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Thoughts on the Development of Digital Employee 1

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6th international conference on Edge computing, EDGE 2022, held as part of the Services conference Federation, SCF 2022

作者： Liu, Feng Ning, Yishuang Yu, Xiaoquan Zou, Maotao Kingdee Research Kingdee International Software Group Company Limited Wan Chai China

ISBN: (数字)9783031234705

ISBN: (纸本)9783031234699

In recent years, the demographic dividend of the global market has gradually been exhausted. Enterprises are facing the dual pressure of labor costs and increasing pressure of market competition, and the demand for digital transformation has further expanded, with the iterative update of robotic processing automation (RPA), artificial intelligence (AI), big data and other technologies. As the most active element of the three elements of productivity, workers are also on the verge of technological explosion, and the concept of digital employee has also come into being. This paper introduces the digital employee's background, definition and key technologies, and explains the reasons and significance of the birth from a social theory perspective. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Competition

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Evaluation of Smart Campus Educational Management System 22

Evaluation of Smart Campus Educational Management System

引用

6th international conference on Education and Multimedia Technology, ICEMT 2022

作者： Li, Xiao-Nian He, Bo Sun, Jun-Min Nie, Li-Xia Cao, Jian-Ying Li, Fang-Fang School of Information Engineering Longdong University Gansu Qingyang745000 China National Engineering Laboratory for Educational Big Data Central China Normal University Hubei Wuhan430079 China

ISBN: (纸本)9781450396455

With the development of artificial intelligence, big data, cloud computing, and other new technologies. The design and construction of smart campus has become a research hotspot. The smart campus, as a platform of educational management, provides a lot of services for the teaching and management of schools. Therefore, it is necessary to comprehensively evaluate the construction of educational management system. This paper constructs the comprehensive evaluation system of the educational management system. Firstly, it constructs the comprehensive evaluation index system of the educational management system. Secondly, the analytic hierarchy process (AHP) is used to determine the weight of indicators at all levels. Finally, the fuzzy comprehensive evaluation method (FCE) is used to calculate the quantitative score of the evaluation object. Through the comprehensive evaluation and analysis of the educational management system of Longdong University, Verify the effectiveness of the evaluation process and methods. At the same time, it provides guidance for the construction of an intelligent campus educational management system. © 2022 ACM.

关键词： Analytic hierarchy process

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Why Transformers Need Adam: A Hessian Perspective 38

Why Transformers Need Adam: A Hessian Perspective

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38th conference on Neural Information Processing Systems, NeurIPS 2024

作者： Zhang, Yushun Chen, Congliang Ding, Tian Li, Ziniu Sun, Ruoyu Luo, Zhi-Quan The Chinese University of Hong Kong Shenzhen China Shenzhen International Center for Industrial and Applied Mathematics Shenzhen China Shenzhen Research Institute of Big Data Shenzhen China

SGD performs worse than Adam by a significant margin on Transformers, but the reason remains unclear. In this work, we provide an explanation through the lens of Hessian: (i) Transformers are "heterogeneous": the Hessian spectrum across parameter blocks vary dramatically, a phenomenon we call "block heterogeneity";(ii) Heterogeneity hampers SGD: SGD performs worse than Adam on problems with block heterogeneity. To validate (i) and (ii), we check various Transformers, CNNs, MLPs, and quadratic problems, and find that SGD can perform on par with Adam on problems without block heterogeneity, but performs worse than Adam when the heterogeneity exists. Our initial theoretical analysis indicates that SGD performs worse because it applies one single learning rate to all blocks, which cannot handle the heterogeneity among blocks. This limitation could be ameliorated if we use coordinate-wise learning rates, as designed in Adam. © 2024 Neural information processing systems foundation. All rights reserved.

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Visualization and Reliability Analysis for Edge computing Open Source Software

Visualization and Reliability Analysis for Edge Computing ...

引用

Thematic area Human Interface and the Management of Information, HIMI 2022 Part of the 24th HCI international conference, HCII 2022

作者： Tamura, Yoshinobu Anand, Adarsh Yamada, Shigeru Yamaguchi University Yamaguchi Japan University of Delhi Delhi India Tottori University Tottori Japan

ISBN: (纸本)9783031064234

At present, there are various software services by using the cloud computing. In particular, the edge computing expanded from the cloud computing is embedded in various situation because of the avoidance of whole system down. Also, the technologies of cloud services based on edge computing and 5G are very important to keep our convenient lifestyles. The appropriate control of the software faults detected in OSS project will directly relate to the quality, reliability, and cost. In particular, the fault correction time is very important factor in order to keep the edge computing service. We focus on the visualization of the estimation results of fault correction time for the assessment of operation performance of edge computing open source software. Then, we discuss the estimation method of fault correction time based on the characteristics of several components by using the deep leaning. We use the deep learning in order to estimate the fault correction time. In particular, we discuss the characteristics of fault trend by using the three dimensional graphs as the visualization of fault big data. Thereby, we can show the recognizability of the proposed method for fault big scale data based on deep learning from the standpoint of edge open source software. In particular, this paper analyzes the fault correction time from the standpoint of the characteristics in the fault content for the actual data sets. Then, we make a visualization based on three dimensional graph by using the estimation method based on deep learning. Moreover, we discuss the estimation results obtained from the three dimensional graphs. Furthermore, we show several numerical examples based on the proposed estimation method by using the actual fault big data. We analyze the fault big data in terms of the fault correction time in OSS component of edge computing in cloud computing in OpenStack. We can obtain the fault correction times from several characteristics of the factor in the bug tracking syst

关键词： Open source software

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Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networks

Nothing Stands Alone: Relational Fake News Detection with Hy...

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2022 IEEE international conference on big data, big data 2022

作者： Jeong, Ujun Ding, Kaize Cheng, Lu Guo, Ruocheng Shu, Kai Liu, Huan Arizona State University School of Computing and Augmented Intelligence United States University of Illinois Chicago Department of Computer Science United States Bytedance Ai Lab London United Kingdom Illinois Institute of Technology Department of Computer Science United States

ISBN: (纸本)9781665480451

Nowadays, fake news easily propagates through online social networks and becomes a grand threat to individuals and society. Assessing the authenticity of news is challenging due to its elaborately fabricated contents, making it difficult to obtain large-scale annotations for fake news data. Due to such data scarcity issues, detecting fake news tends to fail and overfit in the supervised setting. Recently, graph neural networks (GNNs) have been adopted to leverage the richer relational information among both labeled and unlabeled instances. Despite their promising results, they are inherently focused on pairwise relations between news, which can limit the expressive power for capturing fake news that spreads in a group-level. For example, detecting fake news can be more effective when we better understand relations between news pieces shared among susceptible users. To address those issues, we propose to leverage a hypergraph to represent group-wise interaction among news, while focusing on important news relations with its dual-level attention mechanism. Experiments based on two benchmark datasets show that our approach yields remarkable performance and maintains the high performance even with a small subset of labeled news data. © 2022 IEEE.

关键词： Graph neural networks

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Load balance and time delay efficient algorithm for VNF service chain deployment based on DQN 18

Load balance and time delay efficient algorithm for VNF serv...

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18th international conference on Computational intelligence and Security, CIS 2022

作者： Xuan, Hejun Lin, Lidan Liu, Zhenghui Zhao, Xuelin Xinyang Normal University Department of Computer and Information Technology China Big Data Xinyang Normal University Henan Key Laboratory of Analysis and Applications of Education Xinyang Henan China Luo He Vocational Technology College Department of Information Engineering Luohe Henan China

ISBN: (纸本)9798350346275

In mobile edge computing, computing and storage resources are close to the network of the user device, which can effectively reduce network access and computing service delay. However, network function virtualization for mobile edge computing networks is more challenging due to the strong coupling of CPU resources, storage resources, and wireless resources. In order to solve the problems of load balance and long response time of user-oriented service function chain deployment algorithm in mobile edge computing networks, this paper proposed a load balance and time delay efficient algorithm (denoted as LBDQN) for virtual network function service chain deployment problem based Deep Q-LearningFirst, a global optimization model, which minimizes time delay and maximizes the load balance, is established. Then, a new real-time algorithm for VNF service chain deployment based on DQN is proposed. In this algorithm, an adaptive ϵ-greedy method is designed. In addition, a particle swarm optimization is used to optimize the neural network parameters. To demonstrate the efficiency of the proposed algorithm, some simulation experiments are conducted and the experimental results show that the algorithm can effectively reduce the time delay and improve the load balance than the compared algorithms. © 2022 IEEE.

关键词： Time delay

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Analysing the Twitter Sentiments in COVID-19 Using Machine Learning Algorithms

Analysing the Twitter Sentiments in COVID-19 Using Machine L...

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2022 IEEE international conference on Advances in computing, Communication and Applied Informatics, ACCAI 2022

作者： Katarya, Rahul Nath, G Amar Singhal, Divit Shukla, Aryaman Delhi Technological University Big Data Analytics and Web Intelligence Laboratory Department of Computer Science Engineering New Delhi India

ISBN: (纸本)9781665495295

The coronavirus emanated in Wuhan city of China, in the last month of 2019 and was even announced as a global threat. Social media could be an utterly noteworthy supply of facts during a time of crisis. User-generated texts yield perception into users' minds withinside the direction of such times, giving us insights into their critiques in addition to moods. This venture examines Twitter messages (tweets) regarding people's sentiment on the unconventional coronavirus. The essential aim of sentiment evaluation is the origin of human emotion from messages or tweets. This venture is geared toward using numerous gadgets studying type algorithms to expect the people's reception of the worldwide pandemic by reading their tweets on Twitter. In the course of this paper, we are testing our dataset on five different classifiers, namely Random Forest, Logistic regression, Multinomial naive Bayes, K-nearest neighbor, and Support vector machines classifiers. Together with precision rankings and balanced accuracy rankings, metrics are offered to gauge the fulfilment of the numerous algorithms implemented. The K-Nearest Neighbor classifier has given the highest precision score while the Logistic Regression classifier gives the highest recall, F1, accuracy and balanced accuracy scores. © 2022 IEEE.

关键词： Coronavirus

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Abusive Language Detection with Graph based Multi-task Learning

Abusive Language Detection with Graph based Multi-task Learn...

引用

2022 IEEE international conference on big data, big data 2022

作者： Zhang, Chunyun Zhang, Xi Wang, Quan Liang, Jiayi Zhang, Ge Guo, Sanchuan Zang, Wenyu Zhang, Yongdong Beijing University of Posts and Telecommunications Beijing China Beijing Academy of Artificial Intelligence Beijing China China Electronics Corporation Beijing China University of Science and Technology of China Beijing China

ISBN: (纸本)9781665480451

To counter the online abusive language in social media, it is desirable to develop automated detection methods. Previous research has primarily formulated this problem as a sentence-level classification task, ignoring the crucial role of abusive lexicons that can strengthen the model explainability and enable more faithful predictions. Although a few methods have introduced the abusive lexicons for detection, the lexicons they use are either externally provided or labeled by human annotators, suffering from two limitations: (1) lack adaptability to diverse and evolving offensive scenarios;(2) require large human efforts to annotate the *** paper overcomes the limitations of prior work with a multi-task abusive language detection framework. It combines sentence-level and word-level classification tasks, based on dependency tree based graph attention networks (GAT). With the two tasks, it is encouraged to capture both global and local data properties to produce better sentence representations. It is also advantageous in automatic lexicon construction during the learning process, without human annotations. Extensive experiments on two public datasets exhibit that our proposal can outperform the state-of-the-art baselines. Case studies show that the model explainability can be strengthened with the abusive parts identified by our framework. Our code is released to public. 1 © 2022 IEEE.

关键词： Trees (mathematics)

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Research and Application of the data Resource Directory System of the Aerospace Enterprise 1

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11th international conference on big data, bigdata 2022, held as part of the Services conference Federation, SCF 2022

作者： Ma, Yuhan Ji, Cheng Fei, Tingwei Duan, Zhengxuan Luo, Jianchao Beijing Jinghang Research Institute of Computing and Communication Beijing100074 China

ISBN: (数字)9783031235016

ISBN: (纸本)9783031235009

The data resource of the aerospace enterprise have the problems of scattered data, multiple sources, inconsistent data, numerous interfaces, and inconsistent standard rules. It is necessary to carry out data governance work systematically. In order to improve the standardization of data governance work such as data classification, data sharing and data accountability of the aerospace enterprise, we research on the data resource directory system of the aerospace enterprise. We focus on the research of data resource directory standard, data resource inventory, and data resource directory framework. We introduce the application practice of the data resource directory system of the aerospace enterprise, which verifies the effectiveness and practicability of this system. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Classification (of information)

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A Grouping Design for Cascaded Coded Distributed computing 8

A Grouping Design for Cascaded Coded Distributed Computing

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8th IEEE international conference on Computer and Communications, ICCC 2022

作者： Dong, Hongyan Jiang, Jing Guangxi Key Laboratory of Multi-Source Information Mining and Security Guangxi Normal University Guilin China

ISBN: (纸本)9781665450515

In order to reduce the communication load in general distributed computing frameworks such as MapReduce Li et al. introduced coded distributed computing (CDC). The authors in [1] proposed a scheme for cascaded coded distributed computing on general networks. Although the numbers of input files and output functions in [1] are much less than those in [2], large numbers of input files and output functions are still required. In this paper, we present a new CDC scheme which 1) designs the assignments of input file and output function;2) requires less number of input files and output functions compared with those in the scheme derived by [1]. Meanwhile, the ratio of communication load to that of the scheme in [1] is less than 4/3. © 2022 IEEE.

关键词： Distributed computer systems

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