Naval History and Heritage Command

Abstract The year 2022 will mark the centennial of the commissioning of the US Navy’s first aircraft carrier USS Langley. In late 1936, the ship was converted to become a seaplane tender and in 1939 is deployed to Manila. Following news reaching Admiral Hart and the Asiatic Fleet of the Japanese attack on Pearl Harbor, the arrival of Japanese bombers over Manila is imminent and the Langley is determined to be vulnerable to air attack. Departing Manila on December 9, Langley’s skipper Capt. Felix Stump served as the officer in tactical command of a convoy that also included the oilers Trinity and Pecos and is able to work his way through the archipelago, meeting up with the cruisers Houston and Boise which pick up the escort duties. Reaching Darwin before the end of the year, Stump turns over command to his executive officer Cdr. Robert McConnell to join the staff of the newly formed America British Dutch Australian combined command (ABDACOM) combined command under Vice Adm. William A. Glassford. Unfortunately, Langley will be lost on February 27, 1942, during a desperate attempt to transport Army P-40 pursuit planes to support Dutch efforts to defend Java.

The objective of this project is to create a new implementation of a deep learning model that uses digital elevation data to detect shipwrecks automatically and rapidly over a large geographic area. This work is intended to apply a new methodology to the field of underwater archaeology. Shipwrecks represent a major resource to understand maritime human activity over millennia, but underwater archaeology is expensive, misappropriated, and hazardous. An automated tool to rapidly detect and map shipwrecks can therefore be used to create more accurate maps of natural and archaeological features to aid management objectives, study patterns across the landscape, and find new features. Additionally, more comprehensive and accurate shipwreck maps can help to prioritize site selection and plan excavation. The model is based on open source topo-bathymetric data and shipwreck data for the United States available from NOAA. The model uses transfer learning to compensate for a relatively small sample size and addresses a recurring problem that associated work has had with false positives by training the model both on shipwrecks and background topography. Results of statistical analyses conducted—ANOVAs and box and whisker plots—indicate that there are substantial differences between the morphologic characteristics that define shipwrecks vs. background topography, supporting this approach to addressing false positives. The model uses a YOLOv3 architecture and produced an F1 score of 0.92 and a precision score of 0.90, indicating that the approach taken herein to address false positives was successful.

Astronomer and engineer of the first observatory on the Moon. Astronomer and engineer of the first observatory on the Moon.

Can an understanding of history foster innovation? Certainly many great innovators have said so. Here in their own words, via the oral history collection of the lEEE History Center, are some of the ways innovators have drawn upon history to assist the process of invention.

The use of the alpha angle to help the diagnosis of Femoral Acetabular Impingement (FAI) is common. However, there is currently no standard value available across an asymptomatic pre-arthritic population. We present the first large cohort of Computerised Tomography (CT) based alpha angles in patients with no history of hip pathology, including intra- and interobserver validation. We carried out a retrospective analysis of 73 consecutive individuals (146 hip joints) with ages ranging from 18 to 39 years. The age range 18-39 represents 82.4% of those currently serving in the UK Armed Forces. The cohort was drawn from those patients who had received a CT scan in the Lothian Region between 1 Jan 2011 and 31 Dec 2011 due to abdominal pathology. These patients had their electronic patient record checked to rule out any hip-related problems. The alpha angle of Nötzli was measured on the axial view bilaterally. The mean value for the 18-39 age range was found to be 51.89 degree for the left hip and 52.53 degree for the right. Femoral alpha angle is a reproducible measurement for assessing the femoral neck. However, there is wide variability in the alpha angle for patients, irrespective of the presence of symptoms. Our results would suggest that the alpha angle alone should not be used to diagnose FAI in service personnel, as even large angles may be normal.