Architects in organizations are often tasked with aligning technical solutions withthe business strategy. However, as this involves various organizational departments using different tools, technologies, or modeling ...
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ISBN:
(纸本)9798400706226
Architects in organizations are often tasked with aligning technical solutions withthe business strategy. However, as this involves various organizational departments using different tools, technologies, or modeling languages, this requires continuous effort and carries the risk that business and IT departments become misaligned. this is especially the case for synchronizing enterprise architecture models with deployment models, as both describe the organization's IT landscape but are at different abstraction levels. To address this problem, we want to research how an automated approach can support architects in an organization in synchronizing the enterprise architecture models withthe deployment models. For this, we develop a method that uses model transformation techniques to transform deployment models into enterprise architecture models and vice versa. We expect that the automated approach will lead to more consistency between enterprise architecture models and deployment models and reduce the architects' effort to keep the models synchronized. We plan to evaluate the approach with a set of case studies and user studies.
Withthe increasing integration of communication and information technology in smart grid system, research on semi-physical co-simulation techniques for power grid and communication information system is becoming incr...
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Marine ship recognition has always been an important research field. the ships can be usually recognized by analyzing their attribute characteristics. However, in the actual process of recognition, many ship recogniti...
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the window function has a wide range of applications in filter design, signal truncation, information processing, etc., especially in the design of filter using the window function method, the different window functio...
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the active participation of contributors is key to the success of any open source software (OSS) projects. In the open source community, it can be found that some developers have participated together in multiple proj...
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this paper presents an end-to-end AC-D model for addressing the Vehicle Routing Problem with Time Windows (VRPTW) using reinforcement learning techniques. the proposed model employs a parameterized stochastic policy, ...
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To address the problem of image classification in which the intra-class variation and inter-class similarity are large due to external interference, thus increasing the difficulty of image classification, a lightweigh...
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Sleep, a physiological process essential for human health, is characterized by distinct stages. the accurate identification of these stages is paramount for diagnosing sleep disorders and improving sleep quality. Howe...
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ISBN:
(纸本)9798350358513;9798350358520
Sleep, a physiological process essential for human health, is characterized by distinct stages. the accurate identification of these stages is paramount for diagnosing sleep disorders and improving sleep quality. However, manual sleep staging is labor-intensive, which raises the need for automated sleep staging. Advances in machine learning, particularly deep learning, have shown promise in automating sleep stage classification, yet challenges persist in capturing the spatio-temporal dynamics of high-dimensional physiological data. Moreover, multi-source data from channels with different types are typically collected during the entire sleep process. It is essential to effectively utilize these data and capture the spatiotemporal correlations among different sources. therefore, we propose a novel spatio-temporal sleep staging method based on a JK-ViT framework. In the proposed method, a Graph Encoder based on the Jumping knowledge Network (JK-Net) structure is presented to capture the spatio-temporal dynamics. Leveraging the Vision-Transformer (ViT) framework, multisource data from channels of different types are fused and the attention layer captures the correlation between different sources. the effectiveness of method is validated using a private sleep PSG dataset, showcasing its potential to enhance the performance of sleep staging.
Issue tracking systems comprise data which are useful in evaluating or improving software development processes. Revealing and interpreting this information is a challenging problem which needs appropriate algorithms ...
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ISBN:
(纸本)9789897586477
Issue tracking systems comprise data which are useful in evaluating or improving software development processes. Revealing and interpreting this information is a challenging problem which needs appropriate algorithms and tools. For this purpose, we use text mining schemes adapted to the specificity of the software repository. they base on a detailed analysis of the used dictionaries which comprise Natural Language Words (NLW) and are enhanced with specialized entities in issue descriptions (e.g., emails, code snippets, technical names). they are defined with specially developed regular expressions. the pre-processed texts are submitted to original text mining algorithms (machine learning). this approach has been verified in commercial and open-source projects and showed possible development improvements.
In response to the challenges of low accuracy and instability in indoor-outdoor seamless positioning technology for scene recognition, this paper proposes a high-precision indoor-outdoor scene recognition method based...
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