Using Augmented Reality For Studying Left Turn Maneuver At Un-signalized Intersection And Horizontal Visibility Blockage

Augmented reality AR is a promising paradigm that can provide users with real-time, high-quality visualization of a wide variety of information. In AR, virtual objects are added to the real-world view in a real time. Using the AR technology can offer a very realistic environment for driving enhancement as well as driving performance testing under different scenarios. This can be achieved by adding virtual objects (people, vehicles, hazards, and other objects) to the normal view while driving in a safe controlled environment. In this dissertation, the feasibility of adapting the AR technology into traffic engineering was investigated. Two AR systems; AR Vehicle ARV system and Offline AR Simulator OARSim system were built. The systems\u27 outcomes as well as the on-the-road driving under the AR were evaluated. In evaluating systems\u27 outcomes, systems were successfully able to duplicate real scenes and generate new scenes without any visual inconsistency. In evaluating on-the-road driving under the AR, drivers\u27 distance judgment, speed judgment, and level of comfort while driving were evaluated. In addition, our systems were used to conduct two traffic engineering studies; left-turn maneuver at un-signalized intersection, and horizontal visibility blockage when following a light truck vehicle. The results from this work supported the validity of our AR systems to be used as a surrogate to the field-testing for transportation research

Bridging the gap: Using design based activities to develop problem-solving skills in Qatari high school students

A substantial number of secondary school students are accepted into engineering schools without adequate exposure to key engineering based skills, such as analytical thinking, problem solving, critical thinking and design. Unfamiliarity with the practical skills needed in engineering leaves students unprepared, leading to poor academic performance and demotivating them about engineering. It is critical that students be able to apply learnt scientific concepts to solve real life problems. In this paper, we will present a set of design-based learning activities created to help develop the analytical thinking and problem solving skills of students in local Qatari secondary schools. We will discuss implementation details of these design-based learning activities along with results, comments from participating students and teachers as well as data analysis.qscienc

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

Effect of Nanoclay Particles on the Performance of High-Density Polyethylene-Modified Asphalt Concrete Mixture

Utilizing polymers for asphalt concrete (AC) mixture modification has many drawbacks that hinder its wide implementations for roadway construction. Recently, research on employing complementary materials, such as nanomaterials, to balance negative impacts of polymers while enhancing the AC mixture’s performance has received great attention. This study aimed to investigate the effect of incorporating nanoclay (NC) particles on the performance of a high-density polyethylene (HDPE)-modified AC mixture. A 60/70 asphalt binder was first modified with HDPE, and then NC particles were gradually added at a concentration of 1–4% by weight of the asphalt binder. The binders’ physical characteristics, storage stability, and chemical change were scrutinized. AC mixture performance, including pseudo-stiffness, moisture damage resistance, stripping susceptibility, and rutting tendency, was investigated. A statistical analysis on the experimental results was conducted using Kruskal–Wallis and Dunn tests. Test results showed that employing NC/HDPE significantly increased penetration index and thereby enhanced binder temperature sensitivity. Moreover, it prevented oxidation action and separation and, therefore, enhanced binder storage stability. Furthermore, incorporating NC amplified pseudo-stiffness and significantly improved resistance against moisture damage and stripping of HDPE-modified mixtures. Moreover, it improved both elastic (recoverable) and plastic (unrecoverable) deformations of mixtures. The most satisfactory results were attained when incorporating 3% of NC

Automatic vehicle classification system using range sensor

This paper presents an Automatic Vehicle Classification System based upon Laser Intensity Images obtained from range sensors (called AVCSLII). Current systems that utilize loop detectors, video cameras, and range sensors have deficiencies. The loop detectors have high failure rates due to pavement failures and poor maintenance. Video based systems and range sensors do not perform well in deteriorated atmospheric conditions (such as rain and fog). The developed generations of image based range sensors offer the promise of sensors that are less sensitive to deteriorated environmental conditions. AVCSLII system extracts features of laser intensity images, produced by laser sensory units. These features are used to train a Neural Network (NN). The AVCSLII system recalls its trained NN for classification of vehicles. This technique outperforms loop detectors, video cameras, and range data techniques in deteriorated environmental conditions. © 2005 IEEE

Laser Intensity Vehicle Classification System Based On Random Neural Network

This paper presents a Laser Intensity Vehicle Classification System (LIVCS) based upon imagery obtained from range sensors (called LIVCS). Current systems that utilize loop detectors, video cameras, and range sensors have deficiencies. The loop detectors have high failure rates due to pavement failures and poor maintenance. Video based systems and range sensors do not perform well in deteriorated atmospheric conditions (such as rain and fog). The developed generations of image based range sensors offer the promise of sensors that are less sensitive to deteriorated environmental conditions. LIVCS system extracts features of laser intensity images, produced by laser sensory units. These features are used to train a random neural network (RNN). The LIVCS system recalls its trained RNN for classification of vehicles. This technique outperforms loop detectors, video cameras, and range data techniques in deteriorated environmental conditions. Copyright 2005 ACM

Augmented Reality Vehicle System: Left-Turn Maneuver Study

Augmented Reality AR is a promising paradigm that can offer users with real-time, high-quality visualization of a wide variety of information. In AR, virtual objects are added to the real-world view in real time. The AR technology can offer a very realistic environment for enhancing drivers\u27 performance on the road and testing drivers\u27 ability to react to different road design and traffic operations scenarios. This can be achieved by adding virtual objects (people, vehicles, hazards, and other objects) to the normal view while driving an actual vehicle in a real environment. This paper explores a new Augmented Reality Vehicle ARV system and attempts to apply this new concept to a selected traffic engineering application namely the left-turn maneuver at two-way stop-controlled TWSC intersection. This TWSC intersection experiment, in addition to testing the feasibility of the application, tries to quantify the size of gaps accepted by different driver\u27s characteristics (age and gender). The ARV system can be installed in any vehicle where the driver can see the surrounding environment through a Head Mounted Display HMD and virtual objects are generated through a computer and added to the scene. These different environments are generated using a well defined set of scenarios. The results from this study supported the feasibility and validity of the proposed ARV system and they showed promise for this system to be used in the field-testing for the safety and operation aspects of transportation research. Results of the left-turn maneuver study revealed that participants accepted gaps in the range of 4.0-9.0. s. This finding implies that all gaps below 4. s are rejected and all gaps above 9. s are likely to be accepted. The mean value of the left-turn time was 4.67. s which is a little bit higher than reported values in the literature (4.0-4.3. s). Older drivers were found to select larger gaps to make left turns than younger drivers. The conservative driving attitude of older drivers indicates the potential presence of reduced driving ability of elderly. Drivers\u27 characteristics (age and gender) did not significantly affect the left-turn time. Based on the survey questions that were handed to participants, most participants indicated good level of comfort with none or small level of risk while driving the vehicle with the ARV system. None of the participants felt any kind of motion sickness and the participants\u27 answers indicated a good visibility and realism of the scene with overall good system fidelity. © 2011 Elsevier Ltd