Forests are critical to the ecological balance of the earth. However, natural disasters and manmade damages are posing a severe threat to forest resources, calling for effective means of forest management and protection (M&P). Therefore, this paper designs and applies an intelligent patrol algorithm for forest M&P based on cutting-edge techniques like the global positioning system (GPS). Firstly, the information of forest road and the forest road network were obtained with the aid of the GPS. Next, the Dijkstra's algorithm was adopted to identify the shortest patrol path for the M&P personnel and realize the intelligent patrol algorithm, in the light of the key points in forest M&P and the responsible areas of the M&P personnel. Together, the forest road network, M&P route planning and intelligent patrol form an effective framework for high-quality forest M&P. The research results shed new light on the protection of forest resources.

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Students at the Rowan University department of Mechanical Engineering have been assigned a long-term, large-scale design/build project in order to study the effects of integrating the curriculum on subject matter retention and design efficacy. The project, a bench-scale hybrid electric powertrain system, is designed, analyzed and fabricated by students in six modules, starting in their sophomore year and culminating in their final semester as seniors. This complex project has been selected in order to integrate the core mechanical engineering courses: Mechanical Design, Thermodynamics, System Dynamics and Control, and Fluid Mechanics. A bench-scale hybrid-electric vehicle powertrain has sufficient complexity to involve all Mechanical Engineering disciplines and the simplicity to be built by students over the course of five semesters. The research is designed to test two hypotheses:1. A long-term design project that integrates knowledge from multiple courses strengthens student knowledge retention. 2. A large-scale design project requiring tools from many courses improves student problem-solving and design skills.By integrating five semesters of the mechanical engineering curriculum into a cohesive whole, this project has the potential to transform the way undergraduate education is delivered. Before and after testing is being conducted to assess: a) Change in retention between courses and b) Change in student problem-solving and design skills.The centerpiece of the hybrid powertrain is the planetary gearset, which combines power from the air engine and electric motor to produce the desired output speed at the wheels. During the fall semester of their Junior year, the students design and fabricate a small planetary gearset, and conduct tests to assess its performance. The planetary gearset project is conducted in Machine Design, a core mechanical engineering course. This paper describes the planetary gearset assignment only -a description of the full hybrid powertrain project is given the papers listed in the References. Based on student feedback, an overwhelming majority of the students felt that the "hands on" project was valuable in the Machine Design course and enjoyed working on the project.Page 26.450.2

Purpose Automated driving systems (ADSs) are being developed to avoid human error and improve driving safety. However, limited focus has been given to the fallback behavior of automated vehicles, which act as a fail-safe mechanism to deal with safety issues resulting from sensor failure. Therefore, this study aims to establish a fallback control approach aimed at driving an automated vehicle to a safe parking lane under perceptive sensor malfunction. Design/methodology/approach Owing to an undetected area resulting from a front sensor malfunction, the proposed ADS first creates virtual vehicles to replace existing vehicles in the undetected area. Afterward, the virtual vehicles are assumed to perform the most hazardous driving behavior toward the host vehicle; an adaptive model predictive control algorithm is then presented to optimize the control task during the fallback procedure, avoiding potential collisions with surrounding vehicles. This fallback approach was tested in typical cases related to car-following and lane changes. Findings It is confirmed that the host vehicle avoid collision with the surrounding vehicles during the fallback procedure, revealing that the proposed method is effective for the test scenarios. Originality/value This study presents a model for the path-planning problem regarding an automated vehicle under perceptive sensor failure, and it proposes an original path-planning approach based on virtual vehicle scheme to improve the safety of an automated vehicle during a fallback procedure. This proposal gives a different view on the fallback safety problem from the normal strategy, in which the mode is switched to manual if a driver is available or the vehicle is instantly stopped.

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