Assessing Smartphone Ease of Use and Learning from the Perspective of Novice and Expert Users: Development and Illustration of Mobile Benchmark Tasks

Assessing usability of device types with novel function sets that are adopted by diverse user groups requires one to explore a variety of approaches. In this paper, we develop such an approach to assess usability of smartphone devices. Using a three-stage Delphi-method study, we identify sets of benchmark tasks that can be used to assess usability for various user types. These task sets enable one to evaluate smartphone platforms from two perspectives: ease of learning (for those unfamiliar with smartphone use) and ease of use (for experienced users). We then demonstrate an approach for using this task set by performing an exploratory study of both inexperienced smartphone users (using a convenience sample) and experienced users (using the keystroke model). Our exploration illustrates the methodology for using such a task set and, in so doing, reveals significant differences among the leading smartphone platforms between novice and expert users. As such, we provide some preliminary evidence that ease of use is indeed significantly different from ease of learning

Information fusion-based cybersecurity threat detection for intelligent transportation system

Intelligent Transportation Systems (ITS) are sophisticated systems that leverage various technologies to increase the safety, efficiency, and sustainability of transportation. By relying on wireless communication and data collected from diverse sensors, ITS is vulnerable to cybersecurity threats. With the increasing number of attacks on ITS worldwide, detecting and addressing cybersecurity threats has become critically important. This need will only intensify with the impending arrival of autonomous vehicles. One of the primary challenges is identifying critical ITS assets that require protection and understanding the vulnerabilities that cyber attackers can exploit. Additionally, creating a standard profile for ITS is challenging due to the dynamic traffic pattern, which exhibits changes in the movement of vehicles over time. To address these challenges, this paper proposes an information fusion-based cybersecurity threat detection method. Specifically, we employ the Kalman filter for noise reduction, Dempster-Shafer decision theory and Shannon’s entropy for assessing the probabilities of traffic conditions being normal, intruded, and uncertain. We utilised Simulation of Urban Mobility (SUMO) to simulate the Melbourne CBD map and historical traffic data from the Victorian transport authority. Our simulation results reveal that information fusion with three sensor data is more effective in detecting normal traffic conditions. On the other hand, for detecting anomalies, information fusion with two sensor data is more efficient

The growth of the central region by acquisition of counterrotating gas in star-forming galaxies

Galaxies grow through both internal and external processes. In about 10% of nearby red galaxies with little star formation, gas and stars are counter-rotating, demonstrating the importance of external gas acquisition in these galaxies. However, systematic studies of such phenomena in blue, star-forming galaxies are rare, leaving uncertain the role of external gas acquisition in driving evolution of blue galaxies. Here, based on new measurements with integral field spectroscopy of a large representative galaxy sample, we find an appreciable fraction of counterrotators among blue galaxies (9 out of 489 galaxies). The central regions of blue counterrotators show younger stellar populations and more intense, ongoing star formation than their outer parts, indicating ongoing growth of the central regions. The result offers observational evidence that the acquisition of external gas in blue galaxies is possible; the interaction with pre-existing gas funnels the gas into nuclear regions (<1 kpc) to form new stars

Prominent and regressive brain developmental disorders associated with nance-horan syndrome

Nance-Horan syndrome (NHS) is a rare X-linked developmental disorder caused mainly by loss of function variants in the NHS gene. NHS is characterized by congenital cataracts, dental anomalies, and distinctive facial features, and a proportion of the affected individuals also present intellectual disability and congenital cardiopathies. Despite identification of at least 40 distinct hemizygous variants leading to NHS, genotype-phenotype correlations remain largely elusive. In this study, we describe a Sicilian family affected with congenital cataracts and dental anomalies and diagnosed with NHS by whole-exome sequencing (WES). The affected boy from this family presented a late regression of cognitive, motor, language, and adaptive skills, as well as broad behavioral anomalies. Furthermore, brain imaging showed corpus callosum anomalies and periven-tricular leukoencephalopathy. We expand the phenotypic and mutational NHS spectrum and review potential disease mechanisms underlying the central neurological anomalies and the potential neu-rodevelopmental features associated with NHS

Muscular collision chess:A qualitative exploration of the role and development of cognition, understanding and knowledge in elite-level decision making

Decision making (DM) is a crucial part of team invasion games. The role of context and how this drives both the initial DM and primes in-action planning and execution, termed contextual priors, has been investigated. Findings suggest a significant role for cognition, which appears to run contrary to some of the suggestions made by an ecological dynamics approach. Wishing to clarify this situation for coaches and psychologists, this research explores the experience of nine top-tier key decision makers in rugby union, using an interview approach. Results showed a wide range of context-based information considered by players during the DM process. Furthermore, this information acted to prime subsequent attention and in-action thinking. Finally, this research sought to understand if, and therefore how, DM could be taught, developed and primed by players and coaches. Our data are supportive of a more cognitively focused approach to developing DM although our data do not dismiss a role for direct perception in optimising performance. Implications for practice are discussed

Fluorescence spectroscopy for the detection of potentially malignant disorders of the oral cavity: analysis of 30 cases

Oral cancer is a major health problem worldwide and although early diagnosis of potentially malignant and malignant diseases is associated with better treatment results, a large number of cancers are initially misdiagnosed, with unfortunate consequences for long-term survival. Fluorescence spectroscopy is a noninvasive modality of diagnostic approach using induced fluorescence emission in tumors that can improve diagnostic accuracy. The objective of this study was to determine the ability to discriminate between normal oral mucosa and potentially malignant disorders by fluorescence spectroscopy. Fluorescence investigation under 408 and 532 nm excitation wavelengths was performed on 60 subjects, 30 with potentially malignant disorders and 30 volunteers with normal mucosa. Data was analyzed to correlate fluorescence patterns with clinical and histopathological diagnostics. Fluorescence spectroscopy used as a point measurement technique resulted in a great variety of spectral information. In a qualitative analysis of the fluorescence spectral characteristics of each type of injury evaluated, it was possible to discriminate between normal and abnormal oral mucosa. The results show the potential use of fluorescence spectroscopy for an improved discrimination of oral disorders.FAPESP/CePOF-CEPID (07/57126-5)CNPq (477439/2007-1)Instituto Nacional de Ciência e Tecnologia em Oncogenômica (INCITO