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Deep Learning architecture to assist with steering a powered wheelchair
This paper describes a novel Deep Learning architecture to assist with steering a powered wheelchair. A rule-based approach is utilized to train and test a Long Short Term Memory (LSTM) Neural Network. It is the first time a LSTM has been used for steering a powered wheelchair. A disabled driver uses a joystick to provide desired speed and direction, and the Neural Network provides a safe direction for the wheelchair. Results from the Neural Network are mixed with desired speed and direction to avoid obstacles. Inputs originate from a joystick and from three ultrasonic transducers attached to the chair. The resultant course is a blend of desired directions and directions that steer the chair to avoid collision. A rule-based approach is used to create a training and test set for the Neural Network system and applies deep learning to predict a safe route for a wheelchair. The user can over-ride the new system if necessary
Intelligent HMI and control for steering a powered wheelchair using a Raspberry Pi microcomputer
This paper presents a new technique for controlling powered wheelchairs. A Raspberry Pi microcomputer is used to assist in controlling direction. A Raspberry Pi is inserted between user input switches and powered wheelchair motors to create a more intelligent Human Machine Interface (HMI). An electronic circuit is created that consists of an ultrasonic sensor array and a set of control relays. The sensors provided information about obstacles surrounding the wheelchair. Python programming language was used to create a code that digitized the output from the user switches and assessed information provided by the ultrasonic sensor array. The code was loaded onto a Raspberry Pi and the Raspberry Pi controlled voltages supplied to the motors. Tests were conducted and results showed that the new system can successfully assist a wheelchair user in avoiding obstacles. The system can be used as an intelligent interface between any input device or sensor system and wheelchair motors
Management of compressed air to reduce energy consumption using intelligent systems
This research investigated the use of intelligent systems for reducing energy consumption in compressed air systems. An initial literature review has been completed and mathematical models that describe typical compressed air components (compressor, tank, piping network, etc.) were created. The investigations suggested that energy used or wasted in connection with compressed air was a valuable research area to attempt to save energy. The research progressed to investigating ways of minimising energy use for air compressors based on real-time conditions (including anticipated future requirements), using intelligent systems to monitor and make decisions
Task programming methodology for powered wheelchairs
The work described in this paper is directed towards applying task oriented methodologies to the creation of new types of powered wheelchairs. The new work has required the creation of a new type of task machine. In addition, new techniques to analyse situations and implement the results within a new user interface have been investigated. This paper describes task machinery in general and the stages required to create a task machine
Introducing time-delays to analyze driver reaction times when using a powered wheelchair
This paper investigates the introduction of time-delays into wheelchair driving. Two dissimilar ways in which wheelchair drivers interact are compared. Users were observed as they drove their wheelchairs with and without time-delays. Tests took place with a computer system and sensors which provided assistance and then without any assistance provided. As delays became longer then drivers found it more difficult to drive. If the wheelchair moved through a more complicated environment or if the time-delay was made longer, then driving was better if the computer and sensors assisted. Time delays were introduced between the motor controller and the wheelchair joystick. With shorter time-delays or in simpler environments then less assistance was needed from the computer system and sensors. In more complicated environments or if time-delays were longer, then more assistance was needed. That suggest varying sensor support could be helpful depending on the complexity of the environment or the difficulties being experienced by the drivers
TRPV4 receptor as a functional sensory molecule in bladder urothelium: Stretch‐independent, tissue‐specific actions and pathological implications
The newly recognized sensory role of bladder urothelium has generated intense interest in identifying its novel sensory molecules. Sensory receptor TRPV4 may serve such function. However, specific and physiologically relevant tissue actions of TRPV4, stretch-independent responses, and underlying mechanisms are unknown and its role in human conditions has not been examined. Here we showed TRPV4 expression in guinea-pig urothelium, suburothelium, and bladder smooth muscle, with urothelial predominance. Selective TRPV4 activation without stretch evoked significant ATP release-key urothelial sensory process, from live mucosa tissue, full-thickness bladder but not smooth muscle, and sustained muscle contractions. ATP release was mediated by Ca2+-dependent, pannexin/connexin-conductive pathway involving protein tyrosine kinase, but independent from vesicular transport and chloride channels. TRPV4 activation generated greater Ca2+ rise than purinergic activation in urothelial cells. There was intrinsic TRPV4 activity without exogeneous stimulus, causing ATP release. TRPV4 contributed to 50% stretch-induced ATP release. TRPV4 activation also triggered superoxide release. TRPV4 expression was increased with aging. Human bladder mucosa presented similarities to guinea pigs. Overactive bladders exhibited greater TRPV4-induced ATP release with age dependence. These data provide the first evidence in humans for the key functional role of TRPV4 in urothelium with specific mechanisms and identify TRPV4 up-regulation in aging and overactive bladders.
Keywords: ATP release; TRPV4 receptor; aging; overactive bladders; urothelium
The mediation role of public governance in the relationship between entrepreneurship and economic growth
Purpose – The purpose of this paper is to investigate the mediation role of public governance in the relationship between entrepreneurship and economic growth in the United Arab Emirates (UAE).
Design/methodology/approach – To achieve this aim, the study uses a 20-year time series analysis (1996–2015) and tests the effect of entrepreneurship on economic growth, through public governance, via a mediator model.
Findings – The study has determined that public governance buoys the positive effect that entrepreneurship activities exert on economic growth in the UAE. Based on this determination, the study posits a set of recommendations that focus on supporting entrepreneurship activities that play a significant role in economic growth.
Originality/value – The study adds to the literature on the impact of entrepreneurship on economies dependent on oil revenues vis-à-vis a public policy perspective. The study provides insights into the type of entrepreneurship that most efficaciously suits the Emirati social and cultural milieu in terms of fostering national economic growth. In addition, the study limns a vision of the role of public governance in creating an enabling environment that stimulates entrepreneurial activity and, in turn, increases economic growth in the Emirates
Increasing female participation on boards: Effects on sustainability reporting
Utilizing data on 2,116 stock-exchange-listed banks over a 10-year period (2007–2016), this study examines the relationship between board gender diversity and sustainable reporting. Findings from descriptive analysis show that
board diversity tends to be higher with banks endowed with low financial leverage and high assets. Cross-country analysis shows that Central America evinces the highest levels of board diversity among banks. In Europe, however,
repose the highest levels of environmental and social disclosure among banks. In contrast, the highest level of governance disclosure among banks obtains in Australia. A regression model partially corroborates the gender board diversity
as a causal factor of the corporate governance disclosure inasmuch as, when female board members account for 22–50% of the board, a positive significant effect on the level of ESG disclosure results. However, at levels above 50%, negative returns to scale manifest on ESG disclosure from female board participation. Given the effect on the latter on the former uncovered by this research, regulators ought to mandate quotas of female participation on bank boards to
engender sustainable increases in the level of ESG reporting on the part of banks