This is an overview of the combat system test and certification (CST&C) program as a subset of the total ship test program (TSTP) for active fleet surface ships. The paper will discuss how the T&C program meas...
This is an overview of the combat system test and certification (CST&C) program as a subset of the total ship test program (TSTP) for active fleet surface ships. The paper will discuss how the T&C program measures not only the suitability of repairs and modifications done during a ship's combat system industrial availability in a public or private yard period, but also the impact that successful program conduct has on the materiel effectiveness throughout a ship's operational cycle. The CST&C management organization and responsibilities, including NAVSEA's master ordnance repair program as well as combat system code 190's relationship to the CST&C program and the impact of pre- and post-industrial testing requirements on the actual conduct of industrial testing will be addressed.
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STERN, HMETZGER, RHoward K. Stern:is presently vice president of Robotic Vision Systems
Inc. He received a bachelor of electrical engineering degree from College of the City of New York in 1960. Mr. Stern joined Dynell Electronics Corporation in 1971 and became part of the Robotic Vision Systems
Inc. staff at the time of its spin-off from Dynell. He was program manager of the various three-dimensional sensing and replication systems constructed by Dynell and Robotic Vision Systems. As program manager his responsibilities encompassed technical administrative and operational areas. The first two portrait sculpture studio systems and the first three replication systems built by Robotic Vision Systems Inc. were designed manufactured and operated under his direction. Before joining Dynell
Mr. Stern was a senior engineer at Instrument Systems Corporation and chief engineer of the Special Products Division of General Instrument Corporation. Prior to these positions Mr. Stern was chief engineer of Edo Commercial Corporation. At General Instrument and Edo Commercial he was responsible for the design and manufacture of military and commercial avionics equipment. Mr. Stern is presently responsible for directing the systems design and development for all of the company's programs.Robert J. Metzger:is currently engineering group leader at Robotic Vision Systems
Inc. He graduated summa cum laude from the Cooper Union in 1972 with a bachelor of electrical engineering degree. Under sponsorship of a National Science Foundation graduate fellowship he graduated from the Massachusetts Institute of Technology in 1974 with the degrees of electrical engineer and master of science (electrical engineering). In 1979 Mr. Metzger graduated from Polytechnic Institute of New York with the degree of master of science (computer science). Since 1974
Mr. Metzger has been actively engaged in the design of systems and software for noncontact threedimensional optical measurement for both military and commercial applications. Of particular note are his c
Ship's propellers are currently measured by manual procedures using pitchometers, templates and gauges. This measurement process is extremely tedious, labor intensive and time consuming. In an effort to provide in...
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Ship's propellers are currently measured by manual procedures using pitchometers, templates and gauges. This measurement process is extremely tedious, labor intensive and time consuming. In an effort to provide increased accuracy, repeatability and cost effectiveness in propeller manufacture, an automated propeller optical measurement system (APOMS) has been built which rapidly and automatically scans an entire ship's propeller using a 3-D vision sensor. This equipment is integrated with a propeller robotic automated templating system (PRATS) and the propeller optical finishing system (PROFS) which robotically template and grind the propeller to its final shape, using the APOMS-derived data for control feedback. The optical scanning and the final shape are both controlled by CAD/CAM data files describing the desired propeller shape. An automated propeller balancing system is incorporated into the PROFS equipment. The APOMS/PRATS/PROFS equipment is expected to provide lower propeller manufacturing costs.
Question generation is an important task in natural language processing that involves generating questions from a given text. This paper proposes a novel approach for dynamic question generation using a context-aware ...
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Question generation is an important task in natural language processing that involves generating questions from a given text. This paper proposes a novel approach for dynamic question generation using a context-aware auto-encoded graph neural model. Our approach involves constructing a graph representation of the input text, where each node in the graph corresponds to a word or phrase in the text, and the edges represent the relationships between them. We then use an auto-encoder model to learn a compressed representation of the graph that captures the most important information in the input text. Finally, we use the compressed graph representation to generate questions by dynamically selecting nodes and edges based on their relevance to the context of the input text. We evaluate our approach on four benchmark datasets (SQuAD, Natural Questions, TriviaQA, and QuAC) and demonstrate that it outperforms existing state-of-the-art methods for dynamic question generation. In the experimentation, to evaluate the result four performance metrics are used i.e. BLEU, ROUGE, F1-Score, and Accuracy. The result of the proposed approach yields an accuracy of 92% on the SQuAD dataset, 89% with QuAC, and 84% with TriviaQA. while on the natural questions dataset, the model gives 79% accuracy. Our results suggest that the use of graph neural networks and auto-encoder models can significantly improve the accuracy and effectiveness of question generation in NLP. Further research in this area can lead to even more sophisticated models that can generate questions that are even more contextually relevant and natural-sounding.
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