The Intelligent Speed Adaptation (ISA) project we describe in this article is based on Pay as You Drive principles. These principles assume that the ISA equipment informs a driver of the speed limit, warns the driver when speeding and calculates penalty points. Each penalty point entails the reduction of a 30% discount on the driver's car insurance premium, which therefore produced the name, Pay as You Speed. The ISA equipment consists of a GPS-based On Board Unit with a mobile phone connection to a web server. The project was planned for a three-year test period with 300 young car drivers, but it never succeeded in recruiting that number of drivers. After several design changes, the project eventually went forward with 153 test drivers of all ages. This number represents approximately one thousandth of all car owners in the proving ground of North Jutland in Denmark. Furthermore the project was terminated before its scheduled closing date. This article describes the project with an emphasis on recruitment efforts and the project's progress. We include a discussion of possible explanations for the failure to recruit volunteers for the project and reflect upon the general barriers to using ISA with ordinary drivers.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.aap.2011.03.014 | DOI Listing |
Magn Reson Imaging
January 2025
School of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China.
Magnetic resonance imaging (MRI) is a non-invasive medical imaging technique that is widely used for high-resolution imaging of soft tissues and organs. However, the slow speed of MRI imaging, especially in high-resolution or dynamic scans, makes MRI reconstruction an important research topic. Currently, MRI reconstruction methods based on deep learning (DL) have garnered significant attention, and they improve the reconstruction quality by learning complex image features.
View Article and Find Full Text PDFHealthcare (Basel)
December 2024
Graduate School of Biomedical Sciences, Tokushima University, Tokushima 770-8509, Japan.
This study aimed to determine the association between chronic schizophrenia, extrapyramidal symptoms (EPSs), body composition, nutritional status, and dynapenia/sarcopenia. Data from 68 chronic patients with schizophrenia were analyzed using Spearman's rho correlation coefficients, Kruskal-Wallis test, Mann-Whitney U test, and Cramér's V statistics. Among the participants, 32.
View Article and Find Full Text PDFHeliyon
October 2024
Mathematical Science Department, University of Malawi, Malawi.
Front Med (Lausanne)
October 2024
School of Management, Shandong Second Medical University, Weifang, China.
Background: Multiple Chronic Diseases (MCD) are the co-occurrence of two or more chronic conditions within an individual. Compared to patients with a single chronic disease, those with MCD face challenges related to polypharmacy, which increases the risk of adverse drug events, side effects, and drug-drug interactions. Understanding the specific medication preferences of patients with MCD is crucial to optimize treatment plans and enhance treatment safety.
View Article and Find Full Text PDFPLoS One
October 2024
Agricultural Engineering Department, Faculty of Agriculture and Natural Resources, Aswan University, Aswan, Egypt.
There are many problems related to the use of machine learning and machine vision technology on a commercial scale for cutting sugarcane seeds. These obstacles are related to complex systems and the way the farmers operate them, the possibility of damage to the buds during the cleaning process, and the high cost of such technology. In order to address these issues, a set of RGB color sensors was used to develop an automated sugarcane seed cutting machine (ASSCM) capable of identifying the buds that had been manually marked with a unique color and then cutting them mechanically, and the sugarcane seed exit chute was provided with a sugarcane seed monitoring unit.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!