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Engagement Detection Based on Analyzing Micro Body Gestures Using 3D CNN

computers, Materials & Continua 2022年第2期70卷 2655-2677页

作者： Shoroog Khenkar Salma Kammoun Jarraya Department of Computer Science King Abdul-Aziz UniversityJeddahSaudi Arabia MIRACL-Laboratory SfaxTunisia

This paper proposes a novel,efficient and affordable approach to detect the students’engagement levels in an e-learning environment by using *** method analyzes spatiotemporal features of e-learners’micro body gestures,which will be mapped to emotions and appropriate engagement *** proposed engagement detection model uses a three-dimensional convolutional neural network to analyze both temporal and spatial information across video *** follow a transfer learning approach by using the C3D model that was trained on the Sports-1M *** adopted C3D model was used based on two different approaches;as a feature extractor with linear classifiers and a classifier after applying fine-tuning to the pretrained *** model was tested and its performance was evaluated and compared to the existing *** proved its effectiveness and superiority over the other existing methods with an accuracy of 94%.The results of this work will contribute to the development of smart and interactive e-learning systems with adaptive responses based on users’engagement levels.

关键词： Micro body gestures engagement detection 3D CNN transfer learning e-learning spatiotemporal features

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On the Rique Number of Series-Parallel Graphs and Planar Bipartite Graphs 2nd

On the Rique Number of Series-Parallel Graphs and Planar ...

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2nd International Conference on Applied Algorithms, ICAA 2025

作者： Azgor, Sk Ruhul Rahman, Md. Saidur Graph Drawing and Information Visualization Laboratory Department of Computer Science and Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh

ISBN: (纸本)9783031845420

The restricted input queue (rique) is a data structure which is recently introduced to study linear layout of graphs. The rique data structure is a special queue where insertions occur only at the head and removals occur at both the head and the tail. Considering a rique data structure the goal of a linear layout of a graph is to find a linear order of the vertices of the graph and a partition of its edges into pages such that the edges in each page follow the restriction of rique in the underlying order. The rique number of a graph is the smallest number of pages required for linear layout of the graph with rique data structure. A characterization of graphs for admitting a single page rique layout and some bounds on the rique number of complete and complete bipartite graphs are known. In this paper, we show that the rique number of series-parallel graphs as well as planar bipartite graphs is 2. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Directed graphs

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Formal Model of ATM Based on Object Constraint Language (OCL) 10

Formal Model of ATM Based on Object Constraint Language (OCL...

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10th International Conference on Engineering and Emerging Technologies, ICEET 2024

作者： Ahmed, Irfan Naseer, Sadia Umm - E - Habiba Mahmood, Jabar Chaudhry, Shehzad Ashraf Batool, Khadija University of Sialkot Department of Computer Science Sialkot Pakistan School of Cyber Science and Technology College of Computer Science and Technology Zhejiang University State Key Laboratory of Blockchain Hangzhou China College of Engineering Abu Dhabi University Department of Computer Science and Information Technology Abu Dhabi United Arab Emirates Gujranwala Pakistan

ISBN: (纸本)9798331532895

Formal methods (FM) are innovative methods which employ mathematical notations to specify explicit and precise requirements. This paper presents a formal model of an automated teller machine (ATM) using Object Constraint Language (OCL) to illustrate the benefits of employing FM to develop commercial applications. FM provide a mathematically rigorous framework for specifying, developing, and verifying software systems. It enhances reliability, robustness, and security. FM plays a crucial role in the context of ATM, which requires high levels of trust and correctness due to their financial and security-critical nature. Using OCL, we demonstrate how formal specifications can be applied to define an ATM system's precise behavior and constraints. It allows for the early detection and correction of errors, reducing development costs and improving overall system quality. This study argues that adopting FM in commercial applications not only boosts the reliability and security of the systems but also increases customer satisfaction and trust. Results of ATM development under OCL have been compared with traditional methods (TM), showing reductions such as 51 % in development time, 53 % in cost, 94 % in ambiguity and 97% in quality and customer trust. © 2024 IEEE.

关键词： Customer satisfaction

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Bayesian Network Modelling for Improved Knowledge Management of the Expert Model in the Intelligent Tutoring System

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International Journal of Advanced computer science and Applications 2022年第6期13卷 187-192页

作者： Hibbi, Fatima-Zohra Abdoun, Otman Haimoudi, El Khatir Computer Science Department Advanced Science and Technologies Laboratory Polydisciplinary Faculty Abdelmalek Essaadi University Larache Morocco

The expert module is an essential part of the intelligent tutoring system. This module uses only declarative knowledge, excluding other types of domain knowledge: procedural and conditional. This elimination makes the expert module very delicate. To solve this issue, the authors propose to embed knowledge processing into the expert model. The contribution aims to empower the expert model via the fragmentation of the knowledge process into four categories: Analyzation, Application, Conceptualization, and Experimentation using the Bayesian Network method as an instrument for modelling expert systems in uncertain areas. According to the management of the expert system through a list of criteria, the expert module can suggest the correct type of knowledge and their following status © 2022. International Journal of Advanced computer science and *** Rights Reserved.

关键词： Bayesian networks

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Latest Innovations in Intelligent Network-on-Chip Architectures: A Systematic Review 17

Latest Innovations in Intelligent Network-on-Chip Architectu...

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17th IEEE/ACM International Workshop on Network on Chip Architectures, NoCArc 2024

作者： Kakoulli, Elena Neapolis University Pafos Intelligent Systems Laboratory Department of Computer Science Pafos Cyprus Cyprus University of Technology Electrical Engineering and Computer Engineering and Informatics Limassol Cyprus

ISBN: (纸本)9798331506421

This review investigates the latest advancements in intelligent Network-on-Chip (NoC) architectures, focusing on innovations from 2022 to 2024. The integration of Artificial Intelligence (AI) and Machine Learning (ML) into NoC designs has driven significant improvements in performance, scalability, energy efficiency, and security. Key contributions include AI/ML-driven techniques to optimize routing, reduce latency, manage power consumption, and enhancing security against emerging threats. Despite these advancements, challenges such as computational overhead and integration complexities remain. This review consolidates these findings, addresses existing challenges, and proposes future research directions to further leverage AI and ML for developing robust and adaptable NoC architectures. © 2024 IEEE.

关键词： Federated learning

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Comprehensive Learning Strategy Enhanced Chaotic Whale Optimization for High-dimensional Feature Selection

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Journal of Bionic Engineering 2023年第6期20卷 2973-3007页

作者： Hanjie Ma Lei Xiao Zhongyi Hu Ali Asghar Heidari Myriam Hadjouni Hela Elmannai Huiling Chen Key Laboratory of Intelligent Informatics for Safety&Emergency of Zhejiang Province Wenzhou UniversityWenzhou325035China Department of Computer Sciences College of Computer and Information SciencePrincess Nourah Bint Abdulrahman UniversityP.O.Box 8442811671 RiyadhSaudi Arabia Department of Information Technology College of Computer and Information SciencePrincess Nourah Bint Abdulrahman UniversityP.O.Box 8442811671 RiyadhSaudi Arabia

Feature selection(FS)is an adequate data pre-processing method that reduces the dimensionality of datasets and is used in bioinformatics,finance,and *** FS approaches,however,frequently struggle to identify the most important characteristics when dealing with high-dimensional *** alleviate the imbalance of explore search ability and exploit search ability of the Whale Optimization Algorithm(WOA),we propose an enhanced WOA,namely SCLWOA,that incorporates sine chaos and comprehensive learning(CL)*** them,the CL mechanism contributes to improving the ability to *** the same time,the sine chaos is used to enhance the exploitation capacity and help the optimizer to gain a better initial *** hybrid performance of SCLWOA was evaluated comprehensively on IEEE CEC2017 test functions,including its qualitative analysis and comparisons with other *** results demonstrate that SCLWOA is superior to other algorithms in accuracy and converges faster than ***,the variant of Binary SCLWOA(BSCLWOA)and other binary optimizers obtained by the mapping function was evaluated on 12 UCI data ***,BSCLWOA has proven very competitive in classification precision and feature reduction.

关键词： Feature selection Whale Optimization Algorithm Binary optimizer Global optimization

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QPDet: Queuing People Detector for Aerial Images Based on Adaptive Soft Label Assignment Strategy 27th

QPDet: Queuing People Detector for Aerial Images Based on ...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Zhang, Yi Su, Yi Li, Siying Yi, Kai Department of Computer Science Sichuan University Chengdu China Intelligent Policing Key Laboratory of Sichuan Province Luzhou China

ISBN: (纸本)9783031781681

As a branch of object detection task, the detection of queuing people in the aerial images emerges as a new research direction in recent years. However, it remains challenging due to the complex background, variations in the viewpoints and densely located tiny objects. In this paper, we propose a tiny object detector called QPDet to solve the above issues. Firstly, a large-scale dataset of queuing people with dense and diverse annotations has been constructed to enrich the knowledge of this field, in which a large number of queuing people have been sorted and collected using drones. Secondly, a modified YOLOX has been utilized as our detector, which effectively detects the tiny objects in the aerial images. Finally, an adaptive soft label assignment strategy has been proposed to improve the robustness of our detector. Extensive experiments have been conducted to demonstrate the effectiveness of our approach, the results exhibit the superiority of our detector. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Aerial photography

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Machine learning models for modeling the biosorption of Fe(III) ions by activated carbon from olive stone

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Neural Computing and Applications 2024年第21期36卷 13357-13372页

作者： Massaoudi, Ayman Echouchene, Fraj Ben Ayed, Mossaad Berguiga, Abdelwahed Harchay, Ahlem Al-Ghamdi, Sara Belmabrouk, Hafedh Department of Computer Science College of Science and Arts in Gurayat Jouf University Sakakah Saudi Arabia Olive Research Center Jouf University Sakakah Saudi Arabia Laboratory of Electronics and Microelectronics Faculty of Science of Monastir University of Monastir Environment Boulevard Monastir5019 Tunisia Higher Institute of Applied Sciences and Technology of Sousse University of Sousse Sousse Tunisia Department of Industrial Electronics ENISo University of Sousse Sousse Tunisia Department of Computer Science College of Computer and Information Sciences Jouf University Sakakah Saudi Arabia Department of Physics College of Science Majmaah University Al Majma’ah11952 Saudi Arabia

Using experimental results related to the biosorption of Fe(III) by activated carbon derived from olive pit waste, we developed and evaluated four artificial neural network (ANN) models in this study, namely MLP-ANN, RBF-ANN, GR-ANN, and PSO-ANN, to predict the removal efficiency of Fe(III) during the adsorption process. The purpose of these models was to forecast the effect of the following five important operational variables: the initial concentration, time, stirring speed, temperature, and biosorbent dose. We conducted a thorough assessment of the performance of these models and compared their ability to predict the removal capacity. Several statistical metrics have been used to quantify the quality of the different models. The results calculated by the machine learning models were analyzed and compared with the experimental results. The obtained values of the coefficient of determination were 0.9997 for the PSO-ANN model, 0.991 for the GR-ANN model, 0.983 for the RBF-ANN model, and 0.837 for the MLP-ANN model concerning the removal efficiency. All the studied models are able to accurately predict the adsorbed quantity. ANOVA analysis was used to evaluate the effect of the parameters inherent to the PSO-ANN model. The PSO-ANN model proves to be a powerful tool for estimating the efficiency of Fe(III) ion removal. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024. corrected publication 2024.

关键词： Biosorption

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A divide-and-conquer reconstruction method for defending against adversarial example attacks

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Visual Intelligence 2024年第1期2卷 1-17页

作者： Liu, Xiyao Hu, Jiaxin Yang, Qingying Jiang, Ming He, Jianbiao Fang, Hui School of Computer Science and Engineering Central South University Hunan Changsha 410083 China Guangxi Key Laboratory of Cryptography and Information Security School of Computer Science and Information Security Guilin University of Electronic Technology Guangxi Guilin China Department of Computer Science Loughborough University Loughborough LE113TU United Kingdom

In recent years, defending against adversarial examples has gained significant importance, leading to a growing body of research in this area. Among these studies, pre-processing defense approaches have emerged as a prominent research direction. However, existing adversarial example pre-processing techniques often employ a single pre-processing model to counter different types of adversarial attacks. Such a strategy may miss the nuances between different types of attacks, limiting the comprehensiveness and effectiveness of the defense strategy. To address this issue, we propose a divide-and-conquer reconstruction pre-processing algorithm via multi-classification and multi-network training to more effectively defend against different types of mainstream adversarial attacks. The premise and challenge of the divide-and-conquer reconstruction defense is to distinguish between multiple types of adversarial attacks. Our method designs an adversarial attack classification module that exploits the high-frequency information differences between different types of adversarial examples for their multi-classification, which can hardly be achieved by existing adversarial example detection methods. In addition, we construct a divide-and-conquer reconstruction module that utilizes different trained image reconstruction models for each type of adversarial attack, ensuring optimal defense effectiveness. Extensive experiments show that our proposed divide-and-conquer defense algorithm exhibits superior performance compared to state-of-the-art pre-processing methods. © The Author(s) 2024.

关键词： Adversarial attack multi-classification Adversarial example defense Divide-and-conquer strategy Reconstruction network

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Framework and Methodology for Verification of a Complex Scientific Simulation Software, Flash-X

Framework and Methodology for Verification of a Complex Scie...

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2023 Congress in computer science, computer Engineering, and Applied Computing, CSCE 2023

作者： Dhruv, Akash Jain, Rajeev O'Neal, Jared Weide, Klaus Dubey, Anshu Mathematics and Computer Science Argonne National Laboratory LemontIL United States University of Chicago Department of Computer Science ChicagoIL United States

ISBN: (纸本)9798350327595

Computational science relies on scientific software as its primary instrument for scientific discovery. Therefore, similar to the use of other types of scientific instruments, correct software and the correct operation of the software is necessary for executing rigorous scientific investigations. Scientific software verification can be especially difficult, as users typically need to modify the software as part of a scientific study. Systematic methodologies for building test suites for scientific software are rare in the literature. Here, we describe a methodology that we have developed for Flash-X, a community simulation software for multiple scientific domains, that has composable components that can be permuted and combined in a multitude of ways to generate a wide range of applications. Ensuring sufficient code coverage by a test suite is particularly challenging due to this composability. Our methodology includes a consideration of trade-offs between meeting software quality goals, developer productivity, and meeting the scientific goals of the Flash-X user community. © 2023 IEEE.

关键词： Methodology Multiphysics Scientific software Test suite Verification

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