Vehicle-to-Grid Optimization Considering Battery Aging

Electric vehicles (EVs) play a substantial role in reducing greenhouse gas emission and support a sustainable future. However, the increase of EV may lead to rising electricity demand and fluctuation. In this paper, the EV is proposed as a means to support the electricity grid via the vehicle-to-grid (V2G) technology. To reduce energy demand peaks, charging is planned during off-peak hours. Additionally, the EV battery may be used as a buffer to store energy during off-peak hours, and to supply energy to the grid during peak hours. Furthermore, grid frequency may be regulated by controlling the charging power. Since battery utilization will be increased during V2G operations, battery degradation is included in this study. A case study of Swedish households shows that the V2G is not only contributing to the stability of the grid, but may also help reducing the operating cost of an EV owner, even when battery degradation is considered

FuSSI-Net: Fusion of Spatio-temporal Skeletons for Intention Prediction Network

Pedestrian intention recognition is very important to develop robust and safe autonomous driving (AD) and advanced driver assistance systems (ADAS) functionalities for urban driving. In this work, we develop an end-to-end pedestrian intention framework that performs well on day- and night- time scenarios. Our framework relies on objection detection bounding boxes combined with skeletal features of human pose. We study early, late, and combined (early and late) fusion mechanisms to exploit the skeletal features and reduce false positives as well to improve the intention prediction performance. The early fusion mechanism results in AP of 0.89 and precision/recall of 0.79/0.89 for pedestrian intention classification. Furthermore, we propose three new metrics to properly evaluate the pedestrian intention systems. Under these new evaluation metrics for the intention prediction, the proposed end-to-end network offers accurate pedestrian intention up to half a second ahead of the actual risky maneuver.Comment: 5 pages, 6 figures, 5 tables, IEEE Asilomar SS

The geras solutions cognitive test for assessing cognitive impairment : normative data from a population-based cohort

Background: There is a need for the development of accurate, accessible and efficient screening instruments, focused on early-stage detection of neurocognitive disorders. The Geras Solutions cognitive test (GSCT) has showed potential as a digital screening tool for cognitive impairment but normative data are needed. Objective: The aim of this study was to obtain normative data for the GSCT in cognitively healthy patients, investigate the effects of gender and education on test scores as well as examine test-retest reliability. Methods: The population in this study consisted of 144 cognitively healthy subjects (MMSE>26) all at the age of 70 who were earlier included in the Healthy Aging Initiative Study conducted in Umeå, Sweden. All patients conducted the GSCT and a subset of patients (n=32) completed the test twice in order to establish test-retest reliability. Results: The mean GSCT score was 46.0 (±4.5) points. High level of education (>12 years) was associated with a high GSCT score (p = 0.02) while gender was not associated with GSCT outcomes (p = 0.5). GSCT displayed a high correlation between test and retest (r(30) = 0.8, p <0.01). Conclusion: This study provides valuable information regarding normative test-scores on the GSCT for cognitively healthy individuals and indicates education level as the most important predictor of test outcome. Additionally, the GSCT appears to display a good test-retest reliability further strengthening the validity of the test

The Geras Solutions Cognitive Test for Assessing Cognitive Impairment: Normative Data from a Population-Based Cohort

BackgroundThere is a need for the development of accurate, accessible and efficient screening instruments, focused on early-stage detection of neurocognitive disorders. The Geras Solutions cognitive test (GSCT) has showed potential as a digital screening tool for cognitive impairment but normative data are needed.ObjectiveThe aim of this study was to obtain normative data for the GSCT in cognitively healthy patients, investigate the effects of gender and education on test scores as well as examine test-retest reliability.MethodsThe population in this study consisted of 144 cognitively healthy subjects (MMSE>26) all at the age of 70 who were earlier included in the Healthy Aging Initiative Study conducted in Umeå, Sweden. All patients conducted the GSCT and a subset of patients (n=32) completed the test twice in order to establish test-retest reliability.ResultsThe mean GSCT score was 46.0 (±4.5) points. High level of education (>12 years) was associated with a high GSCT score (p = 0.02) while gender was not associated with GSCT outcomes (p = 0.5). GSCT displayed a high correlation between test and retest (r(30) = 0.8, p ConclusionThis study provides valuable information regarding normative test-scores on the GSCT for cognitively healthy individuals and indicates education level as the most important predictor of test outcome. Additionally, the GSCT appears to display a good test-retest reliability further strengthening the validity of the test