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For establishing the suitable framework for the tool development in this study, gaining an insight into the driving attributes of the highly complex relationship between humans (operation controllers) and technology used in the decision making processes (tools) at the AOCC was necessary.
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Ten driving data attributes analyzed here are those previously mentioned (steering angle, speed, longitudinal acceleration, lateral acceleration, yaw rate, accelerator control, brake control, lateral displacement, accelerator control speed, and brake control speed), which covers both longitudinal and lateral control of the vehicle.
Once these MRA models gain more acceptance, they may facilitate scenario testing to determine which control points may be most effective in reducing risks and which risk-driving attributes should be specifically considered and minimized during the development of novel antibiotics.
Using technology-based services in the public sector as the setting, we identified the key service attributes driving adoption and use of transactional e-government services, and citizens' preference structures across these attributes.
Insect pollinators and flowering plants were investigated on a range of riparian margins, and their adjacent grassland fields, to determine the main physical and botanical attributes driving pollinator diversity.
Conjoint analysis has been used in health economics to determine what health products and services patients prefer, and the attributes driving these preferences [ 52, 53, 56- 59].
Ultimately, DCE studies can determine which attributes are driving patient preferences, the trade-offs between attributes that people are willing to accept and how changes in attributes can lead to changes in preferences and likely service uptake.
Therefore, DCEs can explore which attributes are driving public preferences, the trade-offs between attributes that people are willing to accept, and how changes in attributes can lead to changes in preferences.
Ultimately, DCE studies can determine which attributes are driving patient preferences, the trade-offs people make between attributes and how changes in attributes can lead to changes in preferences and likely service uptake.
In this case, we can identify which attributes are driving participants' preferences, the trade-offs participants make between attributes and how changes in attributes can lead to changes in the patients' willingness to participate in the intervention.
Importantly, our data clearly show that the peak driving forces otherwise attributed to recoil, and hydraulic forces, respectively, are of a similar order of magnitude.
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