Receipt from Fishkill Landing Machine Co.

https://digitalcommons.salve.edu/goelet-new-york/1221/thumbnail.jp

Receipt from Standard Underground Cable Co.

https://digitalcommons.salve.edu/goelet-new-york/1220/thumbnail.jp

Invoice from Standard Underground Cable Co.

https://digitalcommons.salve.edu/goelet-new-york/1212/thumbnail.jp

Receipt from W. H. Bowdlear & Co.

https://digitalcommons.salve.edu/goelet-new-york/1222/thumbnail.jp

Receipt from E. P. Gleason Manuf\u27g Co.

https://digitalcommons.salve.edu/goelet-new-york/1254/thumbnail.jp

Receipt from The Columbia Incandescent Lamp Co.

https://digitalcommons.salve.edu/goelet-new-york/1229/thumbnail.jp

Receipt from The American Electrical & Maintenance Co.

https://digitalcommons.salve.edu/goelet-new-york/1285/thumbnail.jp

Receipt from Consolidated Gas Company of New York

https://digitalcommons.salve.edu/goelet-new-york/1255/thumbnail.jp

Condensed report on the saving to society resulting from the use of the Comptometer

In accordance with your wishes we have made an investigation to determine the annual amount of saving to society which results from the use of the Comptometer, an instrument designed to make accurate and rapid arithmetical calculations under the manipulation of a skilled operator. While we recognize the many shades of meaning applicable to both of the words saving and society, and are well aware of the possibility of savings from which society may receive no benefit, we have so confined the use of these words in this connection that a saving to society shall he understood to mean the avoidance of spending or losing, or the prevention of waste, which make possible, at the same total cost as formerly, greater production, or broader distribution, or which reduce the cost of such activities, or in other ways benefit mankind as a whole

Automated analysis of retinal imaging using machine learning techniques for computer vision

There are almost two million people in the United Kingdom living with sight loss, including around 360,000 people who are registered as blind or partially sighted. Sight threatening diseases, such as diabetic retinopathy and age related macular degeneration have contributed to the 40% increase in outpatient attendances in the last decade but are amenable to early detection and monitoring. With early and appropriate intervention, blindness may be prevented in many cases. Ophthalmic imaging provides a way to diagnose and objectively assess the progression of a number of pathologies including neovascular (“wet”) age-related macular degeneration (wet AMD) and diabetic retinopathy. Two methods of imaging are commonly used: digital photographs of the fundus (the ‘back’ of the eye) and Optical Coherence Tomography (OCT, a modality that uses light waves in a similar way to how ultrasound uses sound waves). Changes in population demographics and expectations and the changing pattern of chronic diseases creates a rising demand for such imaging. Meanwhile, interrogation of such images is time consuming, costly, and prone to human error. The application of novel analysis methods may provide a solution to these challenges. This research will focus on applying novel machine learning algorithms to automatic analysis of both digital fundus photographs and OCT in Moorfields Eye Hospital NHS Foundation Trust patients. Through analysis of the images used in ophthalmology, along with relevant clinical and demographic information, Google DeepMind Health will investigate the feasibility of automated grading of digital fundus photographs and OCT and provide novel quantitative measures for specific disease features and for monitoring the therapeutic success