Factors influencing drivers’ acceptance of in-vehicle monitoring

This study investigates the influencing factors that affect drivers’ acceptance of products or services, that implement in-vehicle monitoring. The rapid growth of the sharing economy, aided by smartphones, results in many innovative automotive applications from commercial service providers, such as Uber, MaaS or carsharing applications. However, many projects that try to introduce new business models, using in-vehicle monitoring, ultimately were not received favorably. To investigate the factors, a qualitative analysis and ecosystem approach were used; 19 stakeholders, consisting of regular and professional drivers, as well as automotive-related organisations, unions, transport and research agencies, were interviewed and their inputs were analysed to provide a starting reference of the influencing factors. The study found that there are 9 factors that influence driver’s acceptance of in-vehicle monitoring: (1) Comparing benefits and costs, (2) Privacy, (3) Autonomy of driver, (4) Driver’s ideals and morale, (5) Ownership of vehicle, (6) Trust, (7) Design of system, (8) Awareness of technology, and (9) Media and marketing. Organisations are encouraged to consider these influencing factors when designing their products and services. The study recommends that organisations design products and services that appeals to the drivers’ motivation and perspective of what is important to them during their drive. In addition, technical considerations for data privacy, security and trust are presented. Finally, the overall design and marketing recommendations for organisations are presented

Field-only integral equation method for time domain scattering of electromagnetic pulses

The scattering of electromagnetic pulses is described using a non-singular boundary integral method to solve directly for the field components in the frequency domain, and Fourier transform is then used to obtain the complete space-time behavior. This approach is stable for wavelengths both small and large relative to characteristic length scales. Amplitudes and phases of field values can be obtained accurately on or near material boundaries. Local field enhancement effects due to multiple scattering of interest to applications in microphotonics are demonstrated.Comment: 7 pages, 9 figure

A Comprehensive Survey of Deep Learning in Remote Sensing: Theories, Tools and Challenges for the Community

In recent years, deep learning (DL), a re-branding of neural networks (NNs), has risen to the top in numerous areas, namely computer vision (CV), speech recognition, natural language processing, etc. Whereas remote sensing (RS) possesses a number of unique challenges, primarily related to sensors and applications, inevitably RS draws from many of the same theories as CV; e.g., statistics, fusion, and machine learning, to name a few. This means that the RS community should be aware of, if not at the leading edge of, of advancements like DL. Herein, we provide the most comprehensive survey of state-of-the-art RS DL research. We also review recent new developments in the DL field that can be used in DL for RS. Namely, we focus on theories, tools and challenges for the RS community. Specifically, we focus on unsolved challenges and opportunities as it relates to (i) inadequate data sets, (ii) human-understandable solutions for modelling physical phenomena, (iii) Big Data, (iv) non-traditional heterogeneous data sources, (v) DL architectures and learning algorithms for spectral, spatial and temporal data, (vi) transfer learning, (vii) an improved theoretical understanding of DL systems, (viii) high barriers to entry, and (ix) training and optimizing the DL.Comment: 64 pages, 411 references. To appear in Journal of Applied Remote Sensin

Thaumatin Recovery Via Bioengineering Route And In-Vitro Culture Of Thaumatococcus Daniellii [QP552.T43 C454 2008 f rb].

Peningkatan dalam permintaan untuk ramuan pemanis asli telah menarik minat para penyelidik dan saintis kepada protein perisa manis. Sehingga kini, tujuh protein telah dikenalpasti berupaya memberi rasa manis kepada manusia. Sweet tasting proteins have sparked new interest amongst researchers and scientist alike due to the increased demand for natural sweetening ingredients. To date, there are seven proteins identified to be able to elicit sweetness in humans