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检索条件"任意字段=Proceedings of the 2023 5th International Conference on Big Data Engineering and Technology"

共 11302 条记录，以下是4561-4570 订阅

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Energy Consumption Characteristics of Wall-Hanging Gas Boilers in Hot Summer–Cold Winter Zone of China 5th

Energy Consumption Characteristics of Wall-Hanging Gas Boile...

引用

proceedings of the 5th international conference on Clean Energy and Electrical Systems - proceedings of CEES 2023

作者： Zhou, Yubo Huang, Xiaomei Hu, Zhuojun School of Civil Engineering Chongqing University Chongqing400044 China Energy Engineering Technology Co. LTD. Nanjing210022 China

ISBN: (纸本)9789819938872

With socioeconomic development, the consumption of natural gas heating has increased in regions characterized by hot summers and cold winters. To explore the characteristics of heating energy consumption in residential buildings, original natural-gas consumption data were obtained from residential households in Nanjing, China and a cluster analysis was conducted based on the level of energy consumption and residents’ reliance on heating. the findings indicate that (1) natural-gas heating users can be classified into three clusters: low heating energy consumption and low reliance on heating, medium heating energy consumption and high reliance on heating, and high heating energy consumption and high reliance on heating;(2) heating energy consumption is inversely related to air temperature and a high heating energy consumption is more sensitive to air temperature;and (3) the heating energy consumption is higher on non-working days compared to that for workdays, and low heating energy consumption during workdays strongly influences that on non-working days. these findings will act as reference for building engineers and urban planners to realize the demand characteristics of gas heating in urban settlements situated in hot summer–cold winter zones. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Natural gas

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Design and Implementation of Industrial Gateway for AUTBUS and 5G Protocol Conversion 19

Design and Implementation of Industrial Gateway for AUTBUS a...

引用

19th international conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Wang, Shiyu Wei, Min Hong, Seungho China-Korea Belt and Road Joint Laboratory on Industrial Internet of Things Chongqing University of Posts and Telecommunications Chongqing China Research and Development Center Nestfield Company Ltd Ansan705 Korea Republic of Department of Electronic Engineering Hanyang University Ansan15588 Korea Republic of

ISBN: (纸本)9798331507817

With the rapid development of industrial automation, the demand for preserving the original priority, flow identification, and latency stability of industrial data is continuously increasing. the new generation bus technology, AUTBUS, features multi-node, high bandwidth, and high real-time performance, addressing the limitations of traditional buses in terms of high bandwidth and determinism requirements. the high bandwidth, low latency, and high reliability of 5G networks can meet the flexibility and mobility needs of industrial equipment, promoting the wireless application of devices. Developing an industrial gateway that supports AUTBUS and 5G network protocol conversion is of great significance for the future of industrial networks. this paper designs an industrial gateway that supports AUTBUS-5G network protocol conversion, capable of maintaining the original priority and flow identification characteristics of the network after data conversion. By adopting a multi-factor 5G transmission queue priority sorting method, the average latency jitter of data flow through the industrial gateway is reduced by 85%. © 2025 IEEE.

关键词： Bandwidth

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A Modified Multi-station Combined Processing Algorithm for Telemetry Tracking and Control under Low SNR 5

A Modified Multi-station Combined Processing Algorithm for T...

引用

5th international conference on Information Communication and Signal Processing, ICICSP 2022

作者： Wen, Yu Ping, Dong Yong, Li Beijing Institute of Tracking and Telecommunications Technology Beijing China Beijing Research Institute of Telemetry Beijing China

ISBN: (纸本)9781665485890

the incoherent spread spectrum measurement method is widely used for spacecraft telemetry tracking and control, which requires 4 ground stations communicate with the spacecraft responder simultaneously. With the increasing demand for high data transmission rate, it presents a challenge to bigger antenna aperture of the ground station, as well as the quantity. A novel modified multi-station combined processing algorithm is proposed in this paper to receive the signal carrier, detect the frame pulse, and obtain the measurement data at a low SNR, effectively reducing the antenna aperture requirements to only 1 big station and 3 small stations instead of 4 big stations. the validity of the algorithm is demonstrated with experimental results, confirming its superiority with an adequate precision and engineering implementation meaning. © 2022 IEEE.

关键词： Signal processing

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AshPipe: Asynchronous Hybrid Pipeline Parallel for DNN Training 5

AshPipe: Asynchronous Hybrid Pipeline Parallel for DNN Train...

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5th international conference on big-data Service and Intelligent Computation, BDSIC 2023

作者： Hosoki, Ryubu Endo, Toshio Hirofuchi, Takahiro Ikegami, Tsutomu Tokyo Institute of Technology Yokohama Japan National Institute of Advanced Industrial Science and Technology Tokyo Japan

ISBN: (纸本)9798400708893

Deep Neural Networks (DNNs) have become increasingly computationally intensive and have larger parameters, requiring efficient parallelization or distribution using multiple accelerators. Pipeline parallelism has been proposed as an effective way to distribute models and improve hardware utilization. However, the problem with pipeline parallelism is the trade-off between speedup and accuracy: synchronous approaches do not provide sufficient speedup, while asynchronous approaches suffer from accuracy degradation due to a different scheme from a single worker. In this paper, we propose AshPipe, a hybrid parallel framework that combines data parallelism and asynchronous pipeline parallelism to achieve efficient speedup for training. the proposed runtime uses the 1F1B schedule and data parallelism, with non-uniform numbers of workers and identical global batch sizes across stages. A Switch Parallelism (SP) mechanism is also proposed as an option to mitigate accuracy degradation, which switches over from data parallelism to hybrid parallelism in the course of training. Experimental results show that AshPipe achieves 1.844× the throughput of data parallelism for ViT-H/14 whose parameter size is 632M. With the SP mechanism, AshPipe achieved a 30.2% reduction in training time with comparable accuracy compared to data parallelism when training on the CIFAR100 dataset. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Deep neural networks

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Emerging Trends in Construction Dispute Resolution: Integrating technology and Collaboration for the Future 5th

Emerging Trends in Construction Dispute Resolution: Integrat...

引用

5th international conference on Advanced Technologies and Humanity

作者： Salem, Elsayed Elwakil, Emad Hegab, Mohamed Purdue Univ Sch Construct Management W Lafayette IN 47907 USA Calif State Univ Dept Civil Engn & Construct Management Northridge CA USA

ISBN: (纸本)9783031765568;9783031765575

Construction disputes have historically caused massive delays and cost overruns, often stemming from adversarial relationships between stakeholders. However, the industry is transforming towards more collaborative, technology-enabled dispute prevention and resolution approaches. this paper explores these emerging trends by extensively analyzing current literature and industry outlooks. It examines innovations in digital documentation, data analytics, virtual collaboration, blockchain transactions, integrated project delivery, and relational contracting frameworks reshaping dispute cultures. the study aims to investigate the ability top integrate new technologies for instance BIM and fuzzy logic systems to reduce disputes in construction projects. the analysis also underscores the need for construction professionals to continually expand their expertise in the latest dispute management best practices as projects become more complex. It concludes that an amalgamation of technological tools, collaborative mindsets, proactive planning, and continuous knowledge building is crucial in developing efficient construction disputemanagementmechanismsworldwide. Also, the full sharing of information and collaboration between project parties is the effective way to reduce conflicts and disputes at early stages.

关键词： construction disputes delays technology-enabled dispute resolution digital documentation data analytics virtual collaboration blockchain transactions integrated project delivery relational contracting frameworks dispute cultures dispute management knowledge building construction professionals

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Current Situation and Strategy of Construction engineering Management Informatization Based on big data technology 1

引用

5th international conference on Innovative Computing, IC 2022

作者： Wang, Bin Zhang, Suli Luohe Water Investment Co. Ltd. Henan Luohe462000 China Luohe Survey Planning and Design Institute Henan Luohe462000 China

ISBN: (数字)9789811941320

ISBN: (纸本)9789811941313

With the fierce competition in the market, in order to promote the stable development of construction projects, this paper analyzes the basic management of big data, and proposes the optimization countermeasures of construction and management under big data environment. Firstly, based on the big data technology, this paper discusses the management information of construction engineering. Secondly, it carries out the experimental research on the current situation of the use of construction engineering management information system. Finally, it tests and analyzes the functions and requirements of the system. the experimental results show that 42% of the construction enterprises have the highest demand for the system. © 2022, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： big data

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Optimized data Processing for Hard Drive Failure Prediction 5

Optimized Data Processing for Hard Drive Failure Prediction

引用

5th international conference on Emerging Systems and Intelligent Computing, ESIC 2025

作者： Sivakumar, M. Ragavendra, R. Satapathy, Sandeep Kumar Mishra, Shruti Mallick, Pradeep Kumar Vellore Institute of Technology School of Computer Science & Engineering Tamilnadu Chennai India Vellore Institute of Technology Centre for Advanced Data Science Tamil Nadu Chennai India Kiit University School of Computer Engineeing Odisha India

ISBN: (纸本)9798331522100

With the rise of big data, efficient data handling techniques have become increasingly crucial. Hard drive failure prediction is a critical domain where accurate and timely data handling is paramount. this research paper introduces a data analysis and pre-processing approach for hard drive failure prediction based on machine learning techniques. A large dataset encompassing hard drive operational data, metadata, and error rates was collected. Extensive pre-processing was performed, including data cleaning and transformation. Multiple Machine Learning algorithms, including random forests, were employed to train predictive models for hard drive failure. the results demonstrate the effectiveness of our approach in achieving high accuracy for hard drive failure prediction, highlighting the significance of our pre-processing methods. Additionally, this paper compares existing machine learning algorithms and explores the role of big data in enhancing hard drive failure prediction. the utilization of big data and advanced data handling techniques has led to improved accuracy and predictive capabilities, making it an indispensable factor in this field. © 2025 IEEE.

关键词： data curation

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PCOS Detection Using CNN and ML Algorithms 5th

PCOS Detection Using CNN and ML Algorithms

引用

5th international conference on data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Roja, G. Spandana, B. Divya, N. Anusha, R. Pushpa Rani, K. Narayanamma Institute of Technology and Science Telangana Hyderabad India Department of CSE G. Narayanamma Institute of Technology and Science Telangana Hyderabad India Narayanamma Institute of Technology and Science Telangana Hyderabad India Department of CSE MLR Institute of Technology and Science Telangana Hyderabad India

ISBN: (纸本)9789819780426

Polycystic Ovarian Syndrome (PCOS) is a complicated menstrual sickness that affects a wide range of women of procreative lifetime. Its miles connected with a combination of signs, including abnormal menstrual cycles, hormonal imbalances, and the presence of more than one cyst on the ovaries. the current methods for diagnosing PCOS involve a comprehensive evaluation that includes medical history assessment, physical examinations, and laboratory tests. However, these approaches have limitations. they can be time-consuming, relying on the subjective judgment and expertise of healthcare professionals. In light of these challenges, there is a growing need for more advanced and efficient methods of diagnosing PCOS. By utilizing machine learning algorithms and computer vision techniques, such a system can provide an objective and reliable approach to identify PCOS based on ultrasound images. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Diagnosis

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Exploring Multi-Task Learning for Transfer Learning Based Active Learning in Medical Image Segmentation 5th

Exploring Multi-Task Learning for Transfer Learning Based Ac...

引用

5th international conference on data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Yadav, Surjeet Kumar, Arvind Kannagi, A. Sahoo, Girija Shankar Department of Mechanical Engineering Vivekananda Global University Jaipur India Department of Biotechnology Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

Present methods for medical photograph segmentation have enabled clinical practitioners and researchers to apprehend and create unique interpretations ultra-modern clinical snap shots. But, there is nonetheless tons that may be stepped forward upon. Switch brand new-based energetic modern-day has been proposed to improve the accuracy cutting-edge deep today’s-based scientific photograph segmentation but the consequences are limited. Multi-project modern day, a contemporary transfer modern day, can further enhance the accuracy and robustness modern day segmentation. this research makes a specialty of exploring the efficacy contemporary multi-challenge learning, combined with switch present day based lively contemporary, in scientific image segmentation. In the long run, these research pursuits to take cutting-edge expertise associated with transfer cutting-edge based energetic latest and scientific photo segmentation and make bigger upon it to discover novel methods to improve average accuracy and robustness modern day clinical image segmentation. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Active learning

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Advanced study on agronomic strategies for crop cultivation 4

Advanced study on agronomic strategies for crop cultivation

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4th international conference on Computer technology, Information engineering, and Electron Materials, CTIEEM 2024

作者： Lu, Tingting Gao, Zhan Ma, Doudou Li, Xinyan School of Artificial Intelligence and Big Data Henan University of Technology Zhengzhou China

ISBN: (纸本)9781510689299

this article aims to provide a scientific basis for future crop planting planning in a rural area by first analyzing 2023 data on crop planting areas, rotation patterns, and legume cultivation to develop a model focused on maximizing planting profits. It incorporates expected sales changes, yield variations, and other market and environmental factors as constraints. Using advanced visualization tools and Deming regression models, the study examines the relationship between crop prices and expected sales, while addressing constraints like planting area, rotation, density, and sales volume through mixed integer and linear programming methods. To address future uncertainties in crop sales, yields, costs, and prices, the study employs robust optimization methods and Monte Carlo simulations to ensure stability and adaptability of optimal planting strategies. Furthermore, it explores crop substitutability and complementarity by analyzing relationships between sales, prices, and costs using K-Means clustering and Spearman correlation analysis, optimizing planting strategies to enhance economic benefits and reduce risks associated with market and climate changes. © 2025 SPIE.

关键词： Linear programming

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