Among various automation approaches, the pick and-place robotic arm stands out due to its versatility and potential for wide application in sorting, picking, and placing tasks. The robotic arm is equipped with advance...
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Early defect detection and prediction are essential in softwareengineering to reduce costs and improve quality. This study presents an AI-driven approach for fault detection and prediction employing ML techniques on ...
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In domains such as aerospace, automotive, and medical devices, high-quality software is key due to the critical nature of these applications and the low margin for failure. Ensuring the quality of software is essentia...
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ISBN:
(纸本)9783031783913;9783031783920
In domains such as aerospace, automotive, and medical devices, high-quality software is key due to the critical nature of these applications and the low margin for failure. Ensuring the quality of software is essential to prevent potentially catastrophic outcomes. In this paper, we present an approach to derive quality assurance plans from well-defined process models. Utilizing the GQM model, we derive quality requirements and metrics based on a process example, which we realize in the process management tool Stages. Based on the exemplary realization, we simulate 100 projects to provide data used in a recommendation system that enriches the process model such that quality assurance plans including the metrics of interest can be generated from the process model. Our findings show that, given sufficient data is available, context-specific quality assurance plans can be generated and which particular steps have to be taken to realize the overall concept in the studied tool.
This study addresses the prevalent issues with new energy vehicle batteries, including failure and other complications. It focuses on lithium-ion batteries in pure electric vehicles and proposes a diagnostic approach ...
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software and systems development projects in regulated domains need to provide evidence on their compliance to standards. Such standards often come as comprehensive documentation, i.e., documents, which need to be tai...
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ISBN:
(纸本)9783031783852;9783031783869
software and systems development projects in regulated domains need to provide evidence on their compliance to standards. Such standards often come as comprehensive documentation, i.e., documents, which need to be tailored to and interpreted for a particular project. Utilizing such documentations, it is desirable for companies working in regulated domains to provide tool support with regard to measurement systems that, eventually, help determine the product's quality and to support the compliance analysis. In this paper, we present an AI-supported approach to use a standard's documentation for generating artifact models. Such models are generated in a machine-readable format and, therefore, help companies create measurable items to be included in their metrication and measurement systems. Using selected ECSS standards from the European Space Agency as cases, we present our approach, the prompt engineering for the extraction of artifacts, and we illustrate the opportunities to generate comprehensive artifact models. Our findings show that, given sufficient information is available, the generation of artifact models is possible to a large degree with an average completeness of 99.64% and an average precision of 67.52% thus laying the foundation for building more efficient measurement systems.
Automatic item generation (AIG) can save time in the production of high-quality assessment items, but requires to create and maintain appropriate software tools that fit into a larger context in which the generated it...
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This study deals with the development of a new geoprocessing tool useful for wet gap crossing during military operations. At present, there is no software in the Czech Armed Forces that an engineer staff officer can c...
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ISBN:
(纸本)9783031713965;9783031713972
This study deals with the development of a new geoprocessing tool useful for wet gap crossing during military operations. At present, there is no software in the Czech Armed Forces that an engineer staff officer can comprehensively use to analyse wet gaps. The use of this geoprocessing tool will allow a faster and more efficient task analysis in the planning process. Members of the staffs of individual battalions of the 7th Mechanized Brigade, the 151st and 153rd Engineer Battalions and students of the University of Defence experimentally verified the usability of the geoprocessing tool. The advantage of own development is the possibility of updating the geoprocessing tool and admin options. The proposed geoprocessing tool can also be used as an interoperable element in the planning process of international task forces. The issue of wet gap crossing also confirms its importance from the conflict in Ukraine (e.g. of crossing the North Donetsk, Dnieper River) and also by the acquisition processes for newly acquired combat vehicles and support assets (military bridge vehicles, pontoon bridge set).
In the analysis of drone aerial images, object detection tasks are particularly challenging, especially in the presence of complex terrain structures, extreme differences in target sizes, suboptimal shooting angles, a...
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In the analysis of drone aerial images, object detection tasks are particularly challenging, especially in the presence of complex terrain structures, extreme differences in target sizes, suboptimal shooting angles, and varying lighting conditions, all of which exacerbate the difficulty of recognition. In recent years, the DETR model based on the Transformer architecture has eliminated traditional post-processing steps such as NMS(Non-Maximum Suppression), thereby simplifying the object detection process and improving detection accuracy, which has garnered widespread attention in the academic community. However, DETR has limitations such as slow training convergence, difficulty in query optimization, and high computational costs, which hinder its application in practical fields. To address these issues, this paper proposes a new object detection model called OptiDETR. This model first employs a more efficient hybrid encoder to replace the traditional Transformer encoder. The new encoder significantly enhances feature processing capabilities through internal and cross-scale feature interaction and fusion logic. Secondly, an IoU (Intersection over Union) aware query selection mechanism is introduced. This mechanism adds IoU constraints during the training phase to provide higher-quality initial object queries for the decoder, significantly improving the decoding performance. Additionally, the OptiDETR model integrates SW-Block into the DETR decoder, leveraging the advantages of Swin Transformer in global context modeling and feature representation to further enhance the performance and efficiency of object detection. To tackle the problem of small object detection, this study innovatively employs the SAHI algorithm for data augmentation. Through a series of experiments, It achieved a significant performance improvement of more than two percentage points in the mAP (mean Average Precision) metric compared to current mainstream object detection models. Furthermore, ther
Body Language decoding is an important aspect of understanding human emotions, intentions, and personality by interpreting non-verbal cu es. It helps to get insights into human behavior, mindset, and psychology of the...
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The COVID-19 pandemic has had an unprecedented and widespread impact on education, significantly affecting students worldwide. Although many studies have investigated this impact in the last 5 years, we still lack emp...
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