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12th International Conference on Information and Education Technology, ICIET 2024

作者： Xie, Cui Bai, Tao Liu, Xiudong Dong, Junyu Chang, Xiaofeng Li, Yun College Of Computer Science & Technology Ocean University Of China Qingdao China Basic Teaching Center Ocean University Of China Qingdao China Ocean University Of China Educational Adminstration Office Qingdao China

ISBN: (纸本)9798350371772

Machine learning based academic performance prediction of students is showing great significance in ensuring the good quality of higher education. However, most methods only focus on predicting academic performance in a single aspect (such as only grade) or for students in a single Major. To address this issue, this paper designs an academic multi-task prediction network model called AMPNet for both grade prediction and graduation prediction of all majors in universities. It consists of three parts: the LSTM part, attention part, and feature fusion part. The LSTM part extracts the time series features of students' historical terms and predicts the grade points of the next term. Then these features are further refined by the terms and attributes attention part. Finally, the refined features are input into the feature fusion part, concatenating the input major delay-graduation embedding, and outputs the prediction results of both grade and graduation status. Comparative experiments show that the proposed AMPNet model provides good performance in grade point prediction, and it significantly outperforms mainstream machine learning prediction models in graduation prediction, and ablation experiments demonstrate the effectiveness of three key modules: major delay-graduation embedding, terms attention, and attributes attention. © 2024 IEEE.

关键词： Forecasting

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Hierarchical Encryption in a Residual Number System 14

Hierarchical Encryption in a Residual Number System

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14th International Conference on Advanced computer Information Technologies, ACIT 2024

作者： Yakymenko, Igor Martyniuk, Olesya Martyniuk, Serhii Martyniuk, Andrii Yakymenko, Yurii Kasianchuk, Mykhailo West Ukrainian National University Department of Cyber Security Ternopil Ukraine West Ukrainian National University Department of Applied Mathematies Ternopil Ukraine Ternopil Volodymyr Hnatiuk National Pedagogical University Department of Computer Science and Teaching Methods Ternopil Ukraine Taras Shevchenko National University of Kyiv Faculty of Mechanics and Mathematics Kyiv Ukraine

ISBN: (纸本)9798350350036

Within this article, a method of symmetric encryption of information based on a hierarchical residue number system has been developed. The corresponding mathematical and algorithmic framework is presented. The proposed approach simplifies hardware implementation and enhances operational speed by reducing modulus sizes and consequently numerical operands at each subsequent level, as well as by parallelizing computational processes. Utilizing this encryption method enables the creation of reliable, efficient, and resistant-to-cryptanalysis systems for protecting information streams. A encryption/decryption scheme and an application example of the method are provided. © 2024 IEEE.

关键词： Encryption algorithms

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Numerical study of valence band states evolution in AlxGa1-xAs QDs systems

PeerJ Materials Science

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PeerJ Materials science 2024年 6卷 e32-e32页

作者： Lazarev, Mikhail Faculty of Computer Science Laboratory of Methods for Big Data Analysis HSE University Moscow Russia

Quantum dots (QDs) are very attractive nanostructures from an application point of view due to their unique optical properties. Optical properties and valence band (VB) state character was numerically investigated with respect to the effects of nanostructure geometry and composition. Numerical simulation was carried out using the Luttinger–Kohn model adapted to the particular case of QDs in inverted pyramids. We present the source code of the 4-band Luttinger–Kohn model that can be used to model AlGaAs or InGaAs nanostructures. The work focuses on the optical properties of GaAs/AlGaAs [111] QDs and quantum dot molecules (QDMs). We examine the dependence of Ground State (GS) optical properties on the structural parameters and predict optimal parameters of the QD/QDM systems to achieve dynamic control of GS polarization by an applied electric field. © 2024 Lazarev.

关键词： Polarization

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Using Peer Tutoring to Bolster Retention Rates and Student Performance in CS1 Courses 56

Using Peer Tutoring to Bolster Retention Rates and Student P...

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56th Annual SIGCSE Technical Symposium on computer science Education, SIGCSE TS 2025

作者： Jayaraman, Sharanya Kolarkar, Ameya Department of Computer Science Florida State University Tallahassee FL United States Center for the Advancement of Teaching Florida State University Tallahassee FL United States

ISBN: (纸本)9798400705328

Active Learning approaches have found success in CS1 and CS2 courses, consolidating instructional time on the practical, problem-solving aspects of programming. With the increasing availability of generative Artificial Intelligence Assistants, there is a renewed push to focus on higher-order skills beyond syntax and solving programming problems by matching sample outputs. This poster examines the impact of conceptual explanation-based exercises in introductory programming courses through the implementation of a scaffolded semi-flipped classroom. This method is currently in its third semester as a part of an ongoing, iterative, semi-experimental approach to support student resilience in entrance-level courses. This approach aimed to enhance student engagement, retention, and performance by integrating weekly practice sessions and “group-tutoring" sessions facilitated by peer learning assistants. In these sessions, students were encouraged to articulate their problem-solving strategies and the reasoning behind their solutions, fostering a deeper understanding of programming language paradigms and problem-solving techniques. The findings indicate that this method significantly increased classroom engagement, as students became more active participants in their learning journey. Retention rates improved as students became more confident in understanding and applying programming concepts. Overall, student performance saw a notable rise, with students demonstrating a better grasp of programming paradigms and problem-solving approaches beyond rote memorization and matching sample outputs. © 2025 Copyright held by the owner/author(s).

关键词： Active Learning CS1/CS2 Peer-based Learning Self-Assessment

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Enhancing Long-range Dependency with State Space Model and Kolmogorov-Arnold Networks for Aspect-based Sentiment Analysis 31

Enhancing Long-range Dependency with State Space Model and K...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Lawan, Adamu Pu, Juhua Yunusa, Haruna Umar, Aliyu Lawan, Muhammad School of Computer Science and Technology Beihang University Beijing China National Research Institute for Teaching Materials in Information Science and Tech. China School of Automation Science and Electrical Engineering Beihang University Beijing China School of Computing University of Portsmouth Portsmouth United Kingdom Department of Information and Communication Technology Federal University Gusau Nigeria

ISBN: (纸本)9798891761964

Aspect-based Sentiment Analysis (ABSA) evaluates sentiments toward specific aspects of entities within the text. However, attention mechanisms and neural network models struggle with syntactic constraints. The quadratic complexity of attention mechanisms also limits their adoption for capturing long-range dependencies between aspect and opinion words in ABSA. This complexity can lead to the misinterpretation of irrelevant contextual words, restricting their effectiveness to short-range dependencies. To address the above problem, we present a novel approach to enhance long-range dependencies between aspect and opinion words in ABSA (MambaForGCN). This approach incorporates syntax-based Graph Convolutional Network (SynGCN) and MambaFormer (Mamba-Transformer) modules to encode input with dependency relations and semantic information. The Multihead Attention (MHA) and Selective State Space model (Mamba) blocks in the MambaFormer module serve as channels to enhance the model with short and long-range dependencies between aspect and opinion words. We also introduce the Kolmogorov-Arnold Networks (KANs) gated fusion, an adaptive feature representation system that integrates SynGCN and MambaFormer and captures non-linear, complex dependencies. Experimental results on three benchmark datasets demonstrate MambaForGCN's effectiveness, outperforming state-of-the-art (SOTA) baseline models. © 2025 Association for Computational Linguistics.

关键词： Semantics

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A Study about the Impact of Rewards on Student's Engagement with the Flipped Classroom Methodology 14

A Study about the Impact of Rewards on Student's Engagement ...

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14th IEEE Global Engineering Education Conference, EDUCON 2023

作者： Urquiza-Fuentes, Jaime Rey Juan Carlos University Móstoles ACTIVATE Teaching Innovation Group Laboratory of Information Technologies in Education - LITE Department of Computer Science & Statistics Madrid Spain

ISBN: (纸本)9798350399431

This work describes an incremental design of a course that implements the flipped classroom methodology. The last phase of this implementation was to include rewards based on self-evaluation tests that would impact the students' grades. This should foster students' engagement with the learning methodology. In this work, a deep analysis of the impact of the reward is performed. The analysis of the use of the out-class materials shows that the students' pace does not correspond to the flipped classroom methodology. The students' behaviour is more focused on achieving rewards rather than preparing in-class activities with out-class materials. It is hypothesized that, the main reasons for these behaviours could be that, on the one hand, since the reward is considered by students as another item of the course grade, they work to get the reward. On the other hand, students do not want to change their study methodology because getting involved in the flipped methodology requires from them a significant effort. © 2023 IEEE.

关键词： Students

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Economic Analysis of the Situation Criminalization Production and Protection 15

Economic Analysis of the Situation Criminalization Productio...

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15th International Conference Management of Large-Scale System Development, MLSD 2022

作者： Troyanovskiy, V.M. Federal Research Center 'Computer Science and Control' of the Russian Academy of Sciences Department of Mathematical Methods of Regional Programming Moscow Russia

ISBN: (数字)9781665497015

ISBN: (纸本)9781665497015

The article analyzes criminal activity of an economic nature in case of penetration of crime into production and the system of protection against it. It is advisable to find out under what conditions it is unprofitable to steal, for which it is necessary to supplement legal studies with economic ones. The results of the analysis will help to find ways to rationally counteract crime. © 2022 IEEE.

关键词： Crime

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Optimization on Cognitive Models 15

Optimization on Cognitive Models

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15th International Conference Management of Large-Scale System Development, MLSD 2022

作者： Solomatin, A.N. Federal Research Center 'Computer Science and Control' of the Russian Academy of Sciences Department of Mathematical Methods of Regional Programming Moscow Russia

The concept of acceptable systems with a limited level of systemic pathologies and dysfunctions is considered. The main provisions of cognitive modeling are given and the tasks of single- and multi-criteria optimizati... 详细信息

ISBN: (数字)9781665497015

ISBN: (纸本)9781665497015

关键词： Pathology

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Predicting Students At-Risk Using Deep Learning Neural Network: A comparison of performance of different models

Predicting Students At-Risk Using Deep Learning Neural Netwo...

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2022 International Conference on Electrical, computer, Communications and Mechatronics Engineering, ICECCME 2022

作者： Motaung, Tshepang Padayachee, Kershree Ajoodha, Ritesh School of Computer Science and Applied Mathematics The University of the Witwatersrand Johannesburg South Africa The University of the Witwatersrand Science Teaching and Learning Unit Johannesburg South Africa

ISBN: (数字)9781665470957

ISBN: (纸本)9781665470957

The availability of educational data, along with technology-enhanced learning platforms, allows for the extraction of students' learning behavior, mitigation of their worries, optimization of the educational environment, and data-driven decision-making. To detect at-risk students, this study uses a deep learning neural network trained on a set of attributes taken from a learner activity tracker application called experience API (xAPI). Other probabilistic models such as Random Forest, Support Vector Machine, and k Nearest Neighbours were compared to the convolutional neural network and multilayer perceptron models in correctly classifying at-risk students, and information gain ranking was used to eliminate features that are said to be redundant or irrelevant. After 10 fold cross-validation, the Support Vector Machine model outperformed all other models, including the Convolutional Neural Network and the Multilayer Perceptron, with a peak accuracy score of 77.51%, while the convolutional neural network and the multilayer perceptron achieved accuracy scores of 72.58% and 73.73%, respectively. Student behavioral features, according to the research, are useful predictors of student performance. © 2022 IEEE.

关键词： Multilayer neural networks

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Study on the Influence of Embodied Avatars on Gait Parameters in Virtual Environments and Real World

arXiv

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arXiv 2024年

作者： Zhou, Tianyi Ding, Ding Wang, Shengyu Shi, Chuhan Xu, Xiangyu School of Computer Science and Engineering Southeast University Nanjing China Computer Experimental Teaching Center Southeast University Nanjing China

In this study, we compare the virtual and real gait parameters to investigate the effect of appearances of embodied avatars and virtual reality experience on gait in physical and virtual environments. We developed a virtual environment simulation and gait detection system for analyzing gait. The system transfers real-life scenarios into a realistic presentation in the virtual environment and provides look-alike same-age and old-age avatars for participants. We conducted an empirical study and used subjective questionnaires to evaluate participants’ feelings about the virtual reality experience. Also, the paired sample t-test and neural network were implemented to analyze gait differences. The results suggest that there are disparities in gait between virtual and real environments. Also, the appearance of embodied avatars could influence the gait parameters in the virtual environment. Moreover, the experience of embodying old-age avatars affects the gait in the real world. Copyright © 2024, The Authors. All rights reserved.

关键词： Virtual environments

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