Reducing fuel consumption through modular vehicle architectures

By identifying energy waste streams in vehicles fuel consumption and introducing the concept of lean driving systems, a technological gap for reducing fuel consumption was identified. This paper proposes a solution to overcome this gap, through a modular vehicle architecture aligned with driving patterns. It does not address detailed technological solutions; instead it models the potential effects in fuel consumption through a modular concept of a vehicle and quantifies their dependence on vehicle design parameters (manifesting as the vehicle mass) and user behavior parameters (driving patterns manifesting as the use of a modular car in lighter and heavier mode, in urban and highway cycles). Modularity has been functionally applied in automotive industry as manufacture and assembly management strategies; here it is thought as a product development strategy for flexibility in use, driven by environmental concerns and enabled by social behaviors. The authors argue this concept is a step forward in combining technological solutions and social behavior, of which eco-driving is a vivid example, and potentially evolutionary to a lean, more sustainable, driving culture.

The Main Determinants of the Use of the Cost Accounting System in Portuguese Local Government

This paper explores the main determinants of the use of the cost accounting system (CAS) in Portuguese local government (PLG). Regression analysis is used to study the fit of a model of accounting changes in PLG, focused on cost accounting systems oriented to activities and outputs. Based on survey data gathered from PLG, we have found that the use of information in decision-making and external reporting is still a mirage. We obtain evidence about the influence of the internal organizational context (especially the lack of support and difficulties in the CAS implementation) in the use for internal purposes, while the institutional environment (like external pressures to implement the CAS) appears to be more deterministic of the external use. Results strengthen the function of external reporting to legitimate the organization’s activities to external stakeholders. On the other hand, some control variables (like political competition, usefulness and experience) also evidence some explanatory power in the model. Some mixed results were found that appeal to further research in the future. Our empirical results contribute to understand the importance of interconnecting the contingency and institutional approaches to gain a clear picture of cost accounting changes in the public sector.

Improving The Robustness Of Interventional 4D Ultrasound Segmentation Through The Use Of Personalized Shape Priors

While fluoroscopy is still the most widely used imaging modality to guide cardiac interventions, the fusion of pre-operative Magnetic Resonance Imaging (MRI) with real-time intra-operative ultrasound (US) is rapidly gaining clinical acceptance as a viable, radiation-free alternative. In order to improve the detection of the left ventricular (LV) surface in 4D ultrasound, we propose to take advantage of the pre-operative MRI scans to extract a realistic geometrical model representing the patients cardiac anatomy. This could serve as prior information in the interventional setting, allowing to increase the accuracy of the anatomy extraction step in US data. We have made use of a real-time 3D segmentation framework used in the recent past to solve the LV segmentation problem in MR and US data independently and we take advantage of this common link to introduce the prior information as a soft penalty term in the ultrasound segmentation algorithm. We tested the proposed algorithm in a clinical dataset of 38 patients undergoing both MR and US scans. The introduction of the personalized shape prior improves the accuracy and robustness of the LV segmentation, as supported by the error reduction when compared to core lab manual segmentation of the same US sequences.