检索结果-内蒙古大学图书馆

Outcomes and Conclusions from the 2022 AM Bench Measurements, Challenge Problems, Modeling Submissions, and conference

引用

INTEGRATING MATERIALS AND MANUFACTURING INNOVATION 2024年第3期13卷 598-621页

作者： Levine, Lyle Lane, Brandon Becker, Chandler Belak, James Carson, Robert Deisenroth, David Glaessgen, Edward Gnaupel-Herold, Thomas Gorelik, Michael Greene, Gretchen Habib, Saadi Higgins, Callie Hill, Michael Hrabe, Nik Killgore, Jason Kim, Jai Won Lemson, Gerard Migler, Kalman Moylan, Shawn Pagan, Darren Phan, Thien Praniewicz, Maxwell Rowenhorst, David Schwalbach, Edwin Seppala, Jonathan Simonds, Brian Stoudt, Mark Weaver, Jordan Yeung, Ho Zhang, Fan NIST Gaithersburg MD 20899 USA Lawrence Livermore Natl Lab Livermore CA 94550 USA NASA Langley Res Ctr Hampton VA 23681 USA FAA Scottsdale AZ 85255 USA NIST Boulder CO 80305 USA Univ Calif Davis Davis CA 95616 USA Johns Hopkins Univ Baltimore MD 21218 USA Penn State Univ University Pk PA 16802 USA US Naval Res Lab Washington DC 20375 USA Air Force Res Lab Wright Patterson AFB OH 45433 USA

The Additive Manufacturing Benchmark Test Series (AM Bench) provides rigorous measurement data for validating additive manufacturing (AM) simulations for a broad range of AM technologies and material systems. AM Bench includes extensive in situ and ex situ measurements, simulation challenges for the AM modeling community, and a corresponding conference series. In 2022, the second round of AM Bench measurements, challenge problems, and conference were completed, focusing primarily upon laser powder bed fusion (LPBF) processing of metals, and both material extrusion processing and vat photopolymerization of polymers. In all, more than 100 people from 10 National Institute of Standards and Technology (NIST) divisions and 21 additional organizations were directly involved in the AM Bench 2022 measurements, data management, and conference organization. The international AM community submitted 138 sets of blind modeling simulations for comparison with the in situ and ex situ measurements, up from 46 submissions for the first round of AM Bench in 2018. Analysis of these submissions provides valuable insight into current AM modeling capabilities. The AM Bench data are permanently archived and freely accessible online. The AM Bench conference also hosted an embedded workshop on qualification and certification of AM materials and components.

关键词： Additive manufacturing Benchmarks Model validation AM Bench Qualification and certification

来源：评论

学校读者我要写书评

暂无评论

data Preprocessing on Triage data for Predicting ICU Transfer within 24 Hours 2

Data Preprocessing on Triage Data for Predicting ICU Transfe...

引用

2nd international conference on Technology Innovation and Its Applications, ICTIIA 2024

作者： Crispin, Andrian Reinaldo Candra, Ade Sitompul, Opim Salim Universitas Sumatera Utara Departement of Data Science and Ai Medan Indonesia

ISBN: (纸本)9798350351613

Automation in the medical field, particularly in intensive Care Units (ICU), has become a primary focus of technological research, with efforts directed towards developing early diagnosis systems, condition prediction, and other applications using machine learning technology. Despite initial challenges due to limited access to sensitive patient and hospital data, research has made significant strides in enhancing the efficiency and quality of care through automation. This study evaluates the effectiveness of data preprocessing on triage data for predicting ICU transfer within a 24-hour period, comparing the performance of the Triage in Emergency Department Early Warning Score (TREWS) system with a Random Forest machine learning model. Due to the unavailability of verification for oxygen requirements and consciousness levels, the TREWS system is only partially scored, excluding these two parameters. The overall accuracy of the TREWS system was 54.23%. When dividing the data based on threshold scores of 4 and 7, the accuracy achieved was 50.13% and 55.77%. In contrast, the Random Forest model demonstrated significant improvements over the TREWS scoring system which increased the accuracy to 63% with the inclusion of additional parameters such as oxygen saturation and gender. The results suggest that integrating machine learning models with expanded parameters and effective data preprocessing can significantly enhance prediction accuracy compared to traditional scoring systems. Recommendations include optimizing traditional scoring systems with additional parameters, implementing machine learning models for better prediction, utilizing broader data sets, and providing training for medical teams on the effective use and interpretation of these models. © 2024 ieee.

关键词： data accuracy

来源：评论

学校读者我要写书评

暂无评论

Research on Visualization Application of Power data Based on Business Intelligence Technology 14

Research on Visualization Application of Power Data Based on...

引用

14th international conference on Power and Energy systems, ICPES 2024

作者： Yong, Wen Yu, Zhongjie Li, Kunming Zhang, Fan Jiangsu Frontier Electric Power Technology Co. Ltd Smart Grid Service Center Nanjing China

ISBN: (纸本)9798350391329

With the promotion of the construction of new power systems and the widespread application of smart grids, a massive amount of power data has been collected within the power system. However, due to strong professional barriers, insufficient data connectivity, and lack of analysis and visualization, there is a phenomenon of 'data richness and information scarcity'. Based on this, this article relies on Business Intelligence (BI) technology, uses electricity big data, and utilizes electricity data application analysis tools to construct a self-service multi-dimensional electricity data analysis visualization model, reducing the threshold for business personnel to use BI tools for data analysis and mining, and effectively enhancing the practical application of data analysis results. © 2024 ieee.

关键词： data assimilation

来源：评论

学校读者我要写书评

暂无评论

Minimizing data Transmission Delay in Vehicular Networks through Network Coding-based Broadcasting 17

Minimizing Data Transmission Delay in Vehicular Networks thr...

引用

ieee Congress on Cybermatics: 17th ieee international conference on Internet of Things, iThings 2024, 20th ieee international conference on Green Computing and Communications, GreenCom 2024, 17th ieee international conference on Cyber, Physical and Social Computing, CPSCom 2024, 10th ieee international conference on Smart data, Smartdata 2024

作者： Hu, Jiali Qu, Long Song, Qinglin Zhu, Ran Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China Zhejiang Faraday Laser Technology co. Ltd Wenzhou325024 China

ISBN: (纸本)9798350351637

Advances in wireless communication technology have facilitated the development of vehicular networks. Intelligent vehicles are able to realize a variety of applications and services to enhance the driving experience through Vehicle-to-Everything (V2X) communication. However, meeting the requirement of low latency in dynamic and complex vehicular environments poses a challenge. This paper presents a network coding framework based on a vehicular network data transmission model, aiming to reduce transmission latency and data dropout rate by encoding and broadcasting packets at Roadside Units (RSUs). Due to the mobility of vehicles, interference becomes more complex. To mitigate interference between data transmissions, we employ dynamic power control. However, the optimization problem involved is a mixed integer problem. To reduce the complexity, this paper introduces a Column Generation algorithm to solve the model. The algorithm decomposes the problem into a pricing problem responsible for packet scheduling and a master problem responsible for minimizing the transmission delay to find the optimal coding opportunities and broadcasting strategies for vehicle packets. Experimental results demonstrate that compared to scenarios without network coding, the proposed algorithm reduces transmission latency by 5.694% and decreases data dropout rate by 7.143%. © 2024 ieee.

关键词： Network coding

来源：评论

学校读者我要写书评

暂无评论

Cubic Graph Property dataset for Machine Learning Models 17

Cubic Graph Property Dataset for Machine Learning Models

引用

17th ieee international Scientific conference on Informatics, INFORMATICS 2024

作者： Modrovicova, Bianka Dudas, Adam Matej Bel University Banská Faculty of Natural Sciences Department of Computer Science Bystrica Slovakia

ISBN: (纸本)9798350387674

Proper edge 3-coloring of a cubic graph is an NP-complete problem, which is present in number of real-live problems - correct and efficient assigning of variables used in the program to registers of the system, scheduling of a set of tasks to a set of processors, or frequency assignment of radio stations without interference. Since the finding of a solution to this problem is computationally intensive, the implementation of approaches using machine learning models for the estimation of the edge colorability is desirable. This study presents a sizable Cubic Graph Property dataset, a graph generator focused on cubic graphs and a set of sub-datasets fitting for machine learning, deep learning and anomaly detection models. © 2024 ieee.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Holistic ARDS Prognosis Evaluation Framework Utilizing data Governance and Ensemble Feature Selection

Holistic ARDS Prognosis Evaluation Framework Utilizing Data ...

引用

2023 ieee international conference on systems, Man, and Cybernetics, SMC 2023

作者： Han, Xiaodong Cai, Fei Xiu, Guanghui Tao, Dapeng School of Information Science and Engineering Yunnan University Fist Lab Kunming650500 China Department of Intensive Care Unit Kunming650500 China

ISBN: (纸本)9798350337020

Acute respiratory distress syndrome (ARDS) prognosis has become integral to modern critical care models aimed at determining expected patient outcomes, optimizing clinical pathways, and improving resource allocation. However, existing clinical studies of ARDS prognosis face severe challenges due to the redundancy of multiple sources of heterogeneous data in current healthcare datasets, the high dimensionality of patient features, and the wide variation in the importance of each feature. In this paper, we propose a holistic ARDS prognostic framework for assessing ARDS prognosis through a standardized data governance process and an integrated feature selection approach based on embedded algorithms. Specifically, we extract ARDS patient data from medical data sources by various criteria and normalize the features. Then we apply multiple embedded feature selection methods to obtain a decision matrix based on the data-governed dataset. We conducted extensive experiments to demonstrate the efficiency and superiority of our proposed framework. The experimental results show that our proposed framework performs well in both data governance and feature selection and has wide clinical application potential. © 2023 ieee.

关键词： acute respiratory distress syndrome data governance feature selection machine learning prognosis evaluation

来源：评论

学校读者我要写书评

暂无评论

DSPOL: A High-Level Language for Defining data Policies in data Spaces

DSPOL: A High-Level Language for Defining Data Policies in D...

引用

2024 ieee international conference on Big data, Bigdata 2024

作者： Taniguchi, Shunya Nakajima, Shin Michikata, Takashi Seike, Hirotsugu Koshizuka, Noboru The University of Tokyo Graduate School of Interdisciplinary Information Studies Tokyo Japan The University of Tokyo Interfaculty Initiative in Information Studies Tokyo Japan

ISBN: (纸本)9798350362480

In recent years, data spaces have emerged as a framework for secure data collaboration. data spaces are distributed data collaboration infrastructure systems that enable data collaboration among stakeholders. One of the requirements for data space systems is the technical enforcement of governance policies for the shared data. The objective of this study is to propose a new policy definition language, DSPOL, as a stepping stone toward realizing the enforcement of data governance for the practical use of data spaces. DSPOL can describe the constraints that must be followed in data space systems when accessing and using data, and when distributing deliverables. It has verification and validation functions to ensure that the policy description is as the writer intended and that there are no inconsistencies in the policy. We defined the state transitions of data usage in data user environments, developed a model of the execution infrastructure in data space systems, and formulated the contents of the describable policies. We implemented DSPOL and its verification and validation functions. Examples of policy descriptions based on supposed scenarios were shown, and examples of verification and validation were presented. © 2024 ieee.

关键词： data consistency

来源：评论

学校读者我要写书评

暂无评论

Face Mask Detection Using SSD-Mobilenet-V2 13

Face Mask Detection Using SSD-Mobilenet-V2

引用

13th international conference on Cloud Computing, data science and Engineering, Confluence 2023

作者： Ragunthar, T. Mukherjee, Attri Sati, Shresth Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur Tamil Nadu Chennai India Srm Institute of Science and Technology Computer Science and Engineering Kattankulathur Tamil Nadu Chennai India

ISBN: (纸本)9781665462631

Mask detection plays a major role in the prevention and control of epidemics after the COVID-19 outbreak as it is the most practical and effective method of prevention. For the appropriate employees, a great automatic real-time face mask identification system based on deep learning can significantly lessen work-related stress. The systems for mask identification that are currently in use, however, are largely resource-intensive and do not strike a reasonable balance between speed and accuracy. In our system, the mask detector is SSD, and to extract the image's features and decrease a number of parameters, MobileNet takes the role of VGG-16. Pre-trained models from other domains are transferred to our model using transfer learning techniques. © 2023 ieee.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

MRCA: Metric-level Root Cause Analysis for Microservices via Multi-Modal data 24

MRCA: Metric-level Root Cause Analysis for Microservices via...

引用

39th ACM/ieee international conference on Automated Software Engineering (ASE)

作者： Wang, Yidan Zhu, Zhouruixing Fu, Qiuai Ma, Yuchi He, Pinjia Chinese Univ Hong Kong Shenzhen CUHK Shenzhen Shenzhen Peoples R China Huawei Cloud Comp Technol Co Ltd Shenzhen Peoples R China Shenzhen Res Inst Big Data Shenzhen Peoples R China

ISBN: (数字)9798400712487

ISBN: (纸本)9798400712487

Due to the complexity and dynamic nature of large-scale microservice systems, manual troubleshooting is time-consuming and impractical. Therefore, automated Root Cause Analysis (RCA) is essential. However, existing RCA approaches face significant challenges. (1) Multi-modal data (e.g. traces, logs, and metrics) record the status of microservice systems, but most existing RCA approaches rely on single-source data, failing to understand the system fully. (2) Existing RCA approaches ignore the services' anomaly state and their anomaly intensity. (3) The service-level RCAs lack detailed information for quick issue resolution. To tackle these challenges, we propose MRCA, a metric-level RCA approach using multi-modal data. Our key insight is that using multi-modal data allows for a comprehensive understanding of the system, enabling the localization of root causes across more anomaly scenarios. MRCA first utilizes traces and logs to obtain the ranking list of abnormal services based on reconstruction probability. It further builds causal graphs from services with high anomaly probability to discover the order in which abnormal metrics of different services occur. By incorporating a reward mechanism, MRCA terminates the excessive expansion of the causal graph and significantly reduces the time taken for causal analysis. Finally, MRCA can prune the ranking list based on the causal graph and identify metric-level root causes. Experiments on two widely-used microservice benchmarks demonstrate that MRCA outperforms state-of-the-art approaches in terms of both accuracy and efficiency.

关键词： Root Cause Analysis Microservices Reinforcement Learning Multi-modal

来源：评论

学校读者我要写书评

暂无评论

data Volume-aware Computation Task Scheduling for Smart Grid data Analytic Applications

Data Volume-aware Computation Task Scheduling for Smart Grid...

引用

ieee international conference on Communications (ieee ICC)

作者： Guo, Binquan Li, Hongyan Yan, Ye Zhang, Zhou Wang, Peng Xidian Univ State Key Lab Integrated Serv Networks Xian Peoples R China Tianjin Artificial Intelligence Innovat Ctr TAIIC Tianjin Peoples R China

ISBN: (纸本)9781538674628

Emerging smart grid applications analyze large amounts of data collected from millions of meters and systems to facilitate distributed monitoring and real-time control tasks. However, current parallel data processing systems are designed for common applications, unaware of the massive volume of the collected data, causing long data transfer delay during the computation and slow response time of smart grid systems. A promising direction to reduce delay is to jointly schedule computation tasks and data transfers. We identify that the smart grid data analytic jobs require the intermediate data among different computation stages to be transmitted orderly to avoid network congestion. This new feature prevents current scheduling algorithms from being efficient. In this work, an integrated computing and communication task scheduling scheme is proposed. The mathematical formulation of smart grid data analytic jobs scheduling problem is given, which is unsolvable by existing optimization methods due to the strongly coupled constraints. Several techniques are combined to linearize it for adapting the Branch and Cut method. Based on the topological information in the job graph, the Topology Aware Branch and Cut method is further proposed to speed up searching for optimal solutions. Numerical results demonstrate the effectiveness of the proposed method.

关键词： Smart grid applications data analytics task scheduling job completion time branch and cut disjunctive formulation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：