An Augmented Reality Periscope for Submarines with Extended Visual Classification

Submarines are considered extremely strategic for any naval army due to their stealth capability. Periscopes are crucial sensors for these vessels, and emerging to the surface or periscope depth is required to identify visual contacts through this device. This maneuver has many procedures and usually has to be fast and agile to avoid exposure. This paper presents and implements a novel architecture for real submarine periscopes developed for future Brazilian naval fleet operations. Our system consists of a probe that is connected to the craft and carries a 360 camera. We project and take the images inside the vessel using traditional VR/XR devices. We also propose and implement an efficient computer vision-based MR technique to estimate and display detected vessels effectively and precisely. The vessel detection model is trained using synthetic images. So, we built and made available a dataset composed of 99,000 images. Finally, we also estimate distances of the classified elements, showing all the information in an AR-based interface. Although the probe is wired-connected, it allows for the vessel to stand in deep positions, reducing its exposure and introducing a new way for submarine maneuvers and operations. We validate our proposal through a user experience experiment using 19 experts in periscope operations.

Community noise assessment of urban air mobility vehicle operations using the FAA Aviation Environmental Design Tool

In contrast to most commercial air traffic today, vehicles serving the urban air mobility (UAM) market are anticipated to operate in communities close to the public at large. The approved model for assessing environmental impact of air traffic actions in the United States, the Federal Aviation Administration's Aviation Environmental Design Tool (AEDT), does not support analysis of such operations due to a combined lack of a UAM aircraft performance model and aircraft noise data. This paper discusses the initial development of a method to assess the acoustic impact of UAM fleet operations on the community using AEDT and demonstrates its use for representative UAM operations. In particular, methods were developed using fixed-point flight profiles and user-supplied noise data in a manner that avoids unwanted behavior in AEDT. A set of 32 routes in the Dallas-Ft. Worth area were assessed for single and multiple (fleet) operations for two concept vehicles.

Decision Making and Truck Operating Costs on Haulage Business in Lagos, Nigeria

Aim: To evaluates how managers take decisions on variable components of freight operation and its effects on truck operating costs in haulage business in Lagos, Nigeria. Study Design: The structure of this paper is a descriptive design. It identified a gap in knowledge and employed a structured questionnaire to obtain useful information that gives a clearer understanding of the subject in a new environment. The data collected was analysed using descriptive statistics. Place and Duration of Study: Haulage companies operating in Lagos, Nigeria between June and August 2019. Methodology: The population study is 2154 staff drawn from the eight purposively selected registered haulage companies in Lagos, Nigeria. A structured questionnaire was randomly administered on 337 personnel involved in freight operations. The questionnaire survey was conducted to obtain information on company’s expenses and policy decisions on truck operating components. Result: The decision to use new truck reduces fuel consumption and maintenance cost of haulage business. Furthermore, remunerating drivers in salary is cost effective, regular training of drivers improves their performance while high empty return trips leads to revenue loss. Business owners take decisions on huge financial investment while managers handled those that are directly related to daily fleet operations. Conclusion: The study concluded that decisions on components of freight operation increases truck operating cost of the haulage companies in the study area. The study therefore recommends policy actions that will enhance productivity of haulage companies through effective decisions.

​Investigating Knowledge Creation Processes Among The Royal Malaysian Navy (RMN) Fleet Personnel

This study was conducted to gauge the extent of knowledge creation within the Royal Malaysian Navy (RMN) fleet. It was due to rotational of personnel serving on board for their career progressions and personnel retired that may bring with them substantial amount of knowledge. Thus, quantitative study was conducted, taking into account of descriptive data analyzed by SPSS software with 234 respondents utilizing SECI model as the theoretical platform. Items analysis was conducted to gauge the extent. Apart from that, level and type of knowledge, mechanisms and venues for knowledge creation were identified. The results showed the extent of knowledge creation processes varied in every mode of SECI. Operational knowledge and knowledge from experiences are common within the fleet. Social media identified as the common mechanism utilized. Seminar, workshop and meeting were identified as the venues for most of the knowledge creation processes took place. Besides identifying the extent of knowledge creation processes, this study could be the platform for the fleet to identify suitable recommendation to create and capture more knowledge, to retain and to disseminate knowledge in order to improve fleet operations.

Costs and Benefits of Electrifying and Automating Bus Transit Fleets

Diesel-powered, human-driven buses currently dominate public transit options in most U.S. cities, yet they produce health, environmental, and cost concerns. Emerging technologies may improve fleet operations by cost-effectively reducing emissions. This study analyzes both battery-electric buses and self-driving (autonomous) buses from both cost and qualitative perspectives, using the Capital Metropolitan Transportation Authority’s bus fleet in Austin, Texas. The study predicts battery-electric buses, including the required charging infrastructure, will become lifecycle cost-competitive in or before the year 2030 at existing U.S. fuel prices ($2.00/gallon), with the specific year depending on the actual rate of cost decline and the diesel bus purchase prices. Rising diesel prices would result in immediate cost savings before reaching $3.30 per gallon. Self-driving buses will reduce or eliminate the need for human drivers, one of the highest current operating costs of transit agencies. Finally, this study develops adoption schedules for these technologies. Recognizing bus lifespans and driver contracts, and assuming battery-electric bus adoption beginning in year-2020, cumulative break-even (neglecting extrinsic benefits, such as respiratory health) occurs somewhere between 2030 and 2037 depending on the rate of battery cost decline and diesel-bus purchase prices. This range changes to 2028 if self-driving technology is available for simultaneous adoption on new electric bus purchases beginning in 2020. The results inform fleet operators and manufacturers of the budgetary implications of converting a bus fleet to electric power, and what cost parameters allow electric buses to provide budgetary benefits over their diesel counterparts.