Dental and Dental Hygiene Students’ Career Choice Motivations in 2009–17: A Mixed Methods Approach

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153580/1/jddjde018079.pd

Demonstration of silicon-on-insulator mid-infrared spectrometers operating at 3.8µm

The design and characterization of silicon-on-insulator mid- infrared spectrometers operating at 3.8µm is reported. The devices are fabricated on 200mm SOI wafers in a CMOS pilot line. Both arrayed waveguide grating structures and planar concave grating structures were designed and tested. Low insertion loss (1.5-2.5dB) and good crosstalk characteristics (15-20dB) are demonstrated, together with waveguide propagation losses in the range of 3 to 6dB/cm

Challenges in Collaborative HRI for Remote Robot Teams

Collaboration between human supervisors and remote teams of robots is highly challenging, particularly in high-stakes, distant, hazardous locations, such as off-shore energy platforms. In order for these teams of robots to truly be beneficial, they need to be trusted to operate autonomously, performing tasks such as inspection and emergency response, thus reducing the number of personnel placed in harm's way. As remote robots are generally trusted less than robots in close-proximity, we present a solution to instil trust in the operator through a `mediator robot' that can exhibit social skills, alongside sophisticated visualisation techniques. In this position paper, we present general challenges and then take a closer look at one challenge in particular, discussing an initial study, which investigates the relationship between the level of control the supervisor hands over to the mediator robot and how this affects their trust. We show that the supervisor is more likely to have higher trust overall if their initial experience involves handing over control of the emergency situation to the robotic assistant. We discuss this result, here, as well as other challenges and interaction techniques for human-robot collaboration.Comment: 9 pages. Peer reviewed position paper accepted in the CHI 2019 Workshop: The Challenges of Working on Social Robots that Collaborate with People (SIRCHI2019), ACM CHI Conference on Human Factors in Computing Systems, May 2019, Glasgow, U

Organic farming: Present status, scope and prospects in northern India

Organic agriculture has emerged as an important priority area globally in view of the growing consciousness for safe and healthy food, long term sustainability and environmental concerns despite being contentious in history. Green revolution although paved way for developing countries in self-sufficiency of food but sustaining production against the limited natural resource base demands has shifted steadily from “resource degrading” chemical agriculture to “resource protective” organic agriculture. The essential concept remains the same, i.e., to go back to the arms of nature and take up organic farming to restore the loss. Organic farming emphasizes on rotating crops, managing pests, diversifying crops and livestock and improving the soil. The rainfed areas particularly north-eastern regions where least or no utilization of chemical inputs due to poor resources provides considerable opportunity for promotion of organic farming thereby reflecting its vast but unexplored scope. However, significant barriers like yield reduction, soil fertility enhancement, integration of livestock, marketing and policy etc., arise at both macroscopic and microscopic levels; making practically impossible the complete adoption of ‘pure organic farming’; rather some specific area can be diverted to organic farming and thus a blend of organic and other innovative farming systems is needed. Adoption of Integrated Green Revolution Farming can be possible to a large extent, where the basic trends of green revolution are retained with greater efficiency and closer compatibility to the environment. This review paper attempts to present the recent global and regional scenario of organic farming particularly highlighting the scope, prospects and constraints in the northern areas

A framework to estimate cognitive load using physiological data

Cognitive load has been widely studied to help understand human performance. It is desirable to monitor user cognitive load in applications such as automation, robotics, and aerospace to achieve operational safety and to improve user experience. This can allow efficient workload management and can help to avoid or to reduce human error. However, tracking cognitive load in real time with high accuracy remains a challenge. Hence, we propose a framework to detect cognitive load by non-intrusively measuring physiological data from the eyes and heart. We exemplify and evaluate the framework where participants engage in a task that induces different levels of cognitive load. The framework uses a set of classifiers to accurately predict low, medium and high levels of cognitive load. The classifiers achieve high predictive accuracy. In particular, Random Forest and Naive Bayes performed best with accuracies of 91.66% and 85.83% respectively. Furthermore, we found that, while mean pupil diameter change for both right and left eye were the most prominent features, blinking rate also made a moderately important contribution to this highly accurate prediction of low, medium and high cognitive load. The existing results on accuracy considerably outperform prior approaches and demonstrate the applicability of our framework to detect cognitive load

Hydrogen Production Using TiO2-Based Photocatalysts: A Comprehensive Review

Titanium dioxide (TiO2) is one of the most widely used photocatalysts due to its physical and chemical properties. In this study, hydrogen energy production using TiO2- and titanate-based photocatalysts is discussed along with the pros and cons. The mechanism of the photocatalysis has been elaborated to pinpoint the photocatalyst for better performance. The chief characteristics and limitations of the TiO2 photocatalysts have been assessed. Further, TiO2-based photocatalysts modified with a transition metal, transition metal oxide, noble metal, graphitic carbon nitride, graphene, etc. have been reviewed. This study will provide a basic understanding to beginners and detailed knowledge to experts in the field to optimize the TiO2-based photocatalysts for hydrogen production