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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 11297 条记录，以下是4541-4550 订阅

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UNDERSTANDING thE CHALLENGES AROUND DESIGN ACTIVITIES thAT INCORPORATE BEHAVIORAL data 24

UNDERSTANDING THE CHALLENGES AROUND DESIGN ACTIVITIES THAT I...

引用

24th international conference on engineering Design, ICED 2023

作者： Gomez Ortega, Alejandra Bourgeois, Jacky Kortuem, Gerd Delft University of Technology Netherlands

Recently, methods and approaches such as Participatory data Analysis, data-Enabled Design, and Contextual Inquiry have highlighted how design activities can benefit from behavioral data. this data offers new ways to learn from what people do and how they do it, across time and space. However, behavioral data introduces changes and frictions to design activities and poses several challenges for designers to overcome. In this paper, we conduct two workshops with 18 expert designers, from industry and academia, to understand the nature of these challenges, beyond the technical aspects. We contribute by underlining the challenges and opportunities of incorporating behavioral data into design activities;including a design perspective on data, interacting with participants, and interacting with regulatory bodies. We translate our findings into opportunities for a better alignment between regulatory bodies, designers, and participants. We propose to harness the iterative nature of design activities and embedded it into a process that allows for continuous reflection, reassessment, and review of highly dynamic datasets. © the Author(s), 2023. Published by Cambridge University Press.

关键词： big data

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Multi-scale network combined with multi-loss optimization for low-light image super-resolution reconstruction 5

Multi-scale network combined with multi-loss optimization fo...

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5th international conference on Computer Vision and data Mining, ICCVDM 2024

作者： Liu, Bofeng Yu, Haiyang Hu, Xiaojuan Li, Yanfeng School of Computer Science and Technology Changchun University of Science and Technology Jilin Changchun130022 China Key Laboratory of Photoelectric Measurement & Control and Optical Information Transfer Technology Ministry of Education Changchun University of Science and Technology Jilin Changchun130022 China

ISBN: (纸本)9781510682863

the proposed super resolution reconstruction method aims to address the issues of missing detailed information in low light environments and poor recovery of high frequency details in reconstructed images. To fully extract the retained features of low-light images, a multi-scale feature fusion learning network is introduced, which utilizes convolution to extract shallow features and then extracts deep features through multiple cascaded multi-scale feature extraction modules. Additionally, an attention mechanism is incorporated to adaptively learn the importance of each channel and finally fuse the obtained shallow and multi-scale features. Furthermore, perceptual loss and edge loss are integrated into the loss function to optimize the network for high frequency texture details in the recovered image. Experimental results demonstrate that this method yields clearer edge structures and texture details after super-resolution reconstruction of images acquired in low light environments, outperforming other existing methods both visually and objectively. © 2024 SPIE.

关键词： Convolutional neural networks

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Combining Transfer Learning and Meta Learning for Medical Image Classification 5th

Combining Transfer Learning and Meta Learning for Medical Im...

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

作者： Srivastava, Manish Kaushik, Sanchi Raghavendra, R. Pandeya, Megha Department of Electrical Engineering Vivekananda Global University Jaipur India Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bangalore India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

Adaptive Meta studying (AML) for transfer getting to know is a method used for medical photo classification that leverages present pre-educated models at the goal domain to rapidly and as it should train a deep learning version. It works by tuning the parameters of a pre-trained version which can be critical for a venture-specific use case. It permits quicker and more significant accurate consequences than training from scratch. AML starts by educating the source community on using a goal dataset, then transferring the found out weights to the goal dataset for best-tuning. the version can then be fine-tuned using a small subset of the target dataset or training from the source dataset. In both instances, optimizing the use of AML is stepped forward with each unmarried parameter replaced, significantly reducing the schooling time and improving the overall accuracy. that is particularly beneficial for the clinical photograph category, as there is often a confined quantity of training facts to be had because of ethical and privacy considerations. AML can allow for quicker, greater correct, and more excellent transferable fashions to be created. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Federated learning

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Numerical analysis of inter-valley electrons transferring behavior in GeSn alloys for optoelectronic applications 5

Numerical analysis of inter-valley electrons transferring be...

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5th international conference on Telecommunications, Optics, and Computer Science, TOCS 2024

作者： Huang, Shihao Li, Jiapeng Li, Hailin Sun, Qinqin Xie, Wenming Li, Qiongyu Zhao, Fengyan School of Electronic Electrical Engineering and Physics Fujian University of Technology Fuzhou350118 China Fujian Key Laboratory of Automotive Electronics and Electric Drive Fujian University of Technology Fuzhou350118 China

ISBN: (纸本)9781510691667

the electron-phonon interaction in GeSn alloys provides a handle to tune its optoelectronic properties for a variety of applications. A comprehensive understanding of how the inter-valley scattering between Γ and L valleys modulates electron dynamics in GeSn alloys is needed. this letter focuses on the theoretical analysis of inter-valley scattering mechanisms between Γ and L valleys, and hence on the electron transmission dynamics in GeSn alloys. Firstly, the electronic band structure of GeSn alloys in the full Brillouin zone has been reproduced by 30-band k•p method. Secondly, inter-valley scattering calculations have been shown that scattering rate of electrons from Γ valley to L valley is higher than that from L valley to Γ valley. thirdly, electron transmission dynamics indicates that inter-valley scattering help to enhance the electron population in Γ valley for GeSn materials with low Sn composition. Results are beneficial to understand the microscopic mechanism of carrier scattering in GeSn materials, and can be a potential theoretical approach for optimizing the performance of GeSn-based optoelectronic devices. © 2025 SPIE.

关键词： Photoelectric devices

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A comparative study on BEM solvers for wave energy converters 5th

A comparative study on BEM solvers for wave energy converter...

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5th international conference on Renewable Energies Offshore, RENEW 2022

作者： Raghavan, V. Lavidas, G. Metrikine, A.V. Mantadakis, N. Loukogeorgaki, E. Department of Hydraulic Structures Delft University of Technology Netherlands Department of Civil Engineering Aristotle University of Thessaloniki Greece

ISBN: (纸本)9781032420035

Wave Energy Converters (WECs) are expected to significantly contribute to the energy transition;however, this depends on their interactions with the resource. Calculating the power generated by WECs depends heavily on the accurate modelling of wave-structure interactions. the Boundary Element Method (BEM) based on the potential flow theory has yielded accurate results at low computational costs when compared to complex Computational Fluid Dynamics (CFD) methods. Hydrodynamic Analysis of Marine Structures (HAMS), a recently developed open-source BEM frequency domain solver, originally was created for large marine structures. To date it has only been applied to single WECs with spherical/cylindrical geometries. HAMS offers unique advantages through its efficient removal of irregular frequencies and lower computational costs. this paper aims to compare hydrodynamic coefficients, exciting forces, Response Amplitude Operators (RAOs) and computational costs between HAMS, WAMIT, and NEMOH for a cylindrical point absorber and an oscillating surge WEC, extending the currently limited WECs application in HAMS. © 2023 the Author(s).

关键词： Boundary element method

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IoT with Cloud Based Breast Cancer Diagnosis Using Deep Learning Techniques 5

IoT with Cloud Based Breast Cancer Diagnosis Using Deep Lear...

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5th international conference on Inventive Research in Computing Applications, ICIRCA 2023

作者： Ranjith Kumar, G. Ranjani, M. Santhiya, R. thamilselvi, S.S. K.S. Rangasamy College of Technology Dept. of Electronics and Communication Engineering Tiruchengode India

ISBN: (纸本)9798350321425

Breast cancer is a significant public health issue affecting women worldwide. Early detection and accurate diagnosis are crucial for improving survival rates and reducing mortality. Deep learning, an instance of machine learning, has yielded encouraging results in a variety of medical applications, especially breast cancer detection. Deep learning algorithms can automatically learn and identify patterns in medical images, such as mammograms, to detect breast cancer. Moreover, deep learning can also assist in predicting breast cancer sub-types and prognoses. this proposed study provides a review of the current state-of-the-art in deep learning for breast cancer detection and prognosis, including the use of convolutional neural networks (CNNs). To address the issue of breast cancer detection, a deep learning architectures named ResNet-50 and EffNet-50 are used to detect the affected portion. In this proposed method, the Dicom mammogram image is used for diagnosis. the designed architectures are tested with the training dataset of size 19,994 and a validation set of size 8,333 and its accuracy is found separately for both models and also by combining them. the combined ResNet50 and EffNet50 architectures are found to provide a highest accuracy of 98.6% whereas the individual models accuracy is 96.2% and 96.8% for ResNet-50 and EffNet-50 respectively © 2023 IEEE.

关键词： Medical applications

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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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Short-term traffic flow prediction based on BAS-VMD-CEEMDAN and IWOA-RF 11

Short-term traffic flow prediction based on BAS-VMD-CEEMDAN ...

引用

11th international conference on Information Systems and Computing technology, ISCTech 2023

作者： Tian, Jia Wang, Deyong Fn, Yanyun Zhao, Xueyi Fang, Jian Shi, Wenxi Xinjiang University School of Information Science and Engineering Urumqi830017 China Xinjiang Lianhaichuangzhi Information Technology Co. Ltd Key Laboratory of Big Data of Xinjiang Social Security Risk Prevention and Control Urumqi830011 China Beijing Academy of Science and Technology Beijing100035 China

ISBN: (纸本)9798350342406

Short-term traffic flow forecasting is crucial for intelligent traffic management. In view of the non-linear and random nature of short-term traffic flow, a prediction model based on BAS-VMD-CEEMDAN and IWOA-RF is proposed. Firstly, the parameters of the VMD, namely the modal number (K) and the value of the quadratic penalty term (α), are optimized using the BAS algorithm, and then the traffic flow is decomposed to obtain several VMF components and one RES component, which extracts the smooth information of the traffic flow. Subsequently, the RES component is decomposed using the decomposition completeness of CEEMDAN to obtain several IMF components, refining the complex information of the RES component. then, the RF model is constructed according to the characteristics of each component, and then the parameters of RF models are optimized using IWOA. Finally, overlay the predictions of each component superimposed to obtain the final predictions. Experimental results show that the short-term traffic flow forecasting model basedon BAS-VMD-CEEMDAN-IWOA-RF has a high accuracy compared to other decomposition models. © 2023 IEEE.

关键词： Forecasting

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Neighborhood node selection strategy for blockchain networks based on Boltzmann method 5

Neighborhood node selection strategy for blockchain networks...

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5th international conference on Computer Information Science and Artificial Intelligence, CISAI 2022

作者： Chen, Zhuo Wang, GuoAn Zhou, Chuan Dept of Computer Science and Engineering Chongqing University of Technology 69 Redlight Ave Chongqing China

ISBN: (纸本)9781510662520

In view of the low block propagation efficiency in the blockchain network, which leads to the low throughput and high acknowledgement delay of the blockchain system, a dynamic node neighbor selection strategy is designed. According to the node elimination rate, neighbor nodes are divided into reserved nodes and replacement nodes. First, all possible combinations of neighbor node replacement are found by using the combination rule. then, when determining the strategy of each round, the neighbor node with good transmission timeliness is selected as the reserved node to improve the block transmission efficiency. the selection process of reserved nodes is regarded as a multi arm bandit problem, and a mathematical model is established by using Boltzmann selection strategy. the parameters of the strategy, such as node elimination rate and average propagation delay, are analyzed and verified by simulation experiments. the experimental results show that this strategy can optimize the topology of the blockchain network and effectively reduce the average propagation delay of the blockchain network. © 2023 SPIE.

关键词： Network topology

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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...

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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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