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ArabRecognizer: modern standard Arabic speech recognition inspired by DeepSpeech2 utilizing Franco-Arabic

International Journal of Speech technology 2024年第3期27卷 673-686页

作者： Nasef, Mohammed M. Elshall, Amr A. Sauber, Amr M. Mathematics and Computer Science Department Faculty of Science Menoufia University Shebin el Koom32511 Egypt

Speech recognition is a critical task in spoken language applications. Globally known models such as DeepSpeech2 are effective for English speech recognition, however, they are not well-suited for languages like Arabic. This paper is interested in recognizing the Arabic language, especially Modern Standard Arabic (MSA). This paper proposed two models that utilize "Franco-Arabic" as an encoding mechanism and additional enhancements to recognize MSA. The first model uses Mel-Frequency Cepstral Coefficients (MFCCs) as input features, while the second employs six sequential Gated Recurrent Unit (GRU) layers. Each model is then followed by a fully connected layer with a dropout layer which helped reduce overfitting. The Connectionist Temporal Classification (CTC) loss is used to calculate the prediction error and to maximize the correct transcription likelihood. Two experiments were conducted for each model. The first experiment involved 41 h of continuous speech over 15 epochs. Whereas, the second one utilized 69 h over 30 epochs. The experiments showed that the first model excels in speed while the second excels in accuracy, and both outperformed the well-known DeepSpeech2. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Speech recognition

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Combinatorial Properties of Involutive Fibonacci Arrays

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2024年第5期51卷 553-561页

作者： Blasiyus, Hannah Christy, D. K. Sheena Department of Mathematics Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur603203 India Department of Mathematics Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur603203 India

Various scholars have investigated Fibonacci arrays to uncover its combinatorial features and applications. As an extension of Involutive Fibonacci words, Involutive Fibonacci arrays were introduced. We will look at some of the combinatorial features of Involutive Fibonacci Arrays in this article. © (2024), (International Association of Engineers). All Rights Reserved.

关键词： Computational methods

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Multi-Attribute Group Decision-Making Method under Spherical Fuzzy Bipolar Soft Expert Framework with Its Application

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computer Modeling in Engineering & sciences 2023年第11期137卷 1891-1936页

作者： Mohammed M.Ali Al-Shamiri Ghous Ali Muhammad Zain Ul Abidin Arooj Adeel Department of Mathematics Faculty of Science and ArtsMahayl AssirKing Khalid UniversityAbhaSaudi Arabia Department of Mathematics and Computer Faculty of ScienceIbb UniversityIbbYemen Department of Mathematics Division of Science and TechnologyUniversity of EducationLahorePakistan

Spherical fuzzy soft expert set(SFSES)theory blends the perks of spherical fuzzy sets and group decision-making into a unified *** allows solutions to highly complicated uncertainties and ambiguities under the unbiased supervision and group decision-making of multiple ***,SFSES theory has some deficiencies such as the inability to interpret and portray the bipolarity of *** work highlights and overcomes these limitations by introducing the novel spherical fuzzy bipolar soft expert sets(SFBSESs)as a powerful hybridization of spherical fuzzy set theory with bipolar soft expert sets(BSESs).Followed by the development of certain set-theoretic operations and properties of the proposed model,important problems,including the selection of non-powered dam(NPD)sites for hydropower conversion are discussed and solved under the proposed *** problems mainly focus on the need for an efficient tool capable of considering the bipolarity of parameters,complicated ambiguities,and multiple *** the new approach by a detailed comparative analysis,it is concluded that the proposed model is more comprehensive and reliable for multi-attribute group decisionmaking(MAGDM)than the previous tools,particularly considering the bipolarity of parameters under SFSES environment.

关键词： Spherical fuzzy sets bipolar soft expert sets group decision-making algorithm non-powered dams

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Characteristics of new stochastic solutions to the (2+1)-dimensional nonlinear Schrödinger model via Wiener process

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Optical and Quantum Electronics 2025年第1期57卷 1-15页

作者： Alharbi, Yousef F. Ammar, Sherif I. Abdelrahman, Mahmoud A. E. Department of Mathematics College of Science Taibah University Madinah Saudi Arabia Department of Mathematics and Computer Science Faculty of Science Menofia University Menofia Egypt Department of Mathematics Faculty of Science Mansoura University Mansoura35516 Egypt

We utilize the unified approach and He’s semi-inverse method to derive novel stochastic optical solutions for the (2 + 1)-dimensional nonlinear Schrödinger equation (2D-NLSE) in the context of Itôcalculus. The solutions obtained encompass distinct structures such as super solitons and collapsing dissipative waves. These solutions hold significant potential for elucidating physical phenomena across various domains, including stochastic plasma media, ocean waves, and optical fiber. We investigate the dependence of the 2D-NLSE wave solutions on the physical model parameters, namely the group velocity dispersion, nonlinearity and linear coefficients. These parameters play a crucial role in regulating the amplitude and phase of optical communication waves during propagation. Graphical representations of selected solutions are provided to visually demonstrate their dynamic characteristics. The presented solutions expand the possibilities for optical manipulation and offer prospects for addressing practical challenges. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Group velocity dispersion

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Reliability analysis of three state linear consecutive 2-out-of-4:F system by continuous time Markov model

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International Journal of Reliability and Safety 2024年第3期18卷 252-265页

作者： Madhumitha, J. Vijayalakshmi, G. Department of Mathematics and Statistics Faculty of Science and Humanities SRM Institute of Science and Technology Tamil Nadu Kattankulathur India Department of Mathematics Faculty of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur India

In this paper, the continuous time Markov model for the L (cons/2-4:F) system is described. Each component of the system has three states (good state, degraded state and failed state). The failure and repair times follow an exponential distribution. The dependability measures such as availability and reliability are obtained. The effects of failure and repair rates on system availability and system reliability are presented. The mathematical consequences of the reliability measures will be of incredible assistance to the system engineers and decision-makers in improving and designing the system in future. The proposed system can be used in nuclear power plants and telecommunication systems. © 2024 Inderscience Enterprises Ltd.

关键词： Continuous time systems

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Throughput Prediction Using LS-SVM For 4g-LTE Network and Beyond

Throughput Prediction Using LS-SVM For 4g-LTE Network and Be...

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2024 International Conference on Telecommunications and Intelligent Systems, ICTIS 2024

作者： Hamdani, Mostefa Sahnoune, Ahmed Merzougui, Mokhtar Douara, Abdelmalek Khatemi, Fouad University El Wancharissi Laboratory of Electronics Computer Science and Applied Mathematics Faculty of Science and Technology Department of Mathematics and Computer Science Algeria University El Wancharissi Laboratory of Electronics Computer Science and Applied Mathematics Faculty of Science and Technology Department of Science and Technology Algeria

ISBN: (纸本)9798331527396

The integration of Artificial Intelligence(AI) with Long-Term Evolution (LTE) networks offers substantial potential for improving communication infrastructure. By harnessing AI algorithms, it is possible to dynamically optimize network parameters, proactively predict and mitigate equipment failures, and enhance Quality of Service (QoS) by prioritizing critical services through real-time analysis of key performance indicators. This study focuses on predicting network throughput using Least Square Support Vector Machine (LS-SVM). The predictive models developed can trigger adaptive network reconfigurations, ensuring that the network responds promptly to changing conditions. Simulation results reveal that the integration of LS-SVM significantly improves prediction accuracy, enabling more effective implementation of self-organizing network strategies in real-time. © 2024 IEEE.

关键词： Long Term Evolution (LTE)

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Fast Algorithms for Edge Coloring in Clustered Hypergraphs: A Study of Computational Efficiency

Mari Papel y Corrugado

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Mari Papel y Corrugado 2024年第1期2024卷 143-151页

作者： Sabti, Wasan Mustafa Jawad Shirde, Gholam Hassan Middle Technical University Institute of Technology Baghdad Baghdad Iraq Department of Mathematics and Computer Science Faculty of Science University of Qom Qom Iran

The generalization of edge coloring in hypergraphs, especially clustered ones, remains an open problem due to the intricate structure and organization of hyper-edges grouped in clusters. This study addresses the computational challenges associated with edge coloring in clustered hypergraphs by introducing a novel suite of fast algorithms specifically designed to achieve improved accuracy and computation time. The algorithms utilize structural properties such as hypergraph Laplacian spectral features and submodular optimization to enhance efficiency. Experimental results demonstrate a 10-15% improvement in clustering accuracy and a 20% reduction in computational time compared to baseline methods, validating the approach for both synthetic and real-world datasets. These findings contribute to hypergraph theory and propose a practical solution for applications in network layout, parallel computing frameworks, and data organization. Future work could further optimize these algorithms for large-scale real-time applications. © The authors.

关键词： Consensus algorithm

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On thermoelastic problem based on four theories with the efficiency of the magnetic field and gravity

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Journal of Ocean Engineering and science 2024年第4期9卷 338-347页

作者： A.A.Kilany A.N.Abd-alla A.M.Abd-Alla S.M.Abo-Dahab Department of Mathematics Faculty of ScienceSohag UniversitySohag 82524 Egypt Department of Computer Science Faculty of Computers and InformationLuxor UniversityEgypt Department of mathematics Faculty of ScienceSouth Valley UniversityQena 83523Egypt

The fundamental objective of this paper is to study the effectiveness of magnetic field and gravity on an isotropic homogeneous thermoelastic structure based on four theories of generalized *** another meaning,the models of coupled dynamic theory(CDT),Lord-Shulman(LS),Green-Lindsay(GL)as well as Green-Naghdi(GN II)will be taken in the ***,applying the harmonic method(normal mode technique),the solution of the governing equations and the expressions for the components of the displacement,temperature and(Mechanical and Maxwell’s)stresses is taken into account and calculated *** impacts of the gravity and magnetic field are illustrated graphically which are pronounced on the different physical ***,the results of some research that others have previously obtained may be found some or all of them as special cases from this study.

关键词： Generalized thermoelasticity Gravity Magnetic field Green and Naghdi TheoryⅡ Normal mode approach

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Rice spikelet’s disease detection using hybrid optimization model and optimized CNN

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Soft Computing 2024年第21期28卷 12787-12806页

作者： Patel, Bharati Department of Computer Science and Engineering Faculty of Science and Technology ICFAI University Raipur India

Rice fields all across the world are affected by spikelet sterility, often known as rice spikelet's disease. It is characterized by the improper development of spikelet’s, which lowers grain output and quality. For optimal management and the avoidance of yield losses, this disease must be discovered early. In this study, a deep learning-based approach utilizing optimization techniques was proposed for accurate segmentation and disease detection in rice crops. The research aimed to address the vulnerability of rice crops to disease attacks from seed germination to mature spikelets. The proposed model consisted of three major phases: pre-processing, segmentation, feature extraction and disease detection. Gaussian filtering was employed to preprocess the raw rice crop images, while a new hybrid Whale Customized Gravitational Optimization Algorithm was utilized for segmentation. Disease detection was performed using a hybrid deep learning model called HybridNet, which combines convolutional neural networks (CNN) with an optimized recurrent neural network (RNN) model. The dataset intended for this proposed project is sourced from the CABI PlantwisePlus Knowledge Bank. The proposed model for rice spikelet disease detection achieved high accuracy with Sensitivity (0.9269), Specificity (0.9756), and Accuracy (0.9634). This indicates that the model effectively identifies and detects diseases in rice spikelets, demonstrating its reliable performance in disease management and crop protection. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Convolutional neural networks

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Community Clustering on Fraud Transactions Applied the Louvain-Coloring Algorithm

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International Journal of Electronics and Telecommunications 2023年第3期69卷 593-598页

作者： Mardiansyah, Heru Suwilo, Saib Nababan, Erna Budiarti Efendi, Syahril Department Computer Science Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department Mathematics Faculty of Mathematics and Natural Sciences Universitas Sumatera Utara Medan Indonesia Department Data Science and Artificial Intelligence Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

The contribution main from this research is modularity and better processing time in detecting community by using K-1 coloring. Testing performed on transaction datasets remittance on P2P platforms where the Louvain Coloring algorithm is better in comparison to Louvain Algorithm Data used is data transfer transactions made by customers on the P2P Online platform. The data is the User data that has information transfer transactions, Card data that has information card, IP data that has IP information, and Device data that has information device. Every user owns unique 128-bit identification, and other nodes representing card, device, and IP are assigned a random UUID. The Device node has the guide, and device properties. IP nodes only have property guide and node User has property fraud Money Transfer, guide, money Transfer Error Cancel Amount, first Charge back Date. Each node has a unique 128-bit guide, with the amount whole of as many as 789,856 nodes. Application technique K-1 staining on Louvain algorithm shows enhancement value modularity and better processing time for detecting community on the network large scale. Through a series of exercises and tests carried out in various scenarios, it shows that the experiments carried out in this paper, namely the Louvain Coloring algorithm, are more effective and efficient than the Louvain algorithm in scenario 1,3, and 5 meanwhile For Scenarios 2 and 4 Louvain Algorithm is better. © 2023 Polish Academy of sciences. All rights reserved.

关键词： Clustering algorithms

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