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Decay of solutions to a non-degenerate Schrödinger equation with a dynamic boundary of fractional integral type

SeMA Journal 2025年 1-21页

作者： Elhamid, Hallouz Abd Laboratory of Informatics and Mathematics University of Tiaret Tiaret Algeria Department of Mathematics Faculty of Mathematics and Computer Science Tiaret Algeria

This paper aims to investigate a non-degenerate Schrödinger equation with fractional integral type dynamic boundary control. We focus on establishing the well-posedness of the system by employing semigroup theory. Additionally, we apply the Borichev-Tomilov (Math. Ann. 301 347(2):455–478, 2010) theorem to demonstrate the existence of polynomial decay, which occurs in the absence of exponential stability. © The Author(s), under exclusive licence to Sociedad Española de Matemática Aplicada 2025.

关键词： C0-semigroup Multiplier method Non-exponential stability Well-posedness

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Fine-Tuned Attribute Weighted Naïve Bayes with Modified Partial Instances Reduction for Gaming Disorder Classification

HighTech and Innovation Journal

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HighTech and Innovation Journal 2025年第1期6卷 67-80页

作者： Latubessy, Anastasya Wardoyo, Retantyo Musdholifah, Aina Kusrohmaniah, Sri Doctoral Program Department of Computer Science and Electronics Faculty of Mathematics and Natural Science Universitas Gadjah Mada Yogyakarta55281 Indonesia Department of Informatics Engineering Faculty of Engineering Universitas Muria Kudus Indonesia Department of Computer Science and Electronics Faculty of Mathematics and Natural Science Universitas Gadjah Mada Yogyakarta55281 Indonesia Department of Psychology Faculty of Psychology Universitas Gadjah Mada Yogyakarta55281 Indonesia

Fine Tuning Attribute Weighted Naïve Bayes (FTAWNB) is a reliable modified Naïve Bayes model. Even though it is able to provide high accuracy on ordinal data, this model is sensitive to outliers. To improve the performance of FTAWNB, this research modified the Partial Instances Reduction (PIR) technique to make the FTAWNB more adaptive to outliers. Nevertheless, in contrast to the original PIR technique, which substitutes missing values for data values deemed outliers, the PIR technique suggested in this study replaces data values deemed outliers using a Naïve Bayes weighting approach. The attribute values from the outlier data are replaced with the highest probability values for the attributes in the actual class. This PIR technique is referred to as modified PIR. The FTAWNB model with modified PIR has been evaluated using the Gaming Disorder dataset. Replacing the four attributes with the least amount of information resulted in accuracy gains of 99.74%, an increase of 1.53% over the FTAWNB model. The experimental result shows that adding the modified PIR technique to the FTAWNB model can handle the outlier in the data, proving it by increasing the performance in terms of accuracy, precision, and recall without pruning the dataset used. © 2025, Ital Publication. All rights reserved.

关键词： Attribute Weighted Classification Fine-Tune Gaming Disorder Instances Reduction Naïve Bayes

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A New Keyed Hash Function Based on Compounded Chaotic Maps

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IEEE Access 2025年 13卷 75363-75376页

作者： Dascalescu, Ana-Cristina Boriga, Radu-Eugen Priescu, Iustin Titu Maiorescu University Faculty of Informatics Calea Văcărești 189 Bucharest040051 Romania University of Bucharest Faculty of Mathematics and Computer Science Academiei 14 Bucharest010014 Romania

In this paper, we firstly construct a new chaotic map by compounding a couple of chaotic maps and, using specific mathematical tools (i.e., Lyapunov exponent), we prove its sensitivity to the initial conditions and the underlying chaotic behavior. Secondly, using this chaotic map, we propose a new chaotic keyed hash function which involves each byte of the message in calculation of the chaotic map initial point and the compounded maps control parameters. Corroborating this method with the proven sensitivity of the used chaotic map, we obtain an avalanche effect in the hashing process and the guarantee that all the bits of the message will be related to the hash value. Moreover, the exhaustive numerical simulations show that the proposed hash function has very good confusion and diffusion capabilities, strong collision resistance, high level of security and good speed, being suitable for applications regarding data integrity or authentication, such as ciphers or blockchain applications. © 2013 IEEE.

关键词： Hash functions

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A systematic review on cybersecurity of robotic systems: vulnerabilities trends, threats, attacks, challenges, and proposed framework

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International Journal of Information Security 2025年第3期24卷 1-37页

作者： Verma, Narinder Kumar, Neerendra Verma, Chaman Illés, Zoltán Singh, Deep Department of Computer Science and IT Central University of Jammu Jammu181143 India Department of Media and Educational Informatics Faculty of Informatics Eötvös Loránd University Budapest1053 Hungary Department of Mathematics and Statistics Central University of Punjab Bathinda151401 India

Robotic systems are increasingly used in diverse applications such as healthcare, manufacturing, and critical infrastructure to automate day-to-day tasks. In this study, the existing state-of-the-art robotic system cybersecurity mechanisms are reviewed. Consequently, key aspects of the security mechanisms are highlighted. The study involves an analysis of applications in different domains, communication protocols, architecture, threats, and attacks associated with robotic systems. The systematic review of the existing work comprises inclusion and exclusion criteria, research protocol, initial search and keywords, searching, methodology diagram, research questions, and paper selection process. After analyzing the National Vulnerabilities Database, existing studies, and online resources, the resultant vulnerability trends are presented. The research asserts that cybersecurity measures including secure design, development, access control, and authentication are essential for robotic systems. Further, different machine learning, encryption, and blockchain-based mechanisms may be used to prevent or detect cyber-attacks in robotic systems. Based on comprehensive analysis, a cybersecurity framework is proposed to address the challenges effectively. The framework can be utilized to mitigate cybersecurity risks in robotic systems. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Cyber attacks

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Q-Rung Orthopair Fuzzy Sets-Enhanced FMEA for COVID-19 Risk Assessment

Informatica (Slovenia)

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Informatica (Slovenia) 2025年第1期49卷 81-92页

作者： Abdullah, Lazim Awang, Noor Azzah Qiyas, Muhammad Special Interest Group of Modelling and Data Analytics Faculty of Computer Science and Mathematics Universiti Malaysia Terengganu Kuala Nerus21030 Malaysia College of Computing Informatics and Mathematics Universiti Teknologi MARA Selangor Shah Alam40450 Malaysia Department of Mathematics Riphah International University Failsabad Campus Pakistan

Failure Modes and Effects Analysis (FMEA) is a widely used tool for risk analysis, primarily to identify risk factors affecting system quality. Due to the limitations of the traditional FMEA model, several recent models incorporating advanced fuzzy set extensions have been developed to enhance the reliability of risk assessment outcomes. However, most of these models limit expert flexibility in expressing preferences and often overlook the impact of unequal expert weights and the stability of risk ranking results. This study introduces a new FMEA model based on Q-Rung Orthopair Fuzzy Sets (Q-ROFSs), termed Q-ROFSs-FMEA. Q-ROFSs, an extension of intuitionistic fuzzy sets, introduce a new linguistic term. The Q-ROFSs-FMEA model considers the unequal weights of experts, enabling a dynamic representation of expert preferences. These weights and the linguistic evaluation of risk factors are integrated through an aggregation operator, facilitating consensus among experts. The model is applied to a case study on COVID-19 risk factors, revealing that ‘older age’ (risk priority number 0.000012) is the highest risk factor, while ‘gender’ (risk priority number -0.0037) is the lowest. It is found that the ranking of risk factors determined by the Q-ROFSs-FMEA model is obtained as FM1 FM3 FM6 FM4 FM5 FM7 FM8 FM2 . Furthermore, a comparative analysis indicates consistent ranking results across different models, demonstrating the reliability of the proposed model. The case study and comparative analysis validate the effectiveness and applicability of the Q-ROFSsbased risk assessment model. © 2025 Slovene Society Informatika. All rights reserved.

关键词： Failure modes

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RT-PPS: Real-time privacy-preserving scheme for cloud-hosted IoT data

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Journal of High Speed Networks 2025年第1期31卷 71-89页

作者： Elhoseny, Mohamed Riad, Khaled College of Computing and Informatics University of Sharjah Sharjah27272 United Arab Emirates Faculty of Computers and Information Mansoura University Mansoura35516 Egypt Computer Science Department College of Computer Sciences & Information Technology King Faisal University Al-Ahsa 31982 Saudi Arabia Mathematics Department Faculty of Science Zagazig University Zagazig44519 Egypt

The Internet of Things (IoT) is a rapidly growing network of devices that can communicate with each other and with cloud-based services. These devices generate vast amounts of data that can be used to provide valuable insights into user behavior, environmental conditions, and other important factors. However, as this data is collected and processed by cloud-hosted services, there is a growing concern about privacy and security. Without adequate protection, sensitive information could be exposed to hackers or other malicious actors, putting both individuals and organizations at risk. To address this challenge, real-time privacy-preserving techniques can be used to protect IoT data without compromising its value. This paper introduces an efficient Real-time privacy-preserving scheme (RT-PPS) for cloud-hosted IoT data. RT-PPS employs multi-authority attribute-based encryption on a hybrid cloud environment to keep data secure and private, while still allowing it to be processed and analyzed by cloud-hosted services. RT-PPS has efficient response time and resource consumption, which gives it the ability to handle a huge number of concurrent users at the same time without notable delay. The proposed RT-PPS has been validated through extensive experimental evaluation on a variety of configurations. Moreover, the proposed scheme has been computationally compared with the state-of-the-artwork. RT-PPS has shown excellent performance, effectiveness, and efficiency. The RT-PPS encryption time for a 1 GB dataset while considering 1024 slices is approximately 1000 ms. Also, the RT-PPS decryption time for a 1 GB ciphertext while considering 1024 slices are approximately 235 ms. Finally, RT-PPS is proven secure against any polynomial-time attacks and their variations that have at most a negligible advantage in the introduced security model. Moreover compared to most of the state-of-the-artwork, RT-PPS reduced the ciphertext size and lowered the computations in the encryption, key g

关键词： Ciphertext

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Supervised learning applied to electrocardiogram statistical features for the detection of premature ventricular contraction

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Research on Biomedical Engineering 2025年第1期41卷 1-12页

作者： Issa, Khouloud Rammal, Abbas Assaf, Rabih Ghandour, Ahmad Electrical and Communication Engineering Department College of Engineering Phoenicia University Zahrani South Lebanon Statistics and Informatics Department Faculty of Science Lebanese University Beirut Lebanon Mathematics and Computer Sciences Department Faculty of Arts and Sciences Lebanese American University Beirut Lebanon Department of Mathematics Faculty of Arts and Sciences Holy Spirit University of Kaslik Jounieh Lebanon Biomedical Engineering Department Faculty of Engineering Islamic University of Lebanon Wardenieh30014 Lebanon

Purpose: The development of an automated premature ventricular contraction (PVC) detection system has significant implications for early intervention and treatment decisions. This study aims to develop a novel approach using various supervised machine learning (ML) methods for detecting PVCs in electrocardiogram (ECG) recordings. Methodology: To achieve this, we extracted ten distinct statistical and temporal features from 33 long-term ECG recordings from the benchmark MIT-BIH arrhythmia database (MIT-BIH-AD), capturing significant characteristics from the signals. We then investigated the effectiveness of traditional ML algorithms in identifying PVCs based on these features, namely support vector machine (SVM), decision tree (DT), naïve Bayes (NB), k-nearest neighbor (KNN), linear discriminant analysis (LDA), and artificial neural network (ANN). Results: Among these classifiers, the SVM, KNN, ANN, and DT classifiers demonstrated exceptional discriminatory power and classification performance, yielding near-perfect area under the receiver operating characteristic curve (AUC-ROC) values of 97.3%, 95.4%, 95%, and 94.1%, respectively. On the other hand, the SVM classifier emerged as the most accurate, achieving an overall accuracy of 97.39%, indicative of making correct predictions. Conclusion: These findings underscore the generalization of the proposed approach, especially since we worked on an extended dataset encompassing different types of heartbeats to discriminate PVCs from other heartbeat types, not only normal ones, and providing closer alignment with real-world scenarios. Subsequently, the robustness and accuracy of these models highlight their suitability for clinical applications and their potential for efficient implementation and deployment in the diagnosis of cardiovascular diseases (CVDs), as they demand minimal computational resources and time. © The Author(s), under exclusive licence to The Brazilian Society of Biomedical Engineering 2025.

关键词： Decision trees

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Enhanced Speech Emotion and Gender Recognition Using Hybrid CNN-LSTM Models 4

Enhanced Speech Emotion and Gender Recognition Using Hybrid ...

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4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Priyadharshini, S. Sundar, G. Naveen Narmadha, D. Thangavel, Senthil Kumar Ajibesin, Adeyemi Abel Kolandapalayam Shanmugam, Selvanayaki Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Coimbatore India Amrita School of Computing Department of Computer Science and Engineering Coimbatore India Cape Peninsula University of Technology Faculty of Informatics and Design Department of Information Technology South Africa Ashland University Department of Mathematics and Computer Science United States

ISBN: (纸本)9798331523923

The current paper proposes a new approach for peripheral speech emotion analysis and gender estimation incorporating the best machine learning architectures such as CNNs and LSTMs. Its correct depiction of emotions and the variation of the gendered speech to indicate manifold signal-to-noise ratio make the approach accommodate the difficulty inherent in recognizing emotions from the recording of voices as well as predicting the gender of a speaker. It is then able to ally with preprocessing and collection of a vast range of different speech samples, feature extraction of pitch, tone and spectral data. These features serve as input to the CNNs and LSTMs: LSTMs work well at temporal regular features and the CNNs work well in feature extraction by location (spatio feature). The approach is tested on the RAVDESS and IEMOCAP datasets and establishes a near perfect match to prior approaches with reference to recognition accuracy of emotion analysis and gender prediction. Thus, applying the identified dual method approach, which could be described by such characteristics as highly accurate data pre-preprocessing, clear indication of the features of interest, a different CNN-LSTM model joint training, it offers a reasonably good platform to gain certain insights into such characteristics of the speech as our experiment demonstrates. This work offers satisfactory configurations on concerns such as human computer relation, customer relation and mental health surveillance to suggest that other applications could be achieved in future. © 2025 IEEE.

关键词： Convolutional neural networks

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Generalized saturation game

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Discrete Applied mathematics 2025年 374卷 33-49页

作者： Patkós, Balázs Stojaković, Miloš Stratijev, Jelena Vizer, Máté HUN-REN Alfréd Rényi Institute of Mathematics Reáltanoda utca 13-15 Budapest1053 Hungary Department of Mathematics and Informatics Faculty of Sciences University of Novi Sad Novi Sad21000 Serbia Department of Fundamental Sciences Faculty of Technical Sciences University of Novi Sad Novi Sad21000 Serbia Department of Computer Science and Information Theory Budapest University of Technology and Economics Budapest Hungary

We study the following game version of the generalized graph Turán problem. For two fixed graphs F and H, two players, Max and Mini, alternately claim unclaimed edges of the complete graph Kn such that the graph G of the claimed edges must remain F-free throughout the game. The game ends when no further edges can be claimed, i.e. when G becomes F-saturated. The H-score of the game is the number of copies of H in G. Max aims to maximize the H-score, while Mini wants to minimize it. The H-score of the game when both players play optimally is denoted by s1(n,#H,F) when Max starts, and by s2(n,#H,F) when Mini starts. We study these values for several natural choices of F and H. © 2025 Elsevier B.V.

关键词： Trees (mathematics)

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A STUDY ON SOME CLASSES OF PANTOGRAPH LANGEVIN FRACTIONAL DIFFERENTIAL PROBLEMS WITH NONLOCAL CONDITIONS

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Journal of Mathematical sciences (United States) 2025年 1-18页

作者： Bouzid, Houari Benali, Abdelkader Salim, Abdelkrim Erhan, İnci M. Department of Mathematics Faculty of Exact Science and Informatics Laboratory of Mathematics and Applications (LMA) Hassiba Benbouali University of Chlef Ouled Fares Chlef 02000 Algeria Faculty of Technology Hassiba Benbouali University of Chlef Chlef 02000 Algeria Laboratory of Mathematics Djillali Liabes University of Sidi Bel-Abbes Sidi Bel-Abbes 22000 Algeria Department of Computer Engineering Aydın Adnan Menderes University Aydın 09010 Turkey

This paper concentrates on the examination of a class of nonlocal initial value problems for Langevin fractional differential equations featuring the ψ-Caputo fractional derivative within Banach spaces. By utilizing Banach’s fixed-point theorem, we establish the uniqueness of the solutions to these problems. The existence of solutions is then confirmed using Schaefer’s and Darbo’s fixed-point theorems. Finally, we provide examples to illustrate our findings. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Darbo theorem Fractional differential equations (FDE) Measure of noncompactness ψ-fractional integral

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