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2021 IEEE 4th International Conference on Information Systems and Computer Aided Education (ICISCAE)最新文献

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Research on Accurate Learning Evaluation for College Students Based on Big Data Technology 基于大数据技术的大学生准确学习评价研究
Zheng Liu, Shanshan Gao, Jing Chi, Huijian Han
In this paper, we propose a novel strategy to accurately evaluate learning status and development potentiality for colleges students based on big data modeling and mining. Firstly, we propose an effective method to calculate students ability achievement based on the big data mining technology via three steps. In step 1, we construct the student ability achievement evaluation system, which reflects the “output-oriented concept”. In step 2, we model the educational big data, which embodies the “continuous improvement concept”. In step 3, we compute students ability achievement based on educational big data mining, which embodies the “student-centered concept”. Secondly, we discuss how to accurately evaluate college students learning status and development potentiality based on the ability achievements. Finally, we conduct a series of experiments to demonstrate the effectiveness of the proposed solution. Experimental results demonstrate that the proposed solution can effectively evaluate learning status and development potentiality, moreover, the proposed solution can recommend suitable courses and career plannings for college students.
本文提出了一种基于大数据建模与挖掘的大学生学习现状与发展潜力评估策略。首先,我们提出了一种基于大数据挖掘技术的有效的学生能力成绩计算方法,分三步进行。第一步,构建学生能力成就评价体系,体现“产出导向”理念。第二步,我们对教育大数据进行建模,这体现了“持续改进理念”。第三步,基于教育大数据挖掘计算学生能力成就,体现了“以学生为中心”的理念。其次,探讨了如何基于能力成就来准确评价大学生的学习状况和发展潜力。最后,我们进行了一系列的实验来证明所提出的解决方案的有效性。实验结果表明,该方法可以有效地评价大学生的学习状况和发展潜力,并为大学生推荐合适的课程和职业规划。
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引用次数: 0
Research on Computer Network Information Security Protection Strategy and Evaluation Algorithm Based on Fuzzy Clustering 基于模糊聚类的计算机网络信息安全保护策略及评价算法研究
J. Duan
With the gradual improvement of the infrastructure of the information society, computer network information security has involved all aspects of people's lives. Therefore, computer network security has also affected the security and economic development of all walks of life when applying computer networks to some extent. Nowadays, all walks of life in society are closely related to computer networks, from state secrets to people's daily entertainment. From the computer's own defects and the related prediction of computer security in the future, it can be known that security is the direction that needs to be focused on at present, and the protective measures and evaluation algorithms for computer network information security need further research. In this paper, from the perspective of computer network information security, based on fuzzy clustering analysis, the computer network security protection problem is evaluated. The computer network information security protection strategy and evaluation algorithm introduced in this paper are of great significance for improving the computer network security level.
随着信息社会基础设施的逐步完善,计算机网络信息安全已经涉及到人们生活的方方面面。因此,在应用计算机网络时,计算机网络安全也在一定程度上影响着各行各业的安全和经济发展。如今,从国家机密到人们的日常娱乐,社会各行各业都与计算机网络密切相关。从计算机自身的缺陷和对未来计算机安全的相关预测可知,安全是目前需要重点关注的方向,计算机网络信息安全的防护措施和评估算法有待进一步研究。本文从计算机网络信息安全的角度出发,基于模糊聚类分析对计算机网络安全防护问题进行了评价。本文所介绍的计算机网络信息安全保护策略和评估算法对提高计算机网络安全水平具有重要意义。
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引用次数: 0
Experimental Teaching Platform Development for Topological Sorting Algorithm Education 拓扑排序算法教学实验教学平台的开发
Yabo Luo, Hongxi Teng
Job shop Scheduling Problem is an NP-hard combinatorial optimization problem. The research on its solving algorithm has been a hot topic, and many achievements have been made. However, due to the complexity of time and variable space in the solving process of job shop scheduling problems, teaching tools of scheduling algorithms are still lacking. To solve the problem, this paper takes a topological sorting algorithm to illustrate the design principle and solving instances of the scheduling algorithm for job shop scheduling problems. Firstly, the method of using a graph to express the correlation between operations is described. Secondly, the idea of the topological sorting algorithm for job shop scheduling is proposed, and the steps of algorithm programming are explained in detail. Thirdly, based on the case, the solving performance of the algorithm is analyzed, and the solving effect of the algorithm is expounded.
作业车间调度问题是一个NP-hard组合优化问题。对其求解算法的研究一直是一个热门话题,并取得了许多成果。然而,由于作业车间调度问题求解过程中时间和空间的复杂性,调度算法的教学工具仍然缺乏。为了解决这一问题,本文采用一种拓扑排序算法来说明作业车间调度问题调度算法的设计原理和求解实例。首先,描述了用图表示操作间关联关系的方法。其次,提出了作业车间调度拓扑排序算法的思想,并详细说明了算法的编程步骤。第三,结合实例分析了算法的求解性能,阐述了算法的求解效果。
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引用次数: 0
It is Time to Laugh: Discovering Specific Contexts for Laughter with Attention Mechanism 是时候笑了:用注意力机制发现笑的特定背景
Kaibin Xu, Junpei Zhong, Kristiina Jokinen
Based on previous studies on the co-occurrence between the types of laughter and conversation contents, this paper uses the attention mechanism to further study the types of laughter and the specific wording in the conversation. We assume that the types of laughter also co-occurs with specific words, as well as a certain pause, in the conversation. We have established a neural network learning model based on the attention mechanism. The results of our model show that certain words in the conversation are related to specific types of laughter.
本文在前人研究笑声类型与对话内容共现的基础上,运用注意机制进一步研究笑声类型和对话中的具体措辞。我们假设,在谈话中,笑声的类型也会与特定的词语以及特定的停顿同时出现。我们建立了一个基于注意机制的神经网络学习模型。我们模型的结果表明,谈话中的某些词与特定类型的笑声有关。
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引用次数: 0
Tanh discrete estimate for all-opical neural network based on MZI 基于MZI的全光神经网络Tanh离散估计
Ruizhen Wu, Ping Huang, Jingjing Chen, Lin Wang, Yan Wu, Mingming Wang
Optical neural networks (ONNs) can process information in parallel and have low energy advantages which researched more and more recently aims to replace the electrical Artificial neural networks (ANN s) solutions. The MZI with Gridnet or FFTnet can realize the convolution calculation is already proved by lots of researches. But the activation functions still have to use the DAC/ ADC to do the photoelectric conversion and then calculated in electronic-based hardware systems. We proposed a discrete estimate scheme for all-optical activation function in this paper. The scheme can give different accurate results with different implementation cost.
光神经网络(ONNs)具有并行处理信息和低能耗的优点,是近年来越来越多的研究旨在取代电人工神经网络(ANN)的解决方案。网格网或FFTnet的MZI可以实现卷积计算,这已经被大量的研究证明。但是在基于电子的硬件系统中,激活函数仍然需要使用DAC/ ADC进行光电转换然后计算。本文提出了一种全光激活函数的离散估计方案。在不同的实施成本下,该方案可以得到不同的精确结果。
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引用次数: 0
A model of information sharing based on isolated information system 基于孤立信息系统的信息共享模型
Zhou Bin
In order to solve the problem of information resource sharing caused by information isolated island, this paper proposes a cross system online information resource sharing platform model based on the existing information system of colleges and universities, which is role and transaction oriented. The online resource sharing platform based on this model establishes a specific structure of intermediate database on the basis of the existing isolated information system, adopts the strategy of non authoritative data accurate association matching authoritative data, realizes its interconnection with the existing system databases through specific program algorithm logic, constructs a distributed interconnected database, and realizes cross database data association matching. After solving the problem of information island fundamentally, an information resource sharing platform that can define any role or transaction can be built to meet the current cross system information resource sharing needs. Based on the existing system management information, the purpose of accurately sharing information across systems by roles or transactions through the new platform is realized. Through the implementation and practical application of the model technology, it is proved that it can better solve the problem of information resource sharing caused by information island, and realize the accurate cross system information resource sharing service.
为了解决信息孤岛导致的信息资源共享问题,本文在现有高校信息系统的基础上,提出了面向角色和面向交易的跨系统在线信息资源共享平台模型。基于该模型的在线资源共享平台在现有孤立信息系统的基础上建立特定结构的中间数据库,采用非权威数据精确关联匹配权威数据的策略,通过特定的程序算法逻辑实现其与现有系统数据库的互联,构建分布式互联数据库,实现跨数据库数据关联匹配。在从根本上解决了信息孤岛问题后,可以构建一个可以定义任意角色或事务的信息资源共享平台,以满足当前跨系统信息资源共享的需求。在现有系统管理信息的基础上,通过新平台实现了系统间按角色或事务准确共享信息的目的。通过模型技术的实施和实际应用,证明该模型技术能较好地解决信息孤岛导致的信息资源共享问题,实现准确的跨系统信息资源共享服务。
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引用次数: 0
Research on GAN-based Text Effects Style Transfer 基于gan的文本效果风格迁移研究
Yinquan Liu, Zhuang Chen
With the development of neural style transfer and generative adversarial network, the research of text effect style transfer has appeared. The text effect style transfer aims to render text images with style images to produce text effects images. However, for more complex text, the existing methods will generate unrecognizable font images. Therefore, we propose to add morphological methods to the glyph transformation to limit the degree of glyph transformation, and add distance transformation loss when training the texture network to limit the texture transfer, so as to improve the overall transformation effect. Experiments show that, compared with other existing technologies, our proposed method is more suitable for stylizing complex glyph images.
随着神经风格迁移和生成对抗网络的发展,文本效应风格迁移的研究应运而生。文本效果风格转换的目的是用样式图像渲染文本图像,产生文本效果图像。然而,对于更复杂的文本,现有的方法将产生无法识别的字体图像。因此,我们提出在字形变换中加入形态学方法来限制字形变换的程度,在纹理网络训练时加入距离变换损失来限制纹理转移,从而提高整体变换效果。实验表明,与其他现有技术相比,本文提出的方法更适合于复杂象形图像的风格化。
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引用次数: 0
Transient stability control system based on mapping cloud and online pre decision 基于映射云和在线预决策的暂态稳定控制系统
Xuhan Wu, Wentao Wang, Hong Wang
In order to reasonably describe the uncertainty of output of instruments and actuators, a concept of transient stability control based on online pre-decision of mapping cloud is proposed. This paper describes an online pre-decision transient stability control system developed by Electric Power Automation Research Institute, which integrates quantitative analysis technology of motion stability of nonautonomous nonlinear multi-rigid-body system, object-oriented distributed parallel processing platform and regional stability control device. The system online tracks the system working conditions using the stability margin index of the controlled power system provided by EEAC, and quickly searches for the control strategy that corresponds to a given fault set, satisfies a certain system stability margin value, and has the least control cost, so as to correct The development and change of the power grid and the change of operation mode have strong adaptive ability. The system is an organic combination of transient stability quantitative analysis technology EEAC and mature regional stability control device FWK, and is a new product of domestic safety and stability control technology.
为了合理描述仪器和执行器输出的不确定性,提出了一种基于映射云在线预决策的暂态稳定控制概念。本文介绍了电力自动化研究所开发的一种在线预决策暂态稳定控制系统,该系统集成了非自治非线性多刚体系统运动稳定性定量分析技术、面向对象的分布式并行处理平台和区域稳定控制装置。系统利用EEAC提供的被控电力系统稳定裕度指标在线跟踪系统工况,快速搜索对应于给定故障集、满足一定系统稳定裕度值、控制成本最小的控制策略,从而对电网的发展变化和运行方式的变化具有较强的自适应能力。该系统是暂态稳定定量分析技术EEAC与成熟的区域稳定控制装置FWK的有机结合,是国内安全稳定控制技术的新产物。
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引用次数: 0
Virtual Service Failure Recovery Algorithm Based on Particle Swarm in IPv6 Networks 基于粒子群的IPv6网络虚拟业务故障恢复算法
Jianwei Li, Zhibing Zhang, Kai-Zhong Zhou, Dan Luo
In a IPv6 network environment, how to restore as many virtual network services as possible under the constraints of limited resources is an urgent problem to be solved. To solve this problem, this paper models the virtual network service recovery problem as a problem of maximizing the number of failed services recovery. A particle swarm-based virtual service failure recovery algorithm in IPv6 networks is proposed. The algorithm first constructs the faulty resource and virtual service as a two-layer correlation model. Secondly, the network resource recovery problem is modeled as a particle swarm problem, and the particle swarm optimization algorithm is used to solve it. In the experimental part, by comparing with existing algorithms, it is verified that the algorithm in this paper can recover more virtual network services that have failed.
在IPv6网络环境下,如何在有限的资源约束下恢复尽可能多的虚拟网络业务是一个迫切需要解决的问题。为了解决这一问题,本文将虚拟网络服务恢复问题建模为服务恢复失败次数最大化的问题。提出了一种基于粒子群的IPv6网络虚拟业务故障恢复算法。该算法首先将故障资源和虚拟服务构建为两层关联模型;其次,将网络资源恢复问题建模为粒子群问题,并采用粒子群优化算法对其进行求解;在实验部分,通过与现有算法的比较,验证了本文算法能够恢复更多失效的虚拟网络服务。
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引用次数: 0
A Multi-Agent Reinforcement Learning Framework with Recurrent Communication Module for Traffic Light Control 基于循环通信模块的交通灯控制多智能体强化学习框架
Bo Qin, Wei He, Bin Zhang, Jingchen Li
As a significant issue in the development of Smart City, traffic light control is closely related to public transport. Multi-agent reinforcement learning is a feasible paradigm to control decentralized systems. In this work, we design a recurrent communication module for traffic light control systems. Aiming at lightweight decentralized learning, we decouple the interaction among entities, using an improved recurrent neural network to share messages. Regarding traffic lights as a partially observable Markov Decision Process, we develop a complete reinforcement learning model. Every light receives messages from its neighbors through the improved recurrent neural network. For the further lights, its neighbor lights can play the role of intermediation to transmit messages. By our communication framework, traffic lights can learn their control policies in a decentralized way, and distribution control can be executed through a communication channel. Several simulated experiments show that our method outperforms the fixed time method and the existing reinforcement learning-based frameworks under different traffic demands.
交通信号灯控制与公共交通密切相关,是智慧城市发展中的一个重要问题。多智能体强化学习是控制分散系统的一种可行范例。在本工作中,我们设计了一个用于交通灯控制系统的循环通信模块。针对轻量级去中心化学习,我们解耦了实体之间的交互,使用改进的递归神经网络来共享消息。将交通灯作为一个部分可观察的马尔可夫决策过程,我们开发了一个完整的强化学习模型。每一束光都通过改进的循环神经网络接收来自邻居的信息。对于更远的灯,它的邻居灯可以起到中介的作用来传输消息。通过我们的通信框架,交通灯可以以分散的方式学习控制策略,并通过通信通道执行分布式控制。多个仿真实验表明,在不同的交通需求下,该方法优于固定时间方法和现有的基于强化学习的框架。
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引用次数: 0
期刊
2021 IEEE 4th International Conference on Information Systems and Computer Aided Education (ICISCAE)
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