software is an integral piece of all modern spacecraft design. In the present day, it supports mission- critical operations such as rendezvous and docking, autonomous navigation of rovers, mid-course adjustments, atti...
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software is an integral piece of all modern spacecraft design. In the present day, it supports mission- critical operations such as rendezvous and docking, autonomous navigation of rovers, mid-course adjustments, attitude control, re-entry and managing of spacecraft's systems. The first manned spacecraft - Mercury, was not equipped with a computer. In fact, NASA spent its first fifteen years running Earth- orbital and deep space missions without an on-board general-purpose computer. As the natural evolution of more complex missions came about, technology rapidly advanced in parallel, serving as the supporting force behind the enablement of more sophisticated onboard computers. This progression allowed for enhanced capabilities, which has made possible for spacecraft to be more intelligent, increasing the value of the software component. Examples are reflected in the ever-growing functionality and autonomy of spacecraft, as well as the volume of mission data that is collected and pre-processed in-orbit. Expansion in intelligence is the result of the software's ability to change the functions of the computer in which it resides, and by extension, the hardware it controls. As missions constantly transform to best fit their desired result, using software to adjust for the changes is much more cost-effective than replacing or even altering the hardware, which in some cases is not even an option. software also provides a means to recover from various malfunctions, and compensate for hardware defects and failures - potentially extending mission life. This paper explores the importance and role of software in space systems, focusing on a new software enhancement, currently in development, to automate, and later add artificial intelligence to the Mobile Servicing System on-board the International Space Station. With deep space exploration and the newly planned Lunar Gateway, our next generation space robotics will have to operate without human intervention, using artificial
During the last academic year, the Electrical, Computer, software, and systemsengineering Department at Embry-Riddle Aeronautical University started an innovative effort to integrate a series of graduate systems engi...
Unified Modeling Language (UML) is a versatile tool for specifying, visualizing, and documenting softwaresystems through diagrams. In the early stages of development, addressing design issues is critical to improving...
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Background: In this Innovative Practice Work in Progress, we present our initial efforts to integrate formal methods, with a focus on model-checking specifications written in Temporal Logic of Actions (TLA+), into com...
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ISBN:
(纸本)9798350351507
Background: In this Innovative Practice Work in Progress, we present our initial efforts to integrate formal methods, with a focus on model-checking specifications written in Temporal Logic of Actions (TLA+), into computer science education, targeting undergraduate juniors/seniors and graduate students. Many safety-critical systems and services crucially depend on correct and reliable behavior. Formal methods can play a key role in ensuring correct and safe system behavior, yet remain underutilized in educational and industry contexts. Aims: We aim to (1) qualitatively assess the state of formal methods in computer science programs, (2) construct level-appropriate examples that could be included midway into one's undergraduate studies, (3) demonstrate how to address successive 'failuresy' through progressively stringent safety and liveness requirements, and (4) establish an ongoing framework for assessing interest and relevance among students. Methods: We detail our pedagogical strategy for embedding TLA+ into an intermediate course on formal methods at our institution. After starting with a refresher on mathematical logic, students specify the rules of simple puzzles in TLA+ and use its included model checker (known as TLC) to find a solution. We gradually escalate to more complex, dynamic, event-driven systems, such as the control logic of a microwave oven, where students will study safety and liveness requirements. We subsequently discuss explicit concurrency, along with thread safety and deadlock avoidance, by modeling bounded counters and buffers. Results: Our initial findings suggest that through careful curricular design and choice of examples and tools, it is possible to inspire and cultivate a new generation of software engineers proficient in formal methods. Conclusions: Our initial efforts suggest that 84% of our students had a positive experience in our formal methods course. Our future plans include a longitudinal analysis within our own institution and
Applications such as autonomous vehicles and medical screening use deep learning models to localize and identify hundreds of objects in a single *** the past,it has been shown how an attacker can fool these models by ...
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Applications such as autonomous vehicles and medical screening use deep learning models to localize and identify hundreds of objects in a single *** the past,it has been shown how an attacker can fool these models by placing an adversarial patch within a ***,these patches must be placed in the target location and do not explicitly alter the semantics elsewhere in the *** this paper,we introduce a new type of adversarial patch which alters a model’s perception of an image’s *** patches can be placed anywhere within an image to change the classification or semantics of locations far from the *** call this new class of adversarial examples‘remote adversarial patches’(RAP).We implement our own RAP called IPatch and perform an in-depth analysis on without pixel clipping on image segmentation RAP attacks using five state-of-the-art architectures with eight different encoders on the CamVid street view ***,we demonstrate that the attack can be extended to object recognition models with preliminary results on the popular YOLOv3 *** found that the patch can change the classification of a remote target region with a success rate of up to 93%on average.
As a pivotal enabler of intelligent transportation system(ITS), Internet of vehicles(Io V) has aroused extensive attention from academia and industry. The exponential growth of computation-intensive, latency-sensitive...
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As a pivotal enabler of intelligent transportation system(ITS), Internet of vehicles(Io V) has aroused extensive attention from academia and industry. The exponential growth of computation-intensive, latency-sensitive,and privacy-aware vehicular applications in Io V result in the transformation from cloud computing to edge computing,which enables tasks to be offloaded to edge nodes(ENs) closer to vehicles for efficient execution. In ITS environment,however, due to dynamic and stochastic computation offloading requests, it is challenging to efficiently orchestrate offloading decisions for application requirements. How to accomplish complex computation offloading of vehicles while ensuring data privacy remains challenging. In this paper, we propose an intelligent computation offloading with privacy protection scheme, named COPP. In particular, an Advanced Encryption Standard-based encryption method is utilized to implement privacy protection. Furthermore, an online offloading scheme is proposed to find optimal offloading policies. Finally, experimental results demonstrate that COPP significantly outperforms benchmark schemes in the performance of both delay and energy consumption.
Cars have significantly been transformed to the point of autonomously driving in complex situations by sensing their surroundings and inferring insights based on sensor inputs. Even though smart cars can process the v...
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Increased sensing and computing capabilities in cars are crucial for advanced traffic and driving automation. However, novel data delivery, testing, and machine learning pipelines are still needed to harness the full ...
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Recent advances in deep learning have led to the widespread use of convolutional neural networks (CNNs) and recurrent neural networks (RNNs) across various fields. For aircraft attitude estimation, CNNs can effectivel...
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The documentation landscape for nursing care data in Germany is predominantly heterogeneous and unstructured. Therefore, insightful methods such as Artificial Intelligence (AI) are difficult to implement. We propose a...
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