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Application of Artificial Intelligence Methods for Generating Mathematical Problems in Primary Education: Analysis of Effectiveness and Prospects for Automated Assessment

Application of Artificial Intelligence Methods for Generatin...

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Machine Learning and Natural Language Processing (MLNLP), International Conference on

作者： Nazipov Rustam Salavatovich Avksentieva Elena Yurievna Faculty of Software Engineering and Computer System ITMO University Saint Petersburg Russia Faculty of Software Engineering and Computer System ITMO University Saint-Petersburg Russia

ISBN: (数字)9798350354973

ISBN: (纸本)9798350354980

The present study aims to evaluate the effectiveness of using modern neural network models (ChatGPT 4o, Claude 3.5 Sonnet, GigaChat 3.0, YandexGPT 3) for generating mathematical problems for elementary school students. The research conducts a comparative analysis of the quality of generated problems, assesses the possibility of their direct use without expert review, and develops recommendations for automating the quality control process. The methodology includes the generation of various types of mathematical problems, their expert evaluation according to developed criteria, and statistical analysis of the results. The study identifies the strengths and weaknesses of each model, determines the types of problems in which the models demonstrate the best results, and suggests directions for further improvement of AI systems in the educational context.

关键词： Analytical models Statistical analysis Reviews Neural networks Process control Quality control Machine learning Chatbots Mathematical models Context modeling

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Moodle-based Learning Management system Design as a Learning Media at SMKN 40 Jakarta 7

Moodle-based Learning Management System Design as a Learning...

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7th International Conference on New Media Studies, CONMEDIA 2023

作者： Setya, Oktaviano Nanda Prima Widodo Nugraheni, Murien State Jakarta University Informatics and Computer Engineering Education Jakarta Indonesia State Jakarta University Information System and Technology Jakarta Indonesia

ISBN: (纸本)9798350307504

Indonesia is currently in the final stages of the COVID-19 pandemic, which has changed the world of the online learning. Online learning has many benefits, one of which students can learn anywhere and anytime. SMK Negeri 40 Jakarta is one of the vocational high schools located in DKI Jakarta. Based on observation at SMKN 40 Jakarta, teachers use a learning management system for daily learning. Therefore, a Moodle-based learning management system is needed. Learning Management system is a web application to manage various learning activities automatically, which is built using Moodle platform with RAD (Rapid Application Development) methodology. The result is a Moodle-based learning management system application that can be useful in supporting the teaching and learning process at school. Based on the results of black box testing and user acceptance testing, the learning management system created is very good, therefore it can be concluded this application can be accepted and implemented at SMK Negeri 40 Jakarta. © 2023 IEEE.

关键词： Black-box testing

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Multi - Task Learning with Convolutional Neural Network for Packet Format Detection and Modulation Classification of Wireless LAN 13

Multi - Task Learning with Convolutional Neural Network for ...

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13th International Conference on Information and Communication Technology Convergence, ICTC 2022

作者： Putra, Dody Ichwana Pratama, M. Harry Bintang Nagao, Yuhei Kurosaki, Masayuki Ochi, Hiroshi Graduate School of Computer Science and System Engineering Kyushu Institute of Technology Iizuka Japan

ISBN: (数字)9781665499392

ISBN: (纸本)9781665499392

In this paper, we propose multi-task learning (MTL) using a convolutional neural network (CNN) to simultaneously perform packet format detection and modulation classification of wireless LAN (WLAN) signals. Compared to single-task learning, the main advantage of this method is the high classification accuracy and rapid learning with a lightweight neural network model. These are achieved because of learning shared knowledge (i.e., model weight or gradients) between related tasks. This shared representation model increases data efficiency and reduces overfitting. The WLAN signals generated by the Matlab wave generator are used to validate and test the model. The results show that even with different time offsets, the proposed method has an accuracy of 98% for packet format detection and 86% for modulation classification. © 2022 IEEE.

关键词： Orthogonal frequency division multiplexing

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Sentiment Analysis of Public Opinion on Twitter about the Implementation of the Merdeka Curriculum Using the Support Vector Machine Algorithm

Sentiment Analysis of Public Opinion on Twitter about the Im...

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2023 International Conference on Modeling and E-Information Research, Artificial Learning and Digital Applications, ICMERALDA 2023

作者： Ramadhanti, Intan Widodo Nugraheni, Murien Universitas Negeri Jakarta Informatics and Computer Engineering Education Jakarta Indonesia Universitas Negeri Jakarta Information System and Technology Jakarta Indonesia

ISBN: (纸本)9798350369359

In 2022 the Head of Standards, Curriculum, Education Assessment (BSKAP) No. 0441HIKR/2022 issued a Decree (SK) regarding Education Units for the Implementation of the Merdeka Curriculum in 140 thousand educational units in Indonesia. The implementation of this new curriculum raises various public opinions on social media Twitter. Therefore, research on the analysis of public sentiment on the implementation of the Merdeka Curriculum was carried out. The tweets taken are tweets with positive and negative sentiments. This study aims to see whether the SVM algorithm is good at carrying out text classification for sentiment analysis of the Merdeka Curriculum by looking at the accuracy value and describing how the public's sentiment on Twitter is about the Merdeka Curriculum. The data used is a dataset of 1,186 tweets, that is 363 positive tweets and 823 negative tweets. The results showed that the accuracy of the Support Vector Machine algorithm with linear, polynomial, and sigmoid kernels was 91.82% and the RBF kernel was 89.88%. As well as seen from the results of the sentiment analysis of implementing the Merdeka Curriculum there were more negative responses, one of which was regarding too many assignments and projects that made students feel tired and stressed. © 2023 IEEE.

关键词： Support vector machines

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Resilience assessment framework toward interdependent bus-rail transit network:Structure,critical components,and coupling mechanism

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Communications in Transportation Research 2023年第1期3卷 118-129页

作者： Bing Liu Xiaoyue Liu Yang Yang Xi Chen Xiaolei Ma School of Transportation Science and Engineering Beihang UniversityBeijing100191China Department of Civil&Environmental Engineering University of UtahSalt Lake CityUT84112USA School of Computer Science and Engineering Beihang UniversityBeijing100191China Key Laboratory of Intelligent Transportation Technology and System Ministry of EducationBeijing100191China

Understanding the interdependent nature of multimodal public transit networks(PTNs)is vital for ensuring the resilience and robustness of transportation ***,previous studies have predominantly focused on assessing the vulnerability and characteristics of single-mode PTNs,neglecting the impacts of heterogeneous disturbances and shifts in travel behavior within multimodal ***,this study introduces a novel resilience assessment framework that comprehensively analyzes the coupling mechanism,structural and functional characteristics of bus-rail transit networks(BRTNs).In this framework,a network performance metric is proposed by considering the passengers’travel behaviors under various ***,stations and subnetworks are classified using the k-means algorithm and resilience metric by simulating various disturbances occurring at each station or *** proposed framework is validated via a case study of a BRTN in Beijing,*** indicate that the rail transit network(RTN)plays a crucial role in maintaining network function and resisting external disturbances in the interdependent ***,the coupling interactions between the RTN and bus transit network(BTN)exhibit distinct characteristics under infrastructure component disruption and functional *** findings provide valuable insights into emergency management for PTNs and understanding the coupling relationship between BTN and RTN.

关键词： Complex network Bus-rail transit network Resilience analysis Interdependent coupling relationship Classification analysis

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Al-Biruni Earth Radius Optimization for COVID-19 Forecasting

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computer systems Science & engineering 2023年第7期46卷 883-896页

作者： El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mostafa Abotaleb Tatiana Makarovskikh Amal H.Alharbi Doaa Sami Khafaga Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura University35516MansouraEgypt Department of System Programming South Ural State University454080ChelyabinskRussia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Several instances of pneumonia with no clear etiology were recorded in Wuhan,China,on December 31,*** world health organization(WHO)called it COVID-19 that stands for“Coronavirus Disease 2019,”which is the second version of the previously known severe acute respiratory syndrome(SARS)Coronavirus and identified in short as(SARSCoV-2).There have been regular restrictions to avoid the infection spread in all countries,including Saudi *** prediction of new cases of infections is crucial for authorities to get ready for early handling of the virus ***:Analysis and forecasting of epidemic patterns in new SARSCoV-2 positive patients are presented in this research using metaheuristic optimization and long short-term memory(LSTM).The optimization method employed for optimizing the parameters of LSTM is Al-Biruni Earth Radius(BER)***:To evaluate the effectiveness of the proposed methodology,a dataset is collected based on the recorded cases in Saudi Arabia between March 7^(th),2020 and July 13^(th),*** addition,six regression models were included in the conducted experiments to show the effectiveness and superiority of the proposed *** achieved results show that the proposed approach could reduce the mean square error(MSE),mean absolute error(MAE),and R^(2)by 5.92%,3.66%,and 39.44%,respectively,when compared with the six base *** the other hand,a statistical analysis is performed to measure the significance of the proposed ***:The achieved results confirm the effectiveness,superiority,and significance of the proposed approach in predicting the infection cases of COVID-19.

关键词： COVID-19 prediction meta-heuristic optimization LSTM Al-Biruni earth radius algorithm

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Towards High-throughput and Low-latency Billion-scale Vector Search via CPU/GPU Collaborative Filtering and Re-ranking 23

Towards High-throughput and Low-latency Billion-scale Vector...

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23rd USENIX Conference on File and Storage Technologies, FAST 2025

作者： Tian, Bing Liu, Haikun Tang, Yuhang Xiao, Shihai Duan, Zhuohui Liao, Xiaofei Jin, Hai Zhang, Xuecang Zhu, Junhua Zhang, Yu National Engineering Research Center for Big Data Technology and System Service Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China Huawei Technologies Co. Ltd. China

ISBN: (纸本)9781939133458

Approximate nearest neighbor search (ANNS) has emerged as a crucial component of database and AI infrastructure. Ever-increasing vector datasets pose significant challenges in terms of performance, cost, and accuracy for ANNS services. None of modern ANNS systems can address these issues simultaneously. In this paper, we present FusionANNS, a high-throughput, low-latency, cost-efficient, and high-accuracy ANNS system for billion-scale datasets using SSDs and only one entry-level GPU. The key idea of FusionANNS lies in CPU/GPU collaborative filtering and re-ranking mechanisms, which significantly reduce I/O operations across CPUs, GPU, and SSDs to break through the I/O performance bottleneck. Specifically, we propose three novel designs: (1) multi-tiered indexing to avoid data swapping between CPUs and GPU, (2) heuristic re-ranking to eliminate unnecessary I/Os and computations while guaranteeing high accuracy, and (3) redundant-aware I/O deduplication to further improve I/O efficiency. We implement FusionANNS and compare it with the state-of-the-art SSD-based ANNS system-SPANN and GPU-accelerated in-memory ANNS system-RUMMY. Experimental results show that FusionANNS achieves 1) 9.4-13.1× higher query per second (QPS) and 5.7-8.8× higher cost efficiency compared with SPANN;2) and 2-4.9× higher QPS and 2.3-6.8× higher cost efficiency compared with RUMMY, while guaranteeing low latency and high accuracy. © 2025 FAST. All Rights Reserved.

关键词： Collaborative filtering

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Educational Training on Business Management Using Web-Based Applications with Cryptocurrency Integration 7

Educational Training on Business Management Using Web-Based ...

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7th International Conference on Vocational Education and Electrical engineering, ICVEE 2024

作者： Yohannes, Ervin Yamasari, Yuni Prapanca, Aditya Indriyanti, Aries Dwi Nuryana, I Kadek Dwi Lin, Chih-Yang Muchtar, Kahlil State University of Surabaya Informatic Engineering Surabaya Indonesia State University of Surabaya Information System Surabaya Indonesia National Central University Mechanical Engineering Taoyuan Taiwan Syiah Kuala University Electrical and Computer Engineering Banda Aceh Indonesia

ISBN: (纸本)9798331505103

The business model has developed significantly in various aspects and fields. One of the most popular models is the Business Model Canvas, which has greatly helped people build their businesses. With advancements in technology, this model has been combined with artificial intelligence (AI) into a web-based application. Moreover, we have integrated cryptocurrency into our application to provide players with a real-time business environment experience. Additionally, we have developed both administrator and player systems, which are user-friendly and adaptable to various languages. Based on the experimental results, anyone who has played this simulation/training has done so without any problems. The team with the highest Net Profit Value (NPV) is nominated as the winner in this business simulation/training. Our demo can be accessed at https://***/demo. © 2024 IEEE.

关键词： application business cryptocurrency educational web

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A Framework for Deepfake Detection using Convolutional Neural Network and Deep Features 3

A Framework for Deepfake Detection using Convolutional Neura...

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3rd International Conference on Machine Learning and Data engineering, ICMLDE 2024

作者： Soundarya, B.C. Gururaj, H.L. Naveen Kumar, C.M. Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal India Department of Computer Science and Business System Malnad College of Engineering Hassan India

With the advancement of Artificial Intelligence, facial recognition has become a crucial biometric feature. Deepfake technology leverages AI and can create hyper-realistic digitally manipulated videos of people appearing to say or do things that never occurred. The emergence of Generative Adversarial Networks (GANs) has further enabled the creation of fake visual content with astonishing realism. This technology has diverse applications, such as in the film industry, where it allows for video recreation without reshooting, creating awareness videos, restoring the voices of those who have lost them, and updating movie scenes at low cost. However, this rapid advancement also presents significant challenges. The proliferation of synthetic images raises severe concerns about their societal impact, particularly in terms of potential misuse for harassment and blackmail. Therefore, developing robust deepfake detection models is imperative. This study evaluates the performance of a proposed ResNet34 model in deepfake detection. We utilize the FaceForensics++ dataset to train and assess the model, incorporating images generated by four popular deepfake techniques. Our experimental results demonstrate that integrating linear ternary patterns (LTP) and edge detection-based features with the modified ResNet34 model achieves superior performance, attaining 97.5% accuracy and surpassing other approaches. © 2024 The Authors. Published by ELSEVIER B.V.

关键词： Convolutional neural networks

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Anomaly Detection in Microservice systems Using Autoencoders 4

Anomaly Detection in Microservice Systems Using Autoencoders

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4th International Conference on Advancements in Computing, ICAC 2022

作者： de Silva, Manul Daniel, Sam Kumarapeli, Manith Mahadura, Sashika Rupasinghe, Lakmal Liyanapathirana, Chethana Computer System Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

The adaptation of microservice architecture has increased massively during the last few years with the emergence of the cloud. Containers have become a common choice for microservices architecture instead of VMs (Virtual Machines) due to their portability and optimized resource usage characteristics. Along with the containers, container-orchestration platforms are also becoming an integral part of microservice-based systems, considering the flexibility and scalability offered by the container-orchestration media. With the virtualized implementation and the dynamic attribute of modern microservice architecture, it has been a cumbersome task to implement a proper observability mechanism to detect abnormal behaviour using conventional monitoring tools, which are most suitable for static infrastructures. We present a system that will collect required data with the understanding of the dynamic attribute of the system and identify anomalies with efficient data analysis methods. © 2022 IEEE.

关键词： Containers

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