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A round robin was conducted to evaluate the state of the art of room acoustic modeling software both in the physical and perceptual realms. The test was based on six acoustic scenes highlighting specific acoustic phenomena and for three complex, “real-world” spatial environments. The results demonstrate that most present simulation algorithms generate obvious model errors once the assumptions of geometrical acoustics are no longer met. As a consequence, they are neither able to provide a reliable pattern of early reflections nor do they provide a reliable prediction of room acoustic parameters outside a medium frequency range. In the perceptual domain, the algorithms under test could generate mostly plausible but not authentic auralizations, i.e., the difference between simulated and measured impulse responses of the same scene was always clearly audible. Most relevant for this perceptual difference are deviations in tone color and source position between measurement and simulation, which to a large extent can be traced back to the simplified use of random incidence absorption and scattering coefficients and shortcomings in the simulation of early reflections due to the missing or insufficient modeling of diffraction.

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BackgroundThe use of mobile devices in health (mobile health/mHealth) coupled with related technologies promises to transform global health delivery by creating new delivery models that can be integrated with existing health services. These delivery models could facilitate healthcare delivery into rural areas where there is limited access to high-quality access care. Mobile technologies, Internet of Things and 5G connectivity may hold the key to supporting increased velocity, variety and volume of healthcare data.ObjectiveThe purpose of this study is to identify and analyse challenges related to the current status of India’s healthcare system—with a specific focus on mHealth and big-data analytics technologies. To address these challenges, a framework is proposed for integrating the generated mHealth big-data and applying the results in India's healthcare.MethodA critical review was conducted using electronic sources between December 2018 and February 2019, limited to English language articles and reports published from 2010 onwards.Main outcomeThis paper describes trending relationships in mHealth with big-data as well as the accessibility of national opportunities when specific barriers and constraints are overcome. The paper concentrates on the healthcare delivery problems faced by rural and low-income communities in India to illustrate more general aspects and identify key issues. A model is proposed that utilises generated data from mHealth devices for big-data analysis that could result in providing insights into the India population health status. The insights could be important for public health planning by the government towards reaching the Universal Health Coverage.ConclusionBiomedical, behavioural and lifestyle data from individuals may enable customised and improved healthcare services to be delivered. The analysis of data from mHealth devices can reveal new knowledge to effectively and efficiently support national healthcare demands in less developed nations, without fully accessible healthcare systems.

This research addresses blackhole and selective forwarding routing attacks, which are fundamental security attacks on the routing of data in IoT networks. Most IoT devices today, from medical devices to connected vehicles and even smart buildings, have the capability of communicating wirelessly with one another. Although, consumers are progressively embracing the concept of connected devices, recent studies indicate that security is not high on the priority list of manufacturers especially in the way these IoT devices route and communicate data amongst themselves. Thus, it leaves the door wide open to attacks and compromises. In this study, a trust-based routing Protocol for Low-Power and Lossy Networks addressing blackhole and selective forwarding attacks is proposed. We show that our proposed protocol is not only secure from blackhole and selective forwarding attacks, but also does not impose undue overheads on network traffic.

Social engineering attacks are possibly one of the most dangerous forms of security and privacy attacks since they are technically oriented to psychological manipulation and have been growing in frequency with no end in sight. This research study assessed the major aspects and underlying concepts of social engineering attacks and their influence in the New Zealand banking sector. The study further identified attack stages and provided a user-reflective model for the mitigation of attacks at every stage of the social engineering attack cycle. The outcome of this research was a model that provides users with a process of having a reflective stance while engaging in online activities. Our model is proposed to aid users and, of course, financial institutions to rethink their antisocial engineering strategies while constantly maintaining a self-reflective assessment of whether they are being subjected to social engineering attacks while transacting online.

With the Room Acoustical Quality Inventory (RAQI), a measuring instrument for the perceptual space of performance venues for music and speech has been developed. First, a focus group with room acoustical experts determined relevant aspects of room acoustical impression in the form of a comprehensive list of 50 uni- and bipolar items in different categories. Then, n = 190 subjects rated their acoustical impression of 35 binaurally simulated rooms from 2 listening positions, with symphonic orchestra, solo trumpet, and dramatic speech as audio content. Subsequent explorative and confirmative factor analyses of the questionnaire data resulted in three possible solutions with four, six, and nine factors of room acoustical impression. The factor solutions, as well as the related RAQI items, were tested in terms of reliability, validity, and several types of measurement invariance, and were cross-validated by a follow-up experiment with a subsample of 46% of the original participants, which provided re-test reliabilities and stability coefficients for all RAQI constructs. The resulting psychometrically evaluated measurement instrument can be used for room quality assessment, acoustical planning, and the further development of room acoustical parameters in order to predict primary acoustical qualities of venues for music and speech.