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Retraction Note: Enhanced semantic visual secret sharing scheme for the secure image communication

Multimedia Tools and Applications 2024年第26期83卷 68877-68877页

作者： A, John Blesswin Raj, Christhu Sukumaran, Rajeev G, Selva Mary Computer Science and Engineering K Ramakrishnan College of Technology Anna University Trichy India Centre for Applied Research in Education SRM Institute of Science and Technology Chennai India Teaching Learning Centre Indian Institute of Technology (IIT) Madras India Computer Science and Engineering K Ramakrishnan College of Engineering Anna University Trichy India

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University leagues alongside rankings

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Quality and Quantity 2023年第1期57卷 721-736页

作者： Banász, Zsuzsanna Kosztyán, Zsolt T. Csányi, Vivien V. Telcs, András Department of Economics University of Pannonia Egyetem str. 10 Veszprém Hungary MTA-PE Budapest Ranking Research Group Eötvös Loránd Research Network (ELKH) Egyetem str. 10 Veszprém Hungary Department of Quantitative Methods University of Pannonia Egyetem str. 10 Veszprém Hungary Institute of Advanced Studies Koszeg Koszeg Hungary Research Centre of Faculty of Business and Economics University of Pannonia Egyetem str. 10. Veszprém Hungary Head of Department of Computational Sciences MTA Wigner Research Center for Physics Budapest Hungary Department of Computer Science and Information Theory Budapest University of Technology and Economics Budapest Hungary

University rankings can both orient and disorient potential students. In rankings, universities with very different characteristics are compared, which makes interpretation difficult. We propose the application of a clustering method, which creates groups of universities that are close to each other with respect to a subset of indicators, but the indicators also show homogeneity with respect to the universities in that group. We call such groups leagues. These leagues are defined by the data themselves and are not based on subjective criteria. We demonstrate our proposition using one member of the family of the two-way clustering method, namely, biclustering. The case we present is based on the Round University Ranking (RUR) 2020 dataset. The use of leagues could provide better guidance not only for potential applicants but also for university funding organizations and policy-makers. Our case study led to a somewhat surprising observation. In the top league (based on the RUR data and indicators), the three most important indicators measure reputation, not scientific or educational performance. © 2022, The Author(s).

关键词： Biclustering Leagues Rankings Universities

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Comparative numerical study featuring magnetized nanofluids configured by elongating sheet with thermophoresis and Brownian motion

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Partial Differential Equations in Applied Mathematics 2024年 11卷

作者： Puchakayala, Srinivasa Rao Borra, Shashidar Reddy Kallu, Saritha Formanova, Shoira Khan, M. Ijaz Waqas, M. Ahmad, Furqan Gupta, Manish Department of Mathematics Malla Reddy Engineering College (Autonomous) Dhulapally Telangana Hyderabad 500100 India Department of Mathematics Sreenidhi Institute of Science and Technology Ghatkesar Telangana Hyderabad 501301 India Department of Humanities and Sciences (Mathematics) CVR College of Engineering Ibrahimpatnam Telangana Hyderabad 501510 India Department of Chemistry and Its Teaching Methods Tashkent State Pedagogical University Tashkent Uzbekistan Department of Mechanical Engineering College of Engineering Prince Mohammad Bin Fahd University Al-Khobar Saudi Arabia NUTECH School of Applied Science and Humanities National University of Technology Islamabad 44000 Pakistan Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon Western Caspian University Baku Azerbaijan Division of Research and Development Lovely Professional University Phagwara India

This study investigates the heat and mass transfer characteristics of MHD rotating Fe₃O₄-Al₂O₃/H₂O hybrid nanofluid flow over a three-dimensional stretching surface. Comparative analysis was conducted among the base fluid H₂O, Al₂O₃-H₂O nanofluid, and Fe₃O₄-Al₂O₃/H₂O hybrid nanofluid, focusing on velocity, temperature, and concentration distributions influenced by thermophoresis, Brownian motion, Hall current, temperature ratio, magnetic parameter, rotation, and thermal radiation. The governing nonlinear partial differential equations were transformed into ordinary differential equations using similarity adaptations and solved numerically with the BVP-5C method in MATLAB. Results indicate that increasing the thermophoresis and Brownian motion parameters elevates the temperature profile while affecting the concentration distribution differently. The hybrid nanofluid exhibited a higher temperature distribution compared to the nanofluid and base fluid, whereas the base fluid showed a greater concentration gradient. © 2024 The Author(s)

关键词： Brownian motion Elongating sheet Hall current Hybrid nanofluid Joule heating Thermophoresis

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Comparative analyses of multi-criteria methods in supplier selection problem

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Procedia computer science 2022年 207卷 4593-4602页

作者： Bartosz Paradowski Zdzisław Szyjewski Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology Szczecin ul. Żołnierska 49 71-210 Szczecin Poland Institute of Management University of Szczecin ul. Cukrowa 8 71-004 Szczecin Poland

The ever-growing interest in multi-criteria decision-making methods requires research that would compare them with each other as the decision-makers would need help choosing the appropriate method. It is important to highlight the differences between them, because using different methods may result in discrepancies in the obtained rankings. Additionally, it is worthwhile for the research to take into account the problems whose solution is extremely valuable. To this end, we present a comparison of five multi-criteria decision-making methods: TOPSIS, VIKOR, COMET, SPOTIS, and MARCOS in the supplier selection problem. The conducted research showed significant differences in the evaluation of the preferences of the alternatives and some discrepancies in the obtained rankings.

关键词： MCDM MCDA supplier selection comparison rank similarity

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Practical Study of Selected Multi-Criteria methods Comparison

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Procedia computer science 2022年 207卷 4565-4573页

作者： Jakub Więckowski Zdzisław Szyjewski Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology Szczecin ul. Żołnierska 49 71-210 Szczecin Poland Institute of Management University of Szczecin ul. Cukrowa 8 71-004 Szczecin Poland

Multi-Criteria Decision Analysis (MCDA) methods enable a comprehensive analysis of decision options to identify the most preferred values. However, the abundance of these techniques, using different transformations in the calculations, can cause a divergence of results. However, the resulting rankings should be as consistent and reliable as possible. In this paper, we used the TOPSIS, COPRAS, SPOTIS, and COMET methods to examine the consistency of their results in the practical problem of laptop evaluation. The rankings were then compared with the reference ranking. The research showed that among the methods listed, the COPRAS method's results differed the most from the others. In turn, this technique ensured a ranking in line with the reference ranking. Based on the results, it can be established that the methods used are characterized by high consistency of results.

关键词： MCDA TOPSIS COPRAS SPOTIS COMET Comparison Laptops assessment

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Unsupervised graphical user interface learning 28

Unsupervised graphical user interface learning

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28th International Workshop on Concurrency, Specification and Programming, CS and P 2019

作者： Czaus, Przemyslaw Department of Mathematical Methods of Computer Science Faculty of Mathematics and Computer Science University of Warmia and Mazury in Olsztyn Sloneczna 54 Olsztyn10-710 Poland

While there are many different papers on automatic testing or generation of interfaces[1, 2, 3, 4], the information concerning similar to human perception user interface learning methods are scarce. Given the recent leaps in Artificial Intelligence (AI) one might find this topic very useful in implementing a solution for communication of AI with applications created for human interaction. User interfaces differ between operating systems, hardware possibilities and implementation. The main objective of the study was the analysis of the applications' Graphic User Interface (GUI) and interaction with the graphic interface elements in general. This method can be used to track the change in application behaviour based on any action from the user, without having knowledge about the underlying object structure. Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Machine learning

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MetAug: Contrastive Learning via Meta Feature Augmentation

arXiv

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arXiv 2022年

作者： Li, Jiangmeng Qiang, Wenwen Zheng, Changwen Su, Bing Xiong, Hui Science & Technology on Integrated Information System Laboratory Institute of Software Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Guangdong China Gaoling School of Artificial Intelligence Renmin University of China Beijing China Beijing Key Laboratory of Big Data Management and Analysis Methods Beijing China Guangzhou China Department of Computer Science Engineering The Hong Kong University of Science and Technology Hong Kong

What matters for contrastive learning? We argue that contrastive learning heavily relies on informative features, or "hard" (positive or negative) features. Early works include more informative features by applying complex data augmentations and large batch size or memory bank, and recent works design elaborate sampling approaches to explore informative features. The key challenge toward exploring such features is that the source multi-view data is generated by applying random data augmentations, making it infeasible to always add useful information in the augmented data. Consequently, the informativeness of features learned from such augmented data is limited. In response, we propose to directly augment the features in latent space, thereby learning discriminative representations without a large amount of input data. We perform a meta learning technique to build the augmentation generator that updates its network parameters by considering the performance of the encoder. However, insufficient input data may lead the encoder to learn collapsed features and therefore malfunction the augmentation generator. A new margin-injected regularization is further added in the objective function to avoid the encoder learning a degenerate mapping. To contrast all features in one gradient back-propagation step, we adopt the proposed optimization-driven unified contrastive loss instead of the conventional contrastive loss. Empirically, our method achieves state-of-the-art results on several benchmark datasets. Copyright © 2022, The Authors. All rights reserved.

关键词： Backpropagation

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Improving EEG-Based Motor Imagery Classification Using Hybrid Neural Network

Improving EEG-Based Motor Imagery Classification Using Hybri...

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International Conference on Information, Communication and Networks (ICICN)

作者： Cong Li Honghong Yang Xia Wu Yumei Zhang Key Laboratory of Modern Teaching Technology Ministry of Education (Shaanxi Normal University) Xi’an China School of Computer Science Shaanxi Normal University Xi’an China

ISBN: (纸本)9781665411578

Motor imagery EEG (MI-EEG) is a subjective signal generated by testers, which is collected through brain-computer interface (BCI). With the characteristics of noninvasive, inexpensive, and easily applied to human beings, MI-EEG classification is a popular research area in recent years. Due to the low signal-to-noise ratio and incomplete EEG signals, high accuracy rate classification is still a challenging problem. Most existing works of deep learning only regard EEG signals as chain-like sequences data and use single neural network for classification. To solve the above issues, we propose an improved EEG signals classification method via a hybrid neural network (HNN). In our work, we first use the origin EEG signals without removing noise and any filtering process, to ensure real-time property. Then, the EEG signals are divided into some small segments, and we arrange the data by considering the spatial position of electrodes. Finally, we propose a hybrid neural network by combing CNN, DNN, LSTM network. Experimental results for two challenging EEG signal classification benchmark datasets show that the proposed method has a good classification performance compared with several state-of-the-art EEG signal classification algorithms. After multiple sample testing, the average experiment result is 75.52%, which is 7.32% higher than the latest method.

关键词： Electrodes Deep learning Filtering Conferences Pattern classification Electroencephalography Real-time systems

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Interventional Contrastive Learning with Meta Semantic Regularizer

arXiv

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arXiv 2022年

作者： Qiang, Wenwen Li, Jiangmeng Zheng, Changwen Su, Bing Xiong, Hui Science & Technology on Integrated Information System Laboratory Institute of Software Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Guangdong China Gaoling School of Artificial Intelligence Renmin University of China Beijing China Beijing Key Laboratory of Big Data Management and Analysis Methods Beijing China Guangzhou China Department of Computer Science & Engineering The Hong Kong University of Science and Technology Hong Kong

Contrastive learning (CL)-based self-supervised learning models learn visual representations in a pairwise manner. Although the prevailing CL model has achieved great progress, in this paper, we uncover an ever-overlooked phenomenon: When the CL model is trained with full images, the performance tested in full images is better than that in foreground areas;when the CL model is trained with foreground areas, the performance tested in full images is worse than that in foreground areas. This observation reveals that backgrounds in images may interfere with the model learning semantic information and their influence has not been fully eliminated. To tackle this issue, we build a Structural Causal Model (SCM) to model the background as a confounder. We propose a backdoor adjustment-based regularization method, namely Interventional Contrastive Learning with Meta Semantic Regularizer (ICL-MSR), to perform causal intervention towards the proposed SCM. ICL-MSR can be incorporated into any existing CL methods to alleviate background distractions from representation learning. Theoretically, we prove that ICL-MSR achieves a tighter error bound. Empirically, our experiments on multiple benchmark datasets demonstrate that ICL-MSR is able to improve the performances of different state-of-the-art CL methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantics

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Rule-based expert system supporting Individual Education-and-Therapeutic Program composition in SYSABA

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Procedia computer science 2022年 207卷 4535-4544页

作者： Joanna Kołodziejczyk Nela Grzegorczyk-Dłuciak Ewa Kuliga Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Żołnierska 49 71-210 Szczecin Poland Polish Association of Behavioral Therapy Os. Wysokie 7 31-819 Krakow Poland

System for Applied Behavioral Analysis (SYSABA) is a freeware web-based software developed in Poland that aids therapists who work with developmentally disordered children. A pioneer in Poland application is adapted to Applied Behavior Analysis (ABA) methodology and is compliant with the Polish Regulation of the Ministry of Education. A part of SYSABA is a module that helps compose a compliant with Polish regulations and ABA methodology, the Individual Education-and-Therapeutic Program (pol. IPET). This development process is guided by an expert system, including specialists’ knowledge of the subject. The IPET composition is demanding and time-consuming, and the decisions made by the therapist will influence the treatment results. Because there are many paths to the final curriculum, the decision-making module in SYSABA was designed to improve and standardize the process. The paper provides details of the IPETs expert module design in SYSABA. The expert knowledge of long-term supervisors was expressed in a set of regulations and constraints supplying a rule-based expert system. The unstructured expertise was translated into a logical SYSABA two-level framework. Thirty-six rules guiding skill and behavior curricula were created. The effectiveness of the expert system was confirmed by a survey after one year of SYSABA usage.

关键词： Rule-based expert system autism (ASD) Applied Behavior Analysis (ABA) logical framework

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