Context aware ontology‐based hybrid intelligent framework for vehicle driver categorization

In public vehicles, one of the major concerns is driver's level of expertise for its direct proportionality to safety of passengers. Hence, before a driver is subjected to certain type of vehicle, he should be thoroughly evaluated and categorized with respect to certain parameters instead of only one‐time metric of having driving license. These aspects may be driver's expertise, vigilance, aptitude, experience years, cognition, driving style, formal education, terrain, region, minor violations, major accidents, and age group. The purpose of this categorization is to ascertain suitability of a driver for certain vehicle type(s) to ensure passengers' safety. Currently, no driver categorization technique fully comprehends the implicit as well as explicit characteristics of drivers dynamically. In this paper, machine learning–based dynamic and adaptive technique named D‐CHAITs (driver categorization through hybrid of artificial intelligence techniques) is proposed for driver categorization with an objective focus on driver's attributes modeled in DriverOntology. A supervised mode of learning has been employed on a labeled dataset, having diverse profiles of drivers with attributes pertinent to drivers' perspectives of demographics, behaviors, expertise, and inclinations. A comparative analysis of D‐CHAIT with three other machine learning techniques (fuzzy logic, case‐based reasoning, and artificial neural networks) is also presented. The efficacy of all techniques was empirically measured while categorizing the drivers based on their profiles through metrics of accuracy, precision, recall, F‐measure performance, and associated costs. These empirical quantifications assert D‐CHAIT as a better technique than contemporary ones. The novelty of proposed technique is signified through preprocessing of feature attributes, quality of data, training of machine learning model on more relevant data, and adaptivity This is the peer reviewed version of the following article: Context aware ontology‐based hybrid intelligent framework for vehicle driver categorization, which has been published in final form at https://doi.org/10.1002/ett.3729. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions

Ontology Evolution for Personalized and Adaptive Activity Recognition

Ontology-based knowledge driven Activity Recognition (AR) models play a vital role in realm of Internet of Things (IoTs). However, these models suffer the shortcomings of static nature, inability of self-evolution and lack of adaptivity. Also, AR models cannot be made comprehensive enough to cater all the activities and smart home inhabitants may not be restricted to only those activities contained in AR model. So, AR models may not rightly recognize or infer new activities. In this paper, a framework has been proposed for dynamically capturing the new knowledge from activity patterns to evolve behavioural changes in AR model (i.e. ontology based model). This ontology based framework adapts by learning the specialized and extended activities from existing user-performed activity patterns. Moreover, it can identify new activity patterns previously unknown in AR model, adapt the new properties in existing activity models and enrich ontology model by capturing change representation to enrich ontology model. The proposed framework has been evaluated comprehensively over the metrics of accuracy, statistical heuristics and Kappa Coefficient. A well-known dataset named DAMSH has been used for having an empirical insight to the effectiveness of proposed framework that shows a significant level of accuracy for AR models This paper is a postprint of a paper submitted to and accepted for publication in IET Wireless Sensor Systems and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at the IET Digital Librar

Optical scattering from graphene foam for oil imaging/sensing

This work studied a new way of sensing oil leaks using graphene foam through an optical imaging and light scattering method.</p

Patient-Reported Outcomes (PROs) in NRG Oncology RTOG 1010: Phase III Trial Evaluating the Addition of Trastuzumab to Trimodality Treatment of HER2 Overexpressing (HER2+) Esophageal Adenocarcinoma (EAC)

Purpose/Objective(s): NRG/RTOG 1010 evaluated the benefit of trastuzumab for patients (pts) with HER2+ localized EAC receiving trimodality therapy. Adding trastuzumab did not improve disease-free (primary endpoint) or overall survival, nor treatment toxicity (Lancet Oncology 2022). The primary PRO objective was improvement (impr) in the FACT-Esophageal Cancer Subscale (ECS) score with trastuzumab at restaging prior to surgery. A secondary objective was to assess if impr in ECS score is associated with pathologic complete response (pCR). Materials/Methods: Pts with HER2+ EAC (T1N1-2; T2-3N0-2) were stratified by presence of adenopathy & randomized 1:1 to weekly paclitaxel, carboplatin with 50.4 Gy radiation (CRT) followed by surgery ± trastuzumab (CRT+T), 4mg/kg week 1, 2mg/kg/weekly x 5 during CRT, 6 mg/kg x1 prior to surgery, and then 6mg/kg every 3 weeks (wks) x 13. The ECS, v4, was done at baseline, 6-8 wks post-CRT and at 1 & 2 years. Impr in ECS and its Swallowing Index (SI) & Eating Index (EI) were defined as increases of 5, 2 & 2 points, respectively, from baseline. PRO sample size provided ≥ 80% power with 1-sided 0.05 alpha & a chi-squared test to determine if the proportion of pts categorized as improved at 6-8 wks is ≥ 25% higher for the CRT+T arm. Correlation between pCR & impr in ECS score was evaluated via chi-squared test. Results: From 2010-2015, 203 HER2+ pts were randomized; 194 eligible. Of 171 PRO consenting pts, the ECS was completed by 162 (95%) at baseline, 108 (64%) 6-8 wks, 82 (49%) 1 year & 55 (33%) at 2 years. The main reason for FACT-E noncompliance was pt death. Patient & tumor characteristics were similar between arms. Median age was 63 years; 86% male; 96% white; 65% Zubrod 0, 80% cT3 & 71% cN1-2 (AJCC 7th ed). For ECS scores at 6-8 wks, the mean change (Δ) was higher (better) from baseline at 4.6 (95% CI: 1.3, 7.8) for the CRT+T arm vs 0.9 (95% CI: -2.7, 4.6) for the CRT arm; the proportion of pts with an impr in 6-8 wks ECS was higher on the CRT+T arm (46% vs 38% on the CRT arm) although not significantly different (p=0.39). Table 1 shows ECS, SI & EI scores for all timepoints. At 6-8 wks, 30% with a pCR had an impr in ECS vs 45% of nonpCR pts (p=0.18). There were no significant correlations between pCR and ECS, SI & EI impr at any time points. Conclusion: The addition of trastuzumab to trimodality therapy for localized HER2+ EAC did not significantly improve survival or PROs. ECS score improvement following therapy was not associated with a pCR. The higher proportion of pts with improved ECS at 6-8 weeks and 2 years in the CRT+T arm is interesting and suggests that HER2 may still be an important target to explore

Fabry disease: recent advances in pathology, diagnosis, treatment and monitoring

<p>Abstract</p> <p>Background</p> <p>In Fabry disease (α-galactosidase A deficiency) accumulation of Globotriaosylceramide (Gb3) leads to progressive organ failure and premature death. The introduction of enzyme replacement therapy (ERT) was the beginning of a new era in this disorder, and has prompted a broad range of research activities. This review aims to summarize recent developments and progress with high impact for Fabry disease.</p> <p>Methods</p> <p>A Pubmed analysis was performed using the search terms "Fabry disease", "Anderson-Fabry disease", "alpha-galactosidase A" and "Gb3". Of the given publications by 31st January 2009 only original articles recently published in peer reviewed journals were included for this review. Case reports were included only when they comprised a new aspect. In addition we included relevant conference abstracts when the results had not already been published as original articles.</p> <p>Results</p> <p>Apart from Gb3-accumulation cellular and organ specific damages may be related also to inflammatory and immunological consequences. It will be interesting whether this may lead to new therapeutic strategies in the treatment of Fabry disease. Since newborn screening is still difficult in Fabry disease, detection of patients in populations at risk is of great importance. Undiagnosed patients with Fabry disease may still be found in cohorts of subjects with renal diseases, cardiomyopathy and TIA or stroke. Efforts should be undertaken to identify these individuals and initialise ERT in order to hault disease progression. It has also been demonstrated that Gb3-accumulation leads to pre-clinical damages and it is believed that early treatment may be the only possibility so far to prevent irreversible organ damage.</p