Browse Topic: Education and training
In contemporary society, where Global Navigation Satellite Systems (GNSS) are utilised extensively, their inherent fragility gives rise to potential hazards with respect to the safety of ship navigation. In order to address this issue, the present study focuses on an ASM signal delay measurement system based on software defined radio peripherals. The system comprises two distinct components: a transmitting end and a receiving end. At the transmitting end, a signal generator, a first time-frequency synchronisation device, and a VHF transmitting antenna are employed to transmit ASM signals comprising dual Barker 13 code training sequences. At the receiving end, signals are received via software-defined radio equipment, a second time-frequency synchronisation device, a computing host, and a VHF receiving antenna. Utilising sliding correlation algorithms enables accurate time delay estimation. The present study leverages the high performance and low cost advantages of the universal
Recent advancements in energy efficient wireless communication protocols and low powered digital sensor technologies have led to the development of wireless sensor network (WSN) applications in diverse industries. These WSNs are generally designed using Bluetooth Low Energy (BLE), ZigBee and Wi-Fi communication protocol depending on the range and reliability requirements of the application. Designing these WSN applications also depends on the following factors. First, the environment under which devices operate varies with the industries and products they are employed in. Second, the energy availability for these devices is limited so higher signal strength for transmission and retransmission reduces the lifetime of these nodes significantly and finally, the size of networks is increasing hence scheduling and routing of messages becomes critical as well. These factors make simulation for these applications essential for evaluating the performance of WSNs before physical deployment of
Single motorcycle accidents are common in Nagano Prefecture where is mountainous areas in Japan. In a previous study, analysis of traffic accident statistics data suggested that the fatality and serious injury rates for uphill right curves and downhill left curves are high, however the true causes of these accidents remain unclear. In this study, a motorcycle simulator was used to evaluate the driving characteristics due to these road alignments. Evaluation courses based on combinations of uphill/downhill slopes and left/right curves were created, and experiments were conducted. The subjects of the study were expert riders and novice riders. The results showed that right curves are even more difficult to see near the entrance of the curve when accompanied by an uphill slope, making it easier to delay recognition and judgment of the curve. Expert riders recognized curves faster than novice riders. Additionally, expert riders take a large lean of the vehicle body, actively attempted to
This document establishes training guidelines applicable to fiber optic safety training, technical training and fiber awareness for individuals involved in the manufacturing, installation, support, integration and testing of fiber optic systems. Applicable personnel include: Managers Engineers Technicians Logisticians Trainers/Instructors Third Party Maintenance Agencies Quality Assurance Shipping Receiving Production Purchasing
This document establishes re-certification guidelines applicable to fiber optic fabricator technical training for individuals involved in the manufacturing, installation, support, integration and testing of fiber optic systems. Applicable personnel include: Managers Engineers Technicians Trainers/Instructors Third Party Maintenance Agencies Quality Assurance Production
This document establishes training guidelines applicable to fiber optic fabricator technical training for individuals involved in the manufacturing, installation, support, integration and testing of fiber optic systems. Applicable personnel include: Managers Engineers Technicians Trainers/Instructors Third Party Maintenance Agencies Quality Assurance Production
An important characteristic of battery electric vehicles (BEVs) is their noise signature. Besides tire and wind noise, noise from auxiliaries as pumps, the electric drive unit (EDU) is one of the major contributors. The dynamic and acoustic behavior of EDUs can be significantly affected by production tolerances. The effects that lead to these scatter bands must be understood to be able to control them better and thus guarantee a consistently high quality of the products and a silent and pleasant drive. The paper discusses a simulation driven approach to investigate production tolerances and their effect on the NVH behavior of the EDU, using high precision transient multi-body dynamic analysis. This approach considers the main effects, influences, and the interaction from elastic structures of electric motor and transmission with accurate gear contact models in a fully coupled way. It serves as virtual end of line test, applicable in all steps of a new EDU development, by increasing
The United States Marine Corps enlists the JCB 4CX backhoe loader as its latest recruit. JCB recently announced that it has secured a contract to provide 4CX backhoe loaders to the United States Marine Corps. According to JCB, the agreement includes not only machines but also attachments testing and hands-on operator training. “The 4CX is the direct result of more than 70 years of continuous improvement,” said Chris Giorgianni, vice president of government and defense for JCB North America. “It's built to perform in the most demanding environments, whether that's military engineering missions or high-pressure construction jobsites.”
Like those in many other industries, truck and off-highway vehicle manufacturers face the challenge of producing quality components and maintaining productive processes while also generating a better bottom line. Improving employee training, simplifying complex operations and implementing better workflows can all help generate efficiencies. While not a new concept, lightweighting - in this case, reducing the weight of parts through the substitution of traditional steel with high-strength, thinner steels - can also be a viable answer to a better vehicle. As a rule of thumb, when manufacturers double the strength of the material through lightweighting, it is possible to reduce the weight of the part by one-third. That weight reduction can then lower the cost per part for greater profitability per piece of equipment and greater annual savings.
The Gatik Arena platform integrates NVIDIA Cosmos models to create closed-loop, ultra-realistic digital environments that address real-world limitations. Gatik Arena is a next-generation simulation platform designed to accelerate the development and validation of autonomous vehicle (AV) systems. Gatik, which targets autonomous middle-mile logistics, built and fine-tuned Arena in-house to meet specific operational and technical needs. Unveiled in July 2025, the platform is said to produce photorealistic, structured and controllable synthetic data that addresses the limitations of traditional real-world data collection. Founded in 2017, Gatik plans to scale its freight-only, driverless operations in 2025, and the Arena platform is central to this endeavor. Gatik collaborated with NVIDIA to integrate its Cosmos world foundation models (WFMs), which enable the creation of ultra-high-fidelity, physics-informed digital environments for robust AV training and validation, said Norm Marks, VP
The use of modeling and simulation (M&S) to enable aggressive training, testing, analysis, and experimentation of capabilities has risen in recent years. An increase in M&S demand to enable Force Readiness necessitates the use of modular and reusable simulation software. To meet this need, the U.S. Army Combat Capabilities Development Command Ground Vehicle Systems Center (DEVCOM GVSC) has developed a modular simulation software framework called Project Great Lakes (ProjectGL). The software supports complex simulation requirements for multiple vehicles, terrains, sensors and other technologies, while using a common, internal framework to support extensive configuration. The paper presents the framework’s core design philosophy, architecture and common use cases. The paper concludes with a discussion on possible areas of framework expansion and development guidelines for partners interested in extending the framework.
The development of cyber-physical systems necessarily involves the expertise of an interdisciplinary team – not all of whom have deep embedded software knowledge. Graphical software development environments alleviate many of these challenges but in turn create concerns for their appropriateness in a rigorous software initiative. Their tool suites further enable the creation of physics models which can be coupled in the loop with the corresponding software component’s control law in an integrated test environment. Such a methodology addresses many of the challenges that arise in trying to create suitable test cases for physics-based problems. If the test developer ensures that test development in such a methodology observes software engineering’s design-for-change paradigm, the test harness can be reused from a virtualized environment to one using a hardware-in-the-loop simulator and/or production machinery. Concerns over the lack of model-based software engineering’s rigor can be
As unmanned vehicular networks become more prevalent in civilian and defense applications, the need for robust security solutions grows in parallel. While ROS 2 offers a flexible platform for robotic operations, its security model lacks the adaptability required for dynamic trust management and proactive threat mitigation. To address these shortcomings, we propose a novel framework that integrates containerized ROS 2 nodes with Kubernetes-based orchestration, a dynamic trust management subsystem, and integrability with simulators for real-time and protocol-flexible network simulation. By embedding trust management directly within each ROS 2 container and leveraging Kubernetes, we overcome ROS 2’s security limitations by enabling real-time monitoring and machine learning-driven anomaly detection (via an autoencoder trained on custom data), facilitating the isolation or removal of suspicious nodes. Additionally, Kubernetes policies allow seamless scaling and enforcement of trust-based
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