Glaucoma is caused by a pathological rise in the intraocular pressure, which results in a progressive loss of vision by a damage to retinal cells and the optical nerve head. Early detection of pressure-induced damage ...
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ISBN:
(数字)9781510614345
ISBN:
(纸本)9781510614345;9781510614338
Glaucoma is caused by a pathological rise in the intraocular pressure, which results in a progressive loss of vision by a damage to retinal cells and the optical nerve head. Early detection of pressure-induced damage is thus essential for the reduction of eye pressure and to prevent severe incapacity or blindness. Within the new European Project GALAHAD (Glaucoma Advanced, Label free High Resolution Automated OCT Diagnostics), we will develop a new low-cost and high-resolution OCT system for the early detection of glaucoma. The device is designed to improve diagnosis based on a new system of optical coherence tomography. Although OCT systems are at present available in ophthalmology centres, high-resolution devices are extremely expensive. The novelty of the new Galahad system is its super wideband light source to achieve high image resolution at a reasonable cost. Proof of concept experiments with cell and tissue Glaucoma test standards and animal models are planned for the test of the new optical components and new algorithms performance for the identification of Glaucoma associated cell and tissue structures. The intense training of the software systems with various samples should result in a increased sensitivity and specificity of the OCT software system.
Intermodal (IM) trains are typically the fastest freight trains operated in North America. The aerodynamic characteristics of many of these trains are often relatively poor resulting in high fuel consumption. However,...
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Intermodal (IM) trains are typically the fastest freight trains operated in North America. The aerodynamic characteristics of many of these trains are often relatively poor resulting in high fuel consumption. However, considerable variation in fuel efficiency is possible depending on how the loads are placed on railcars in the train. Consequently, substantial potential fuel savings are possible if more attention is paid to the loading configuration of trains. A wayside machine vision (MV) system was developed to automatically scan passing IM trains and assess their aerodynamic efficiency. MV algorithms are used to analyse these images, detect and measure gaps between loads. In order to make use of the data, a scoring system was developed based on two attributes - the aerodynamic coefficient and slot efficiency. The aerodynamic coefficient is calculated using the Aerodynamic Subroutine of the train energy model. Slot efficiency represents the difference between the actual and ideal loading configuration given the particular set of railcars in the train. This system can provide IM terminal managers feedback on loading performance for trains and be integrated into the software support systems used for loading assignment.
Robotic systems have a tremendous influence on real-world applications as well as the actions and decisions of humans. It is one of the key driving forces towards advancements in the field of technology. With an everl...
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Robotic systems have a tremendous influence on real-world applications as well as the actions and decisions of humans. It is one of the key driving forces towards advancements in the field of technology. With an everlasting desire to master this, humans have made one major compromise: unmonitored depletion of Earth's invaluable resources and uncontrolled accumulation of waste. Furthermore, this so-called progress towards a technologically advanced world has paved the way to create a complex environment that poses several risks to human health. One such risk is caused due to the stagnation of contaminated water which serves as a breeding ground for insects such as mosquitoes and houseflies and causes a plethora of diseases. As a result, mosquito-borne diseases are on the rise in countries such as India, Sri Lanka, Thailand, Cambodia, and Brazil. These diseases are detrimental to the health of the country's population. Dengue, a mosquito-borne disease, is the fastest spreading and most critical. Therefore, the challenge at hand is to develop a robotic system which is efficient in locating "dengue hot-spots" while being complementary to the environment, i.e. fewer emissions, zero greenhouse gases. Current methods of dealing with this challenge require a lot of resources and do not yield expected results. Our design methodology, referred to as EMBED-X, offers a systematic approach that is backed up by protocols which support intelligent and pro-active monitoring of the environment. The robotic system is to be semi-autonomous and remotely connected to a control station for constant data analysis. The aim is to identify objects such as coconut shells, rubber tires, and plastic containers that have the potential for retaining stagnant water. To identify these objects, image analysis algorithms are applied on the images captured by the autonomous robot during the surveillance of a given area. Our imageanalysis algorithm has an accuracy of 66.7% and is continually being imp
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