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16th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2024

作者： Gupta, Kishan Kesari Awasthi, Prashant Shaik, Mahaboobsubani Kaveri, Parag Ravikant Software Engineering Capgemini Technology Service Limited Chennai India Software Engineering Accenture Limited Liability Partnership Chicago United States Software Engineering Hilton Worldwide Holdings Inc McLean United States Symbiosis Institute of Computer Studies and Research Symbiosis International University Pune India

ISBN: (纸本)9798331505264

This study explores the edges, implementation processes, and commercialization standards for framework-agnostic JavaScript element libraries, concentrating on their role in making cross-framework compatible UI elements. Framework-agnostic component libraries offer an user-friendly solution that encourages programmers to create reusable components such as selectors, buttons, and input fields, that can be simply integrated across different frameworks, including Vue, Angular, and React. By consolidating elementary UI components into a single, versatile library, these libraries enhance styling consistency, facilitate development workflows, and minimize monotony and maintenance steps. Key benefits include enhanced cross-framework compatibility, reusability and consistency, lowered development overhead, and simplified maintenance, making these libraries necessary for scalable application development. The experiments provide realistic implementation techniques, such as employing JavaScript with React and the Module Federation library, segregating element logic from presentation, and preserving a constant API layout to increase usability and flexibility. Furthermore, this study surveys diverse commercial models and provides insights into how framework-independent element libraries can assemble for individual programmers and enterprises within the JavaScript ecosystem. Via these prototypes and practices, we demonstrate how these libraries allow efficient, scalable development and promote a cohesive design for UI management across diverse frontend frameworks. © 2024 IEEE.

关键词： Reusability

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Near Surface Layer Meteorological Observation System Based on Programmable Unmanned Aerial Vehicles 2

Near Surface Layer Meteorological Observation System Based o...

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2022 2nd International Conference on Mechanical Automation and Electronic Information engineering, MAEIE 2022

作者： Peng, Jiakai Lu, Jun Yang, Hong Liang, Lei Tang, Ran Zhang, Wei Zhao, Min School of Software Engineering Chengdu University of Information Technology China Sichuan Meteorological Service Center Sichuan Chengdu610225 China

With the rapid development of UAV (Unmanned Aerial Vehicle) technology, to give full play to the spatial flexibility of multi-rotor UAV, this paper designs and develops a programmable UAV-based near-surface layer meteorological observation system to achieve the measurement of meteorological data such as temperature, humidity, air pressure, wind, wind direction and particle concentration in the near-surface layer environment. The data obtained from the measurements are accurate and reliable, and have positive implications for scientific research in meteorology. The system makes good use of the portability and intelligence of the UAV, and can work in different environments and adapt well to all kinds of weather. In addition, the use of a microcontroller realizes the real-time transmission of detection data and ensures the timeliness and reliability of the data. And the ground station can also monitor and intelligently control the whole process of the UAV and complete a variety of different tasks. © Published under licence by IOP Publishing Ltd.

关键词： Meteorology

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Chinese Journal of Electronics 2021年第1期30卷 55-63页

作者： BO Lili ZHU Xuanrui SUN Xiaobing NI Zhen LI Bin School of Information Engineering Yangzhou University Jiangsu Engineering Research Center of Knowledge Management and Intelligent Service State Key Laboratory for Novel Software Technology Nanjing University

Fine-grained change operations can help software developers fix software bugs more accurately and efficiently. However, the current fine-grained change operations are only used in specific fixing process, such as fixing of If statement. In this paper, we conducted an empirical study to explore the fine-grained change operations for bug fixing. Based on the Mozilla bug data,we examined whether similar bugs are fixed with similar change operations. The results show that: First, for bug reports with similar descriptions or bug-fix commits with similar descriptions, their corresponding fine-grained change operations are not related; Second, in the case where the descriptions of both bug reports and bug-fix commits are similar, the fine-grained change operations in patch code are not related; Third, by classifying bug reports, we find that the change operations in the same bug report category are similar; Finally, by analyzing the fine-grained change operations for each bug, we present some combined patterns that are often used together.

关键词： bug reports bug fixing If statement Mozilla bug data bug-fix commits similar descriptions program debugging fine-grained change operations

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Multimodal Propaganda Detection Via Anti-Persuasion Prompt enhanced contrastive learning 48

Multimodal Propaganda Detection Via Anti-Persuasion Prompt e...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Cui, Jian Li, Lin Zhang, Xin Yuan, Jingling Wuhan University of Technology Wuhan China Engineering Research Center of Intelligent Service Technology for Digital Publishing China

ISBN: (纸本)9781728163277

Propaganda, commonly used in memes disinformation, can influence the thinking of the audience and increase the reach of communication. Usually logical fallacy, as a kind of popular expression of memes, aims to create a logical reasonable illusion where the conclusion cannot be drawn with the use of correct logic rules. However, this characteristic inherent in memes leads to difficulties for classic multi-label classifiers to understand propagation techniques. To this end, we propose a novel propaganda detection model called Antipersuasion Prompt Enhanced Contrastive Learning (abbreviated as APCL). First, our APCL reformulates the multi-label classification task by leveraging the category words of propaganda technique based prompt engineering, which is converted into an image-text matching (ITM). Second, prompt engineering is designed with a persuasion prompt template and an anti-persuasion prompt template. The former is to build matched text-image pairs, and the latter is to form mismatched text-image pairs which fit the logical fallacy style of memes. Finally, the propagation technique is predicted based on the distances between the above two prompt templates enhanced texts and an input image. Experimental results on the memes dataset of SemEval2021 task 6 show that our APCL outperforms the state-of-the-art multimodal classification models in terms of F1 measures. © 2023 IEEE.

关键词： Image enhancement

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Adaptive IoT Decision Making in Uncertain Environments 7

Adaptive IoT Decision Making in Uncertain Environments

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7th IEEE International Conference on Smart Internet of Things, SmartIoT 2023

作者： Wang, Yan Zheng, Liwei He, Jingjing Cui, Zhanqi Computer School Software Engineering Research Center Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9798350316575

The rapid growth of the Internet of Things (IoT) has led to widespread deployment of IoT systems in domains such as smart homes, healthcare, and transportation. However, IoT systems often operate under uncertainty, making it difficult to predict and control their behavior. In this paper, we propose an adaptive decision making approach for IoT systems in uncertain, dynamic environments. We present a framework with perception, decision and execution layers to handle uncertainty in IoT systems. The perception layer senses the environment and system state. The decision layer employs an optimized deep Q-network algorithm (Ad-DQN) specifically designed to handle uncertain environments, enabling it to make informed decisions based on learned experiences. The execution layer implements the actions. We demonstrate the framework on an intelligent air conditioning system as a case study of an IoT system operating under uncertainty. The Ad-DQN based decision layer adapts the air conditioning control policy to maximize comfort while minimizing energy usage. Experiments show our method outperforms traditional DQN method in uncertain environments. © 2023 IEEE.

关键词： Reinforcement learning

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The Numerical Model for Sarcoplasmic Reticulum Ca2+ Blink in Rabbit Cardiomyocytes 3

The Numerical Model for Sarcoplasmic Reticulum Ca2+ Blink in...

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3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing, CAMMIC 2023

作者： Liang, Yongshen Xu, Menghao Beijing Engineering Research Center for IoT Software and Systems Beijing University of Technology Beijing100124 China

ISBN: (纸本)9781510667600

Ca2+ in cardiac myocyte are mainly stored in the sarcoplasmic reticulum (SR), the disturbance of Ca2+ dynamics in the SR can cause various cardiovascular diseases. However, there is a lack of research on regulatory mechanism of SR Ca2+. In this paper, we developed a spatially-detailed numerical model for Ca2+ blink to analyze Ca2+ spatiotemporal dynamic characteristics in junctional SR (jSR) cisternae of rabbit cardiomyocytes. The geometric model is constructed by 2-dimensional unstructured triangular meshes with a combined method of Delaunay Triangulations (DT) and Advancing Front Technique (AFT). The numerical method for solving the governing equations adopts Basic Function Method based on unstructured triangular meshes. Finally, our model is well reproduced the SR Ca2+ kinetics of Ca2+ blink and simulated results well match the results of a recent biological experiment. © 2023 SPIE.

关键词： Numerical models

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Soft-GNN:towards robust graph neural networks via self-adaptive data utilization

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Frontiers of Computer Science 2025年第4期19卷 1-12页

作者： Yao WU Hong HUANG Yu SONG Hai JIN National Engineering Research Center for Big Data Technology and System Service Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China College of Information and Communication National University of Defense TechnologyWuhan 430019China Department of Computer Science and Operations Research Universitéde MontréalMontreal H3C 3J7Canada

Graph neural networks(GNNs)have gained traction and have been applied to various graph-based data analysis tasks due to their high ***,a major concern is their robustness,particularly when faced with graph data that has been deliberately or accidentally polluted with *** presents a challenge in learning robust GNNs under noisy *** address this issue,we propose a novel framework called Soft-GNN,which mitigates the influence of label noise by adapting the data utilized in *** approach employs a dynamic data utilization strategy that estimates adaptive weights based on prediction deviation,local deviation,and global *** better utilizing significant training samples and reducing the impact of label noise through dynamic data selection,GNNs are trained to be more *** evaluate the performance,robustness,generality,and complexity of our model on five real-world datasets,and our experimental results demonstrate the superiority of our approach over existing methods.

关键词： graph neural networks node classification label noise robustness

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Application of fractal theory to study morphology of manganese sulfide inclusion in resulfurized free-cutting steels

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Journal of Iron and Steel research International 2023年第1期30卷 137-149页

作者： Xiang-yu Xu Zhi-qi Zeng Qian-ren Tian Chen-wei Cao Ping Shen Jian-xun Fu Center for Advanced Solidification Technology(CAST) State Key Laboratory of Advanced Special SteelSchool of Materials Science and EngineeringShanghai UniversityShanghai 200444China Baosight Software Co. Ltd.Information Service HeadquartersShanghai 201203China

The morphology and distribution of manganese sulfide(MnS)inclusions have a significant influence on the comprehensive performance,which is an important research field for resulfurized *** on the experiments of non-aqueous electrolyte and scanning electron microscope observation,the fractal theory was employed to study the three-dimensional morphologies of MnS *** results showed that the edge fractal dimension of MnS inclusions was between 1.59 and *** addition,similar morphology of MnS inclusions had a close fractal *** MnS edge fractal dimension is highly positively correlated with the morphological *** multifractal spectrums of MnS inclusions on two-dimensional plane of as-cast and as-rolled resulfurized free-cutting steels were *** large-size MnS inclusions belong to large probability subset,while the small-size MnS inclusions belong to small probability *** multifractal spectrum can truly and effectively reflect the difference and non-uniformity of distribution of MnS inclusions on 2D *** the premise of similar content of MnS,with the refinement of MnS inclusions,the multifractal spectrum width and the multifractal spectrum symmetry parameter were *** multifractal spectrum provides a new method for studying the second phase in materials.

关键词： MnS inclusion Morphology Fractal dimension Multifractal Resulfurized steel

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Multi-station low-visibility prediction based on spatio-temporal fusion model

Multi-station low-visibility prediction based on spatio-temp...

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2024 International Conference on Image, Signal Processing, and Pattern Recognition, ISPP 2024

作者： Xiao, Nan Luo, Fei Cao, Liang College of Software Engineering Chengdu University of Information Technology Sichuan Chengdu China Yunnan R&D Institute of Natural Disaster Chengdu University of Information Technology Yunnan Kunming China Automatic Software Generation and Intelligent Service Key Laboratory of Sichuan Province Sichuan Chengdu China CMA - CUIT Meteorological Software Engineering Joint Research Center Sichuan Chengdu China

ISBN: (纸本)9781510680425

The accurate prediction of low-visibility has important application value to the normal operation of navigation, aviation and other transportation vehicles. However, the current low-visibility prediction task mostly uses time series model to extract temporal features, but neglects the spatial correlation between national observation stations. Additionally, those time series model require that the input data must be limited to the Euclidean space. However, due to the discrete distribution of stations, the input data required for multi-station low-visibility prediction does not have a regular spatial structure. To address those limitation, we proposed a weighted location feature convolution based on graph convolution. The construction of the weighted location feature convolution takes into account the distance and pitch angle, reduces the influence caused by the dispersion of national observation stations, and enables the convolution kernel to be shared in different local meteorological spaces. The convolution as a substitute for matrix multiplication within Sequence to Sequence framework, then cascaded the decoder to deal with the spatio-temporal dependence relationship of different levels, leading spatio-temporal fusion model CPGDC. The experimental results show that the CPGDC model achieves has higher accuracy in predicting low-visibility values across multiple national observation stations. © 2024 SPIE.

关键词： Input output programs

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Adversarial Defense based on Image Style Transfer 9

Adversarial Defense based on Image Style Transfer

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9th IEEE International Conference on Cloud Computing and Intelligence Systems, CCIS 2023

作者： He, Zhiquan Lv, Jiantu Lan, Xujia Shenzhen University Guangdong Multimedia Information Service Engineering Technology Research Center Shenzhen China

ISBN: (纸本)9798350304428

Recent research shows that deep neural network is vulnerable to the attack of adversarial samples, which leads to the incorrect output of the model. Therefore, the defense against adversarial attacks on deep learning models has become the hotspot of artificial intelligence security research. This paper proposes an image-processing-based defense method ADIST (Adversarial Defense Based on Image Style Transfer), which removes the adversarial perturbation from the input image by wavelet image restoration, multi-Template image style transfer, and feature modulation before the classification by the target classifying model. Specifically, the input image is style-Transferred multiple times using different style templates. In each style-Transfer branch, the input image is denoised by wavelet decomposed and reconstructed after randomly dropping a certain amount of high-frequency components. Then a feature encoder is applied to the reconstructed image and the style template to extract image features. The image features are further pruned by adaptive truncation to eliminate part of the antagonistic disturbance. Then, the semantic information of the input image is fused with the style-Template part to generate a new image by the style-Transfer module. Finally, the classification results for these multiple new images are combined to produce the final prediction. We have tested the proposed method using ResNet34 and WideResNet50 as the classification network on the Mini-ImageNet dataset. Under white box attack, the proposed method is 2.2% and 2.7% better than the most advanced RAIN method based on image preprocessing, respectively. © 2023 IEEE.

关键词： Image reconstruction

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