Universities are increasingly integrating real-world projects into softwareengineering curricula to prepare students for careers involving complex concepts like Microservices Architecture (MSA). Students frequently s...
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The proceedings contain 71 papers. The topics discussed include: multi-class failure prediction for distributed systems based on KPI data and feature selection;accelerating high-precision vulnerability detection in c ...
ISBN:
(纸本)9798350306378
The proceedings contain 71 papers. The topics discussed include: multi-class failure prediction for distributed systems based on KPI data and feature selection;accelerating high-precision vulnerability detection in c programs with parallel graph summarization;PointStack: a point cloud processing network with enhanced global feature aggregation;improving visual speech recognition for small-scale datasets via speaker embedding;GNN and encoder integrated model for distributed solar and wind power forecasting;automatic detection method for software requirements text with language processing model;MAFF: a novel MobileNetV3 attention feature fusion network for automatic vehicle classification;and interval-valued Z-number aggregation operators and its application in airbus type selection problem.
Deep learning (DL) is assisting academicians and medical professionals in uncovering latent opportunities in data and enhancing the healthcare industry. The edge computing applications like smart healthcare systems wh...
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Deep learning (DL) is assisting academicians and medical professionals in uncovering latent opportunities in data and enhancing the healthcare industry. The edge computing applications like smart healthcare systems where accurate decision-making is required for fast medical treatment. DL in healthcare allows clinicians to correctly analyze any ailment and treat it, resulting in improved medical decisions. We present a unique DL model for the autonomous healthcare edge computing application in this paper. Computer Aided Diagnosis (CAD) is an essential requirement of healthcare edge computing where the patient's medical data is used for fast and accurate disease prediction. Propose the DL-based CAD model for automatic disease classification from the input medical images. The model consists of pre-processing, DL-based feature engineering, and classification. Input medical image is first pre-processed for quality improvement and then automatic features are extracted using the pre-trained DL models (ResNet50 and Densenet201). The pre-trained models are improved by performing the feature scaling followed by a separate classification phase. The proposed CAD model is experimentally evaluated using the medical images dataset. The results reveal the efficiency of the proposed model compared to underlying solutions.
The design and analysis of security in distributed computingsystems raises numerous questions on the tools available for modeling and verification. Particularly, it is difficult to ensure the correctness when using d...
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Among numerical libraries capable of computing gradient descent optimization, JAX stands out by offering more features, accelerated by an intermediate representation known as Jaxpr language. However, editing the Jaxpr...
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ISBN:
(纸本)9783031779404;9783031779411
Among numerical libraries capable of computing gradient descent optimization, JAX stands out by offering more features, accelerated by an intermediate representation known as Jaxpr language. However, editing the Jaxpr code is not directly possible. This article introduces JaxDecompiler, a tool that transforms any JAX function into an editable Python code, especially useful for editing the JAX function generated by the gradient function. JaxDecompiler simplifies the processes of reverse engineering, understanding, customizing, and interoperability of software developed by JAX. We highlight its capabilities, emphasize its practical applications especially in deep learning and more generally gradient-informed software, and demonstrate that the decompiled code speed performance is similar to the original.
RDMA is a technology that enables extremely fast communication between different systems by allowing these systems to transfer data without using the CPU and operating system. This results in the rapid transfer of dat...
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The proceedings contain 7 papers. The special focus in this conference is on engineering Trustworthy softwaresystems. The topics include: From Logic to Programming;digital Twin Tutorial: The Incubator Case Study...
ISBN:
(纸本)9789819646555
The proceedings contain 7 papers. The special focus in this conference is on engineering Trustworthy softwaresystems. The topics include: From Logic to Programming;digital Twin Tutorial: The Incubator Case Study;AI Components for High Integrity, Safety-Critical Human-Cyber-Physical systems: A Challenge for Formal Methods;Testing and Design of Uniform CNF Samplers: A Virtuous Cycle Enabled by Distribution Testing;softwareengineering Experiences of an Optimist;Automating Component-Based Embedded software Construction via Formal Synthesis and LLMs.
With open connectivity and emergent computing, the Industrial Internet of Things (IIoT) combined with cloud computing resources provides significant breakthroughs in the field of industrial automation. These developme...
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The field of Artificial Intelligence (AI) has been witnessing a huge demand in the field of research, tools development, and applications of deployment. There are multiple software companies which are shifting their f...
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This contribution delves into the incorporation of Sustainable Development Goals (SDGs) into the Computer engineering curriculum. The study addresses challenges associated with integrating SDGs as cross-cutting conten...
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