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kProtoClust:Towards Adaptive k-Prototype Clustering without Known k

Computers, Materials & Continua 2025年第3期82卷 4949-4976页

作者： Yuan Ping Huina Li Chun Guo Bin Hao School of Information Engineering Xuchang UniversityXuchang461000China Henan Province Engineering Technology Research Center of Big Data Security andApplications Xuchang461000China College of Computer Science and Technology Guizhou UniversityGuiyang550025China Here Data Technology Shenzhen518000China

Towards optimal k-prototype discovery,k-means-like algorithms give us inspirations of central samples collection,yet the unstable seed samples selection,the hypothesis of a circle-like pattern,and the unknown K are still challenges,particularly for non-predetermined data *** propose an adaptive k-prototype clustering method(kProtoClust)which launches cluster exploration with a sketchy division of K clusters and finds evidence for splitting and *** behalf of a group of data samples,support vectors and outliers from the perspective of support vector data description are not the appropriate candidates for prototypes,while inner samples become the first candidates for instability reduction of *** from the representation of samples in traditional,we extend sample selection by encouraging fictitious samples to emphasize the representativeness of *** get out of the circle-like pattern limitation,we introduce a convex decomposition-based strategy of one-cluster-multiple-prototypes in which convex hulls of varying sizes are prototypes,and accurate connection analysis makes the support of arbitrary cluster shapes *** by geometry,the three presented strategies make kProtoClust bypassing the K dependence well with the global and local position relationship analysis for data *** results on twelve datasets of irregular cluster shape or high dimension suggest that kProtoClust handles arbitrary cluster shapes with prominent accuracy even without the prior knowledge K.

关键词： Prototype finding convex hull support vector data description geometrical information

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System Report for CCL24-Eval Task 6: A Unified Multi-Task Learning Model for Chinese Essay Rhetoric Recognition and Component Extraction 23

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23rd Chinese National Conference on Computational Linguistics, CCL 2024

作者： Fang, Qin Zhang, Zheng Wang, Yifan Peng, Xian National Engineering Research Center of Educational Big Data Central China Normal University Wuhan China

ISBN: (纸本)9780000000002

In this paper, we present our system at CCL24-Eval Task 6: Chinese Essay Rhetoric Recognition and Understanding (CERRU). The CERRU task aims to identify and understand the use of rhetoric in student writing. The evaluation set three tracks to examine the recognition of rhetorical form, rhetorical content, and the extract of rhetorical components. Considering the potential correlation among the track tasks, we employ the unified multi-task learning architecture to fully incorporate the inherent interactions among the related tasks to improve the overall performance and to complete the above 3 track tasks with a single model. Specifically, the framework mainly consists of four sub-tasks: rhetorical device recognition, rhetorical form recognition, rhetorical content recognition, and rhetorical component extraction. The first three tasks are regarded as multi-label classification tasks, and the last task is regarded as an entity recognition task. The four tasks leverage potential information transfer to achieve fusion learning. Finally, the above four sub-tasks are integrated into a unified model through parameter sharing. In the final evaluation results, our system ranked fourth with a total score of 60.14, verifying the effectiveness of our approach. © 2024 China National Conference on Computational Linguistics.

关键词： Multi-task learning

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data-driven Analysis and Evaluation of Pedagogical Innovation 4

Data-driven Analysis and Evaluation of Pedagogical Innovatio...

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4th International Conference on Educational Technology, ICET 2024

作者： Cui, Mengjie Li, Yangyang He, Xiuling Zhou, Ruijie Central China Normal University National Engineering Research Center of Educational Big Data Wuhan China

ISBN: (纸本)9798350376944

The Digital Competence Framework for Teachers released by the European Union aims to improve teachers' digital teaching competence, with the focus shifting from enhancing teachers' information technology application competence to supporting technology-supported pedagogical innovations. The evaluation of teachers' teaching should shift from the application competence of information technology to analyzing and evaluating teachers' pedagogical innovation and cultivating higher-order competence of students. This study investigates the analysis and evaluation method of teaching innovation supported by technology based on accompanying collected teachers' behaviors. 102 courses were selected as subjects. Firstly, the coding rules were explored on the basis of the PICRAT (Passive, Interactive, Creative-Replacement, Amplification, Transformation) framework, and the teachers' behaviors were automatically coded. Secondly, multiple analyses of teaching behaviors were conducted to identify three technologically supported levels of pedagogical innovation, i.e., the basic single type, the integrated progressive type, and the high-level integration type. This study will provide practical guidance for the development of teachers' digital competence. © 2024 IEEE.

关键词： Teaching

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Abnormal Clustering and Cross Slicing Transformer for Insect Fine-Grained Image Classification 2

Abnormal Clustering and Cross Slicing Transformer for Insect...

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2nd International Conference on Algorithm, Image Processing and Machine Vision, AIPMV 2024

作者： Mei, Aokun Huo, Hua Big Data and Computing Intelligence Engineering Technology Research Center School of Information Engineering Henan University of Science and Technology Big Data Analysis Laboratory of Henan Medical Luoyang471023 China

ISBN: (纸本)9798350390254

Insect fine-grained image classification is an application scenario in fine-grained image classification. It not only has the characteristics of small inter-class differences and large intra-class differences, but also has the difficulty that some categories have multiple life-stage forms, which makes the general fine-grained image classification model difficult to play a role in insect scenes. To this end, based on the Vision Transformer, we design a fine-grained classification network for insect images based on abnormal clustering and cross slicing, called ACCS-Trans. In the first stage of the model, we use segmentation and clustering operations to distinguish the special morphology of insects in those few-shot life stages. The model can avoid the interference of few-sample abnormal morphology on the class feature extraction of the current class during training. The second stage is the cross slicing module, which uses the anchor box of the image sample segmentation region in the first stage to cut the original sample image to form the main target image, which is used as the information supplement area of the original image. Finally, the image is divided into doubling patch groups by two vertical patch operations. In the third stage, we concatenate the multiplication patch group and input it into the Vision Transformer network for class feature extraction. We fully experiment with ACCS-Trans on two insect image datasets. Compared with the current mainstream fine-grained image classification models, ACCS- Trans achieves state-of-the-art effects on both datasets, and we do ablation experiments for each module. The effect of each module on our ACCS- Trans is analyzed. The excellent performance of our ACCS- Trans in insect scenes is verified in these experiments, these provide new ideas for the task of fine-grained classification of insect images. © 2024 IEEE.

关键词： Image segmentation

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Teaching Behavior in Elementary School Science Supported by an Intelligent Video Analytics Platform 4

Teaching Behavior in Elementary School Science Supported by ...

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4th International Conference on Educational Technology, ICET 2024

作者： Ding, Yuxin Jin, Yanyan Zhang, Qian Yuan, Pan Dai, Zhicheng Peng, Xian Central China Normal University National Engineering Research Center for Educational Big Data Wuhan China

ISBN: (纸本)9798350376944

In recent years, science education has increasingly been widely noticed and emphasized, and has become a new hotspot in subject teaching research. However, there is still a relative lack of research on classroom teaching behaviors in the integration of information technology and elementary school science. Therefore, this study analyzes teaching behaviors in the dimensions of classroom events, classroom discourse structure, teacher's attention, teacher's emotion, and teacher-student interaction through video analytics by using an intelligent video analytics platform to analyze a classroom video of an elementary school science teaching session that was launched using a tablet mobile device, in order to investigate teacher teaching behaviors and teacher-student interactions in the classroom of integrating information technology and elementary school science. It was found that the classroom atmosphere in the integrated classroom of information technology and elementary school science was lively and the teachers were in a positive emotion, but there were problems of uneven distribution of attention and insufficient teacher-student interaction. These problems were identified with the aim of providing teachers with specific guidelines to improve their teaching methods and strategies, and to help them utilize information technology more effectively to enhance teacher-student interactions, thereby enhancing teaching effectiveness. © 2024 IEEE.

关键词： elementary science information technology intelligent video analytics teaching behavior

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Exploration and Practice in the Construction of Simulation Experiment Platforms for Blockchain Teaching 24

Exploration and Practice in the Construction of Simulation E...

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8th International Conference on Education and Multimedia Technology, ICEMT 2024

作者： Cui, Bo Li, Ru Jia, Ru Yu, Mei-Ju Hou, Wen-Han Engineering Research Center of Ecological Big Data Ministry of Education Inner Mongolia University Hohhot China

ISBN: (纸本)9798400717611

As a key component of next-generation information technology, blockchain technology has been widely applied in fields such as finance, healthcare, and the Internet of Things, leading to a high demand for specialized talent. Despite the introduction of blockchain courses in graduate education by universities worldwide, several challenges persist, including the complexity of the technology and the difficulty of practical operations. To address these issues, the blockchain team at Inner Mongolia University developed a blockchain simulation experiment platform and integrated it into their teaching curriculum. This platform enhances students' understanding and interest in learning through graphical representation of blockchain operations. It offers real-time data visualization, record-keeping of experiments, and an interactive learning experience. The platform supports a range of experiments from basic to complex, covering various aspects of blockchain technology. This teaching approach not only enables students to better integrate theory with practice but also cultivates their innovative abilities and practical skills, contributing valuable talent to the future development of the blockchain industry. © 2024 Copyright held by the owner/author(s).

关键词： Blockchain

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research on AI Empowered Pen Writing Training 4

Research on AI Empowered Pen Writing Training

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4th International Conference on Educational Technology, ICET 2024

作者： Shi, Shanfei Ma, Wan Zhu, Chuang Shu, Jiangbo Central China Normal University National Engineering Research Center of Educational Big Data Wuhan China

ISBN: (纸本)9798350376944

In response to the problems of low efficiency, weak personalization, and lack of high-quality teachers in pen writing training for normal students, this paper proposes a multi-round training mode of pen writing for normal students based on the Xiaoya intelligent teaching platform. Relying on the AI-based quantitative evaluation of standardized Chinese character writing, this model provides a holistic and detailed evaluation from three dimensions: alignment, stretch and uniformity. In the detailed evaluation, it not only provides scores for handwriting samples but also feeds back detailed descriptions of the problems for each writing point, so that students can more accurately understand the handwriting problems in order to correct the writing errors more pertinently. © 2024 IEEE.

关键词： Students

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Cloud-Edge Computing Technology-Based Internet of Things System for Smart Classroom Environment

International Journal of Emerging Technologies in Learning

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International Journal of Emerging Technologies in Learning 2023年第8期18卷 79-96页

作者： Dai, Zhicheng Zhang, Qianqian Zhao, Liang Zhu, Xiaoliang Zhou, Dongbo National Engineering Research Center for E-learning Central China Normal University Wuhan China National Engineering Research Center of Educational Big Data Central China Normal University Wuhan China

Aiming at the many challenges faced by the current smart classroom environment under the traditional cloud computing model, such as excessive data volume causing high pressure on the central nodes, network congestion and real-time problems, an IoT system architecture based on cloud-edge computing technology is proposed. The architecture starts from the idea of distributing the data concentrated in the cloud center to the edge nodes, and consists of four parts: sensor layer, edge computing layer, core network layer and platform application layer, which are used to obtain multi-source heterogeneous data, configure edge nodes on demand, transmit information and provide various educational services, respectively. By storing, computing and analyzing part of the data through edge nodes, it can effectively relieve the computing pressure and storage pressure of the central cloud server and reduce the network latency, thus providing better assistance to the smart classroom environment. A survey was also conducted by means of questionnaires to teachers and students in the smart classrooms of a Chinese university where the proposed system was implemented. The results show that 100.00% of the teachers and 97.14% of the students who participated in the questionnaire survey think that the system can effectively collect educational data and give feedback to students, 96.00% of the teachers and 91.43% of the students think that it can facilitate classroom teaching and bring enjoyable experience to teachers and students, and the overall satisfaction of students and teachers is high. Therefore, the proposed IoT system architecture based on cloud-edge computing technology is fully feasible and can provide a reference for the research, construction and application of smart classroom environment © 2023, International Journal of Emerging Technologies in *** Rights Reserved.

关键词： Students

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Hybrid Evaluation for Occlusion-based Explanations on CNN Inference Queries 40

Hybrid Evaluation for Occlusion-based Explanations on CNN In...

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40th IEEE International Conference on data engineering, ICDE 2024

作者： Ding, Guangyao Xu, Chen Qian, Weining School of Data Science and Engineering East China Normal University Shanghai200062 China Shanghai Engineering Research Center of Big Data Management China

ISBN: (纸本)9798350317152

Deep CNNs are increasingly prevalent in various application domains such as image processing. To explain a CNN prediction, it is popular to employ occlusion-based explanations (OBE). OBE helps users understand which parts of an image are important to a CNN prediction. Existing systems have explored incremental evaluation to accelerate CNN inference in OBE. However, they are oblivious that incremental evaluation does not always outperform full evaluation for certain layers. To address this issue, we propose a hybrid evaluation to efficiently interleave full and incremental evaluations during the CNN inference. Ad-ditionally, it employs a cost model to compare the overhead costs of two types of evaluations and a heuristic method to determine the efficient plan combination for common CNNs. More impor-tantly, hybrid evaluation adopts a dynamic programming-based method for attention-based CNNs. In particular, the dynamic programming-based method significantly reduces the overhead of searching for the efficient plan combination on the complex DAG structure. To demonstrate the efficiency of our techniques, we implement HyInJ, a hybrid CNN inf erence system based on PyTorch. Our experiments show that HyInf reduces execution time by up to 22% on GPU and 55% on CPU in comparison to the state-of-the-art incremental evaluation. © 2024 IEEE.

关键词： Dynamic programming

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Precise control of page cache for containers

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Frontiers of Computer Science 2024年第2期18卷 17-30页

作者： Kun WANG Song WU Shengbang LI Zhuo HUANG Hao FAN Chen YU Hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing Lab School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China

Container-based virtualization isbecoming increasingly popular in cloud computing due to its efficiency and *** isolation is a fundamental property of *** works have indicated weak resource isolation could cause significant performance degradation for containerized applications and enhanced resource ***,current studies have almost not discussed the isolation problems of page cache which is a key resource for *** leverage memory cgroup to control page cache ***,existing policy introduces two major problems in a container-based ***,containers can utilize more memory than limited by their cgroup,effectively breaking memory ***,the Os kernel has to evict page cache to make space for newly-arrived memory requests,slowing down containerized *** paper performs an empirical study of these problems and demonstrates the performance impacts on containerized *** we propose pCache(precise control of page cache)to address the problems by dividing page cache into private and shared and controlling both kinds of page cache separately and *** do so,pCache leverages two new technologies:fair account(f-account)and evict on demand(EoD).F-account splits the shared page cache charging based on per-container share to prevent containers from using memory for free,enhancing memory *** EoD reduces unnecessary page cache evictions to avoid the performance *** evaluation results demonstrate that our system can effectively enhance memory isolation for containers and achieve substantial performance improvement over the original page cache management policy.

关键词： page cache memory cgroup container isolation cloud computing

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