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International Conference on Artificial Intelligence and Education (ICAIE)

作者： Lining Liu Yongsheng Zhang Penglong Zhang Wenqian Sun School of Information Science and Engineering Shandong Normal University Jinan China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan China

ISBN: (数字)9781728166599

ISBN: (纸本)9781728199207

The arrival of the era of artificial intelligence has a great impact on the produce of relationship and mode, resulting in changes in the demand for talents. As an important place to train professional and technical talents, secondary vocational schools need teachers to make changes. Teachers should improve their own educational and teaching ability, and cultivate talents of high-quality, innovative and in line with the needs of social development. By analyzing the development status of artificial intelligence in the field of education and the current students' problems facing teachers (students' characteristics), this paper gives some ideals and suggestions on the development of professional ability of secondary vocational teachers in the era of artificial intelligence.

关键词： Quality function deployment Radio frequency Education Artificial intelligence

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Visualization of fluid simulation: An SPH-based multi-resolution method

Visualization of fluid simulation: An SPH-based multi-resolu...

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作者： Zhang, Guijuan Lu, Dianjie Liu, Hong School of Information Science and Engineering Shandong Normal University Jinan China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan China

Fluid simulation is an important research topic since it is widely used in virtual training, education, computer games, and digital entertainment. Generating fluid simulation results with high degree of visual realism is challenging in these applications. We present a visualization approach for fluid simulation in this paper. Our method allows students to understand the complex natural phenomena so as to solve the fluid engineering problems intuitively. In this study, an SPH (Smoothed Particle Hydrodynamics)-based multi-resolution method is proposed for fluid simulation. The method can keep the accuracy while improve the efficiency significantly. We construct a multi-resolution fluid model from bottom to top by combining fluid computation and surface reconstruction. We first compute multi-resolution particles with a novel adaptive SPH model in the bottom layer. Next, surface particles are extracted and pre-processed to provide samples for surface extraction. Then, the multi-resolution surface reconstruction model is built in the top layer. Meshes from different reconstruction resolutions are merged to obtain the final fluid surface. Experimental results show that our approach can effectively represent multi-scale fluid details and efficiently produce visual-pleasing fluid simulation results. © 2018 John Wiley & Sons, Ltd.

关键词： Visualization

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Can LLMs like GPT-4 outperform traditional AI tools in dementia diagnosis? Maybe, but not today

arXiv

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arXiv 2023年

作者： Wang, Zhuo Li, Rongzhen Dong, Bowen Wang, Jie Li, Xiuxing Liu, Ning Mao, Chenhui Zhang, Wei Dong, Liling Gao, Jing Wang, Jianyong Department of Computer Science and Technology Tsinghua University China Department of Neurology State Key Laboratory of Complex Severe and Rare Diseases Peking Union Medical College Hospital Chinese Academy of Medical Science Peking Union Medical College China The First Affiliated Hospital of Nanchang University China China University of Chinese Academy of Sciences China School of Computer Science and Technology East China Normal University China School of Software Shandong University China

Recent investigations show that large language models (LLMs), specifically GPT-4, not only have remarkable capabilities in common Natural Language Processing (NLP) tasks but also exhibit human-level performance on various professional and academic benchmarks. However, whether GPT-4 can be directly used in practical applications and replace traditional artificial intelligence (AI) tools in specialized domains requires further experimental validation. In this paper, we explore the potential of LLMs such as GPT-4 to outperform traditional AI tools in dementia diagnosis. Comprehensive comparisons between GPT-4 and traditional AI tools are conducted to examine their diagnostic accuracy in a clinical setting. Experimental results on two real clinical datasets show that, although LLMs like GPT-4 demonstrate potential for future advancements in dementia diagnosis, they currently do not surpass the performance of traditional AI tools. The interpretability and faithfulness of GPT-4 are also evaluated by comparison with real doctors. We discuss the limitations of GPT-4 in its current state and propose future research directions to enhance GPT-4 in dementia diagnosis. Copyright © 2023, The Authors. All rights reserved.

关键词： Benchmarking

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Mandari: Multi-Modal Temporal Knowledge Graph-aware Sub-graph Embedding for Next-POI Recommendation

Mandari: Multi-Modal Temporal Knowledge Graph-aware Sub-grap...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Xiaoqian Liu Xiuyun Li Yuan Cao Fan Zhang Xiongnan Jin Jinpeng Chen School of Computer Science (National Pilot Software Engineering School) Beijing University of Posts and Telecommunications Beijing China Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education Beijing China The Technology Innovation Center of Cultural Tourism Big Data of Hebei Province Chengde China Hebei Normal University for Nationalities Chengde China Knowledge Discovery and Data Mining Research Center Zhejiang Lab Hangzhou China

Next-POI recommendation aims to explore from user check-in sequence to predict the next possible location to be visited. Existing methods are often difficult to model the implicit association of multi-modal data with user choices. Moreover, traditional methods struggle to fully explore the variation of user preferences at variable time intervals. To tackle these limitations, we propose a Multi-Modal Temporal Knowledge Graph-aware Sub-graph Embedding approach (Mandari). We first construct a novel Multi-Modal Temporal Knowledge Graph. Based on the proposed knowledge graph, we integrate multi-modal information and leverage the graph attention network to calculate sub-graph prediction probability. Next, we implement a temporal knowledge mining method to model the segmentation and periodicity of user check-in and obtain temporal prediction probability. Finally, we fuse temporal prediction probability with the previous sub-graph prediction probability to obtain the final result. Extensive experiments demonstrate that our approach outperforms existing state-of-the-art methods.

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Research on college teachers teaching ability evaluation model based on DHNN 10

Research on college teachers teaching ability evaluation mod...

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10th International Conference on Information technology in Medicine and Education, ITME 2019

作者： Zhang, Jie Zhang, Yongsheng Wei, Yu Zheng, Zhihua Fan, Shaojun School of Information Science and Engineering Shandong Normal University Jinan250358 China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan250358 China

ISBN: (纸本)9781728139173

The teaching ability of teachers is one of the core abilities of colleges. Its level has gradually become an important indicator for evaluating a school. However, the existing evaluation models of college teachers are timeconsuming, empirical, complex, subjective and speculative. Therefore, based on the teaching features of colleges in China, this paper constructs a fast and effective college teacher evaluation model by discrete Hopfield neural network technology, and introduces the basic ideas and steps of the model. © 2019 IEEE.

关键词： Hopfield neural networks

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Research on education resource recommendation algorithm based on implicit feedback and pairwise 10

Research on education resource recommendation algorithm base...

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10th International Conference on Information technology in Medicine and Education, ITME 2019

作者： Huang, Xiaoxiang Zhang, Yongsheng Zheng, Zhihua Zhang, Jie Duan, Jiaxi School of Information Science and Engineering Shandong Normal University Jinan250358 China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan250358 China

ISBN: (纸本)9781728139173

In view of the problem of how to improve the accuracy of education resources recommendation in Internet era, a recommendation algorithm based on implicit feedback and pairwise education resources are proposed. Firstly, the feature extraction of learner-education resource is carried out, and the implicit features of learner-education resource are extracted by implicit semantic model, and the prediction results of factor decomposition are used as input to sorting learning algorithm. Converting sorting problems to classification problems uses the theory of ordering learning. Based on the experiment comparison with the traditional recommendation algorithm, it is compared with the comparison algorithm, which has better effect on the recommendation of educational resources. The algorithm increases by nearly 30% on metrics MAP, NDGG. © 2019 IEEE.

关键词： Learning algorithms

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The study of searchable encryption mechanism

The study of searchable encryption mechanism

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International Conference on Intelligent Computing, Communication and Devices, ICCD 2017

作者： Cui, Ranran Zhang, Yongsheng Li, Nengneng School of Information Science and Engineering Shandong Normal University Jinan250358 China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan250358 China

ISBN: (纸本)9789811089435

With the development of information technology, more and more data information uploaded to the cloud server, cloud computing encryption storage technology for data security has become particularly important. This paper mainly studies and analyzes the searchable encryption technology in cloud computing. Firstly, the research status of domestic and foreign research is analyzed. Secondly, the classification of searchable encryption technology is introduced from different aspects, and the classification model of searchable encryption technology A detailed elaboration. Finally, some problems encountered in searchable confidentiality technology and the prospect of this technology are introduced. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Cryptography

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A patient outcome prediction based on random forest 19

A patient outcome prediction based on random forest

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4th International Conference on Crowd Science and Engineering, ICCSE 2019

作者： Yang, Shan Zheng, Xiangwei Yuan, Feng School of Information Science and Engineering Shandong Normal University Ji'nan China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Ji’nan China

ISBN: (纸本)9781450376402

Since the research and development value of electronic health records (EHRs) which contains a large number of patient treatment data is very high and meaningful, EHRs has gained attention by researchers in recent years. EHRs has some characteristics such as temporality, sparsity, complexity, irregularity, noisiness and so on, which bring many challenges to direct study the medical data. Thus, an effective feature extraction, or phenotyping from patient EHRs is a key step before any further applications. In this paper, MIMIC-III intensive care database is selected for the experiments. To predict the patient’s death outcome (namely death due to illness or still alive), we make full use of the visit records of patients and propose a prediction method that combines the medical concept representation model Med2Vec with random forest algorithm. Experimental results indicate that the proposed method is robust to parameter variations and noise. Besides, compared with other prediction methods, the performance metrics of the proposed method are very well. Finally, the effect of the Med2Vec model is superior to that obtained by raw data (i.e., no feature learning applied to EHRs data). © 2019 Association for Computing Machinery. All rights reserved.

关键词： Forecasting

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Research and implementation of teaching system for higher vocational specialty courses based on hybrid teaching mode 10

Research and implementation of teaching system for higher vo...

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10th International Conference on Information technology in Medicine and Education, ITME 2019

作者： Zhang, Penglong Zhang, Yongsheng Fan, Shaojun Huang, Xiaoxiang Zhang, Jie School of Information Science and Engineering Shandong Normal University Jinan250358 China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan250358 China

ISBN: (纸本)9781728139173

In recent years, with the diversified development of education and training in China and the continuous 'Internet +', enterprises and society have put forward higher requirements for the ability of skilled talents. However, in the vocational specialty colleges that transport a large number of skilled talents, it is increasingly difficult to meet the needs of students' learning and development. At the same time, it is difficult for students to select appropriate content for independent learning in the vast information on the Internet. Hybrid teaching is a teaching mode that combines the advantages of both traditional teaching and networked teaching. The specialty courses teaching system is based on hybrid teaching mode. It uses Java Web technology as the basis for adopting B/S development mode, MySQL database and eclipse, Navicat as Development tools. The research and implementation of the hybrid teaching system is conducive to the school to help bridging the communication between the students and the enterprise, so that students can learn more directly and provide high-skilled talents with basic professional knowledge and skilled skills. On the other hand, through practice, it also helps to promote the development of hybrid teaching reform, thus solving the complexity and particularity of the informationization process in higher vocational colleges. © 2019 IEEE.

关键词： Teaching

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A grouping approach based on non-uniform binary grid partitioning for crowd evacuation simulation

A grouping approach based on non-uniform binary grid partiti...

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作者： Liu, Hong Li, Yan Li, Wenhao Lu, Dianjie Zhang, Guijuan School of Information Science and Engineering Shandong Normal University Jinan China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan China University of South Australia Adelaide Australia

Small social groups based on kinship or friendships are ubiquitous in human crowds. Therefore, the effect of social groups on crowd evacuations and that of crowd evacuations on social groups must be investigated. To simulate the group phenomenon when an emergency occurs, we propose an improved social force model that takes into account the social group relationship among the population, and based on our proposed model, a novel grouping algorithm predicated on non-uniform binary grid partitioning is put forward. The approach initially maps the individuals into the plane space, and then it adopts top-down binary grid partitioning iteratively until the divided grid contains only the individuals with relations;then, the values of the relation and density of the non-empty grid cells are calculated, and the grids are sorted according to these values. After sorting, selecting, merging, and forming the core grids, the other grids are merged to the core grids. We have compared the algorithm with the hierarchical classification algorithm and the grid-based algorithm. The results show that the accuracy, speed, and scalability are all advantages. We also establish a simulation platform to illustrate the proposed grouping algorithm and the improved social force model for crowd evacuation simulation. © 2018 John Wiley & Sons, Ltd.

关键词： Simulation platform

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