ProcessWiki: A Contribution for Bridging the Last Mile Problem in Automotive Retail

Author(s):  
Matthias Kurz ◽  
Sebastian Huber ◽  
Bernd Hilgarth
Keyword(s):  
2020 ◽  
pp. 81-84
Author(s):  
Griffin Kao ◽  
Jessica Hong ◽  
Michael Perusse ◽  
Weizhen Sheng
Keyword(s):  

Author(s):  
Liying Song ◽  
Tom Cherrett ◽  
Fraser McLeod ◽  
Wei Guan
Keyword(s):  

Author(s):  
Miroslav Svitek ◽  
Sergey Kozhevnikov ◽  
Patrik Horazd'ovsky ◽  
Dmitry Poludov ◽  
Xenia Pogorelskih

2019 ◽  
Vol 220 ◽  
pp. 01006
Author(s):  
I.Z. Latypov ◽  
D.O. Akat’ev ◽  
V.V. Chistyakov ◽  
M.A. Fadeev ◽  
A.K. Khalturinsky ◽  
...  

The work is devoted to the creation of a telescopic transceiver system that organizes an atmospheric point-to-point communication channel, and its use for quantum communication at sideband frequencies as the “last mile” for data protection in a geographically distributed data centre


2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Aihua Fan ◽  
Xumei Chen ◽  
Tao Wan

In recent years, there has been rapid development in bicycle-sharing systems (BSS) in China. Moreover, such schemes are considered promising solutions to the first/last mile problem. This study investigates the mode choice behaviors of travelers for first/last mile trips before and after the introduction of bicycle-sharing systems. Travel choice models for first/last mile trips are determined using a multinomial logit model. It also analyzes the differences in choice behavior between the young and other age groups. The findings show that shared bicycles become the preferred mode, while travelers preferred walking before bicycle-sharing systems were implemented. Gender, bicycle availability, and travel frequency were the most significant factors before the implementation of bicycle-sharing systems. However, after implementation, access distance dramatically affects mode choices for first/last mile trips. When shared bicycles are available, the mode choices of middle-aged group depend mainly on gender and access distance. All factors are not significant for the young and aged groups. More than 80% of public transport travelers take walking and shared bicycles as feeder modes. The proposed models and findings contribute to a better understanding of travelers’ choice behaviors and to the development of solutions for the first/last mile problem.


10.2196/16385 ◽  
2019 ◽  
Vol 21 (10) ◽  
pp. e16385
Author(s):  
Bradford William Hesse

Internet-augmented medicine has a strong role to play in ensuring that all populations benefit equally from discoveries in the medical sciences. Yet, data from the Centers for Disease Control and Prevention collected from 1999 to 2014 suggested that during the first phase of internet diffusion, progress against mortality has stalled, and in some cases, receded in rural areas that are traditionally underserved by medical and broadband resources. This problem of failing to extend the benefits of extant medical knowledge equitably to all populations regardless of geography can be framed as the “last mile problem in health care.” In theory, the internet should help solve the last mile problem by making the best knowledge in the world available to everyone worldwide at a low cost and no delay. In practice, the antiquated supply chains of industrial age medicine have been slow to yield to the accelerative forces of evolving internet capacity. This failure is exacerbated by the expanding digital divide, preventing residents of isolated, geographically distant communities from taking full advantage of the digital health revolution. The result, according to the Federal Communications Commission’s (FCC’s) Connect2Health Task Force, is the unanticipated emergence of “double burden counties,” ie, counties for which the mortality burden is high while broadband access is low. The good news is that a convergence of trends in internet-enabled health care is putting medicine within striking distance of solving the last mile problem both in the United States and globally. Specific trends to monitor over the next 25 years include (1) using community-driven approaches to bridge the digital divide, (2) addressing structural disconnects in care through P4 Medicine, (3) meeting patients at “point-of-need,” (4) ensuring that no one is left behind through population management, and (5) self-correcting cybernetically through the learning health care system.


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