TEI. The results showed that participants were faster (by 1.76 to 2.67 minutes) in pre-prepared message creation using voice than using the keyboard and mouse. Participants were also faster (by 1.72 to 2.49 minutes) in self-generated message creation using voice than using the keyboard and mouse. Although the learning curves were more efficient with the VEI, more participants were satisfied with the TEI. With the VEI, participants reported problems, such as misrecognitions and misspellings, but were satisfied about the visibility of possible executable commands and about the overall accuracy of voice recognition.

Improving Security and Fairness in Federated Learning Systems

The ever-increasing use of Artificial Intelligence applications has made apparent that the quality of the training datasets affects the performance of the models. To this end, Federated Learning aims to engage multiple entities to contribute to the learning process with locally maintained data, without requiring them to share the actual datasets. Since the parameter server does not have access to the actual training datasets, it becomes challenging to offer rewards to users by directly inspecting the dataset quality. Instead, this paper focuses on ways to strengthen user engagement by offering “fair” rewards, proportional to the model improvement (in terms of accuracy) they offer. Furthermore, to enable objective judgment of the quality of contribution, we devise a point system to record user performance assisted by blockchain technologies. More precisely, we have developed a verification algorithm that evaluates the performance of users’ contributions by comparing the resulting accuracy of the global model against a verification dataset and we demonstrate how this metric can be used to offer security improvements in a Federated Learning process. Further on, we implement the solution in a simulation environment in order to assess the feasibility and collect baseline results using datasets of varying quality.

An Empirical Evaluation of Force-Directed Graph Layout

<p>Force-directed graph layout is a widely used algorithm for the automatic layout of graphs. Little experimental work has been done exploring the behaviour of the algorithm under a variety of conditions. This thesis carries out three large-scale metric-based experiments. The first explores how the core algorithm behaves under changes to initial conditions. The second looks at extending the force-directed layout algorithm with additional forces to reduce overlaps. The third develops a novel symmetry metric for graphs and uses that to explore the symmetries of graphs. This thesis also carries out a user study to show that the differences reported by metrics in the graphs are reflected in a difference in user performance when using graphs for a free-form selection task.</p>

An Empirical Evaluation of Force-Directed Graph Layout

<p>Force-directed graph layout is a widely used algorithm for the automatic layout of graphs. Little experimental work has been done exploring the behaviour of the algorithm under a variety of conditions. This thesis carries out three large-scale metric-based experiments. The first explores how the core algorithm behaves under changes to initial conditions. The second looks at extending the force-directed layout algorithm with additional forces to reduce overlaps. The third develops a novel symmetry metric for graphs and uses that to explore the symmetries of graphs. This thesis also carries out a user study to show that the differences reported by metrics in the graphs are reflected in a difference in user performance when using graphs for a free-form selection task.</p>

Classification Performance and Feature Space Characteristics in Individuals with Upper Limb Loss Using Sonomyography

Objective: Sonomyography, or ultrasound-based sensing of muscle deformation, is an emerging modality for upper limb prosthesis control. Although prior studies have shown that individuals with upper limb loss can achieve successful motion classification with sonomyography, it is important to better understand the time-course over which proficiency develops. In this study, we characterized user performance during their initial and subsequent exposures to sonomyography. Method: Ultrasound images corresponding to a series of hand gestures were collected from individuals with transradial limb loss under three scenarios: during their initial exposure to sonomyography (Experiment 1), during a subsequent exposure to sonomyography where they were provided biofeedback as part of a training protocol (Experiment 2), and during testing sessions held on different days (Experiment 3). User performance was characterized by offline classification accuracy, as well as metrics describing the consistency and separability of the sonomyography signal patterns in feature space. Results: Classification accuracy was high during initial exposure to sonomyography (96.2 ± 5.9%) and did not systematically change with the provision of biofeedback or on different days. Despite this stable classification performance, some of the feature space metrics changed. Conclusions: User performance was strong upon their initial exposure to sonomyography and did not improve with subsequent exposure. Clinical Impact: Prosthetists may be able to quickly assess if a patient will be successful with sonomyography without submitting them to an extensive training protocol, leading to earlier socket fabrication and delivery.

The influence Quality of information, Sistem Quality and Service Quality on Satisfaction and User Performace

Research aims: This study aims to analyze the effect of information quality, system quality, and service quality on user satisfaction so that it has an impact on user performance.Design/Methodology/Approach: This type of research is conducted using a quantitative approach, namely research using research instruments, quantitative data analysis with the aim of testing the predetermined hypothesis,The sample used was 61 Religious Teachers at Muhammadiyah Vocational Schools in Cilacap Regency. The data obtained through questionnaires were processed using PLS analysis (Partial Leas Square). Testing the research model (Outer Model) was carried out in two stages, namely testing of the measurement model (Outer Model) with Convergent Validity, Discriminate Validity and structural testing (Inner Model) with Path Coeffecient, Specific Indirect Value.Research findings: The results of data analysis show that information quality has no effect on user satisfaction, system quality, service quality has a positive effect on user satisfaction, system quality has no effect on user performance, service quality affects user performance, information quality, user satisfaction has a positive effect on user performance, namely religion teacher at Muhammadiyah Vocational High School in Cilacap Regency.Theoretical contribution/ Originality: This study examines the influence of information quality, system quality and service quality for employeesPractitioner/Policy implication: it should be that the higher the level of information quality, system quality, service quality, the higher the performanceResearch limitation/Implication: This research was only conducted in Muhammadiyah Junior High School in Cilacap Regency