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Swarm Robotics: Coordination and Collaboration in Multi-Robot Systems 蜂群机器人:多机器人系统中的协调与协作
Pub Date : 2024-03-22 DOI: 10.48047/resmil.v9i1.20
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引用次数: 0
Green Roofing and Sustainable Construction Materials 绿色屋顶和可持续建筑材料
Pub Date : 2024-03-01 DOI: 10.48047/resmil.v10i1.15
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引用次数: 0
Analysis of Thermoluminescence Glow Curves of X-ray irradiated CaSO4:Dy phosphor X 射线辐照 CaSO4:Dy 荧光粉的热致发光辉光曲线分析
Pub Date : 2024-03-01 DOI: 10.48047/resmil.v12i6.51
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引用次数: 0
HYBRID CLOUD SOLUTIONS 混合云解决方案
Pub Date : 2024-03-01 DOI: 10.48047/resmil.v10i1.8
As automation and consumerization become the dominant paradigms for designing and deploying IT infrastructure, these trends will also extend to the next frontier of IT-shop modernization: systems management and higher-level automation. This report identifies and examines the current state of enterprise adoption of private, public and hybrid clouds by workload using original survey research.
随着自动化和消费化成为设计和部署 IT 基础架构的主流模式,这些趋势也将扩展到 IT 部门现代化的下一个前沿领域:系统管理和更高级别的自动化。本报告利用原创调查研究,按工作量确定并研究了企业采用私有云、公共云和混合云的现状。
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引用次数: 0
Green Computing in the Cloud: A Review of Energy-Efficient Practices 云计算中的绿色计算:节能实践回顾
Pub Date : 2024-03-01 DOI: 10.48047/resmil.v10i1.10
Dinesh Kumar, Garg, Rohitash Kumar
: The speedy growth of cloud computing has propelled issues about its environmental footprint, prompting a crucial exam of strength intake in records centers. This evaluate delves into the area of inexperienced computing in the context of cloud environments, focusing on strength-efficient practices and their implications for sustainability. By surveying the latest techniques, technology, and projects, these paper pursuits to offer a comprehensive understanding of ways the cloud computing paradigm can align with environmental duty. From strength-efficient records middle practices to the combination of renewable strength resources, the synthesis of present-day studies and industry practices sheds light at the multifaceted techniques to decrease the carbon footprint of cloud services. The summary concludes via emphasizing the significance of embracing green computing as an quintessential aspect of the evolving panorama of cloud technologies, striving for a harmonious coexistence among digital innovation and environmental sustainability.
:云计算的快速发展引发了有关其环境足迹的问题,促使人们对记录中心的强度摄入量进行重要检查。本评估报告深入探讨了云计算环境下的非经验计算领域,重点关注节能实践及其对可持续发展的影响。通过对最新技术、科技和项目的调查,本文旨在全面了解云计算模式如何与环境责任保持一致。从节约能源的记录中心实践到可再生能源的结合,当今研究和行业实践的综合揭示了减少云服务碳足迹的多方面技术。总结强调了将绿色计算作为不断发展的云技术全景的一个重要方面的意义,努力实现数字创新与环境可持续性的和谐共存。
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引用次数: 0
Legal and Ethical Aspects of IoT Security 物联网安全的法律和道德问题
Pub Date : 2024-03-01 DOI: 10.48047/resmil.v9i1.29
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引用次数: 0
Machine Learning with TensorFlow and PyTorch: A Comparative Analysis 使用 TensorFlow 和 PyTorch 进行机器学习:比较分析
Pub Date : 2024-03-01 DOI: 10.48047/resmil.v10i1.21
Gaurav Agrawal, Shazmeen Taqvi, Richa Gulati
: Machine learning frameworks play a pivotal position inside the development and deployment of modern fashions for a big selection of programs. TensorFlow and PyTorch, two prominent frameworks, have emerged as leaders in the discipline, each with its particular strengths and characteristics. This research paper conducts a complete comparative evaluation of TensorFlow and PyTorch, that specialize in their architecture, ease of use, network aid, and overall performance in system studying packages. The paper begins via offering an outline of the historic improvement and key features of each TensorFlow and PyTorch. Subsequently, it delves into an in depth exam of their respective computational graphs, dynamic/static graph execution modes, and model deployment abilities. Special emphasis is positioned on know-how the learning curve related to each framework, exploring their high-degree APIs, and assessing their extensibility for studies and production environments. The study conducts a performance analysis, evaluating TensorFlow and PyTorch across various benchmarks and real-international eventualities. Metrics such as education pace, useful resource usage, and scalability are taken into consideration to provide a holistic information of their computational efficiency. Additionally, the research investigates the frameworks' compatibility with specialized hardware, which includes GPUs and TPUs, to assess their capability for
:机器学习框架在大量程序的现代时尚开发和部署中发挥着举足轻重的作用。TensorFlow 和 PyTorch 这两个著名的框架已成为该领域的佼佼者,它们各有自己的优势和特点。本研究论文对 TensorFlow 和 PyTorch 进行了全面的比较评估,专门研究了它们在系统研究软件包中的架构、易用性、网络辅助和整体性能。论文首先概述了 TensorFlow 和 PyTorch 各自的历史改进和关键特性。随后,论文深入研究了它们各自的计算图、动态/静态图执行模式和模型部署能力。本研究特别强调了解与每个框架相关的学习曲线、探索它们的高级应用程序接口,以及评估它们在研究和生产环境中的可扩展性。本研究进行了性能分析,评估了 TensorFlow 和 PyTorch 在各种基准和实际国际情况下的表现。研究考虑了教育速度、有用资源使用和可扩展性等指标,以提供有关其计算效率的整体信息。此外,研究还调查了这些框架与专用硬件(包括 GPU 和 TPU)的兼容性,以评估它们在以下方面的能力
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引用次数: 0
Exploratory Data Analysis (EDA) for Beginners: Tools and Best Practices 探索性数据分析 (EDA) 入门:工具和最佳实践
Pub Date : 2024-03-01 DOI: 10.48047/resmil.v10i1.11
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引用次数: 0
AI in Healthcare: Applications, Challenges, and Future Prospects 医疗保健中的人工智能:应用、挑战和未来展望
Pub Date : 2024-03-01 DOI: 10.48047/resmil.v10i1.18
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引用次数: 0
Review on studies of radioactivity in soil 土壤放射性研究综述
Pub Date : 2024-03-01 DOI: 10.48047/resmil.v12i6.52
N. B. Singh, H. S. Singh, A. R. Devi, B. A. Sharma, Th. Basanta Singh
: Natural radioactivity is a source of continuous exposure to human beings. It originates from both extraterrestrial sources and radioactive elements in the earth’s crust. The amount of radioactivity in soil varies widely. The main radionuclides contaminant in soil are mainly from 238 U and 232 Th decay series and 40 K . Activity concentrations of soil samples are normally measured by means of high-resolution gamma-ray spectrometry. Several studies on natural radioactivity in soil as well as building materials has been done and various observations were reported. In this article, a review on studies of radioactivity in soil was carried out
:天然放射性是人类持续受到辐射的一个来源。它来源于地外辐射源和地壳中的放射性元素。土壤中的放射性含量差异很大。土壤中的主要放射性核素污染物主要来自 238 U 和 232 Th 衰变系列以及 40 K。土壤样本的放射性浓度通常通过高分辨率伽马射线光谱仪来测量。对土壤和建筑材料中的天然放射性进行了多项研究,并报告了各种观察结果。本文对土壤中的放射性研究进行了综述。
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引用次数: 0
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