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Automatic speaker identification system based on MLP network and deep learning in the presence of severe interference

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Multimedia Tools and Applications 2025年 1-42页

作者： Shafik, Amira Sedik, Ahmed El-Shafai, Walid Khalaf, Ashraf A. M. El-Rabaie, El-Sayed M. El-Samie, Fathi E. Abd Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Electrical Engineering Faculty of Engineering Minia University Minia61519 Egypt Smart Systems Engineering Laboratory College of Engineering Prince Sultan University Riyadh11586 Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial Intelligence Kafr Elsheikh University Kafr El‑Shaikh Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Automatic Speaker Identification (ASI) is so crucial for security. Current ASI systems perform well in quiet and clean surroundings. However, in noisy situations, the robustness of an ASI system against additive noise and interference is a crucial factor. An investigation of the impact of interference on ASI system performance is presented in this paper, which introduces algorithms for achieving high ASI system performance. The objective is to resist the interference of various forms. This paper presents two models for the ASI task in the presence of interference. The first one depends on Normalized Pitch Frequency (NPF) and Mel-Frequency Cepstral Coefficients (MFCCs) as extracted features and Multi-Layer Perceptron (MLP) as a classifier. In this model, we investigate the utilization of a Discrete Transform (DT), such as Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Discrete Sine Transform (DST), to increase the robustness of extracted features against different types of degradation through exploiting the sub-band decomposition characteristics of DWT and the energy compaction property of DCT and DST. This is achieved by extracting features directly from contaminated speech signals in addition to features extracted from discrete transformed signals to create hybrid feature vectors. The enhancement techniques, such as Spectral Subtraction (SS), Winer Filter, and adaptive Wiener filter, are used in a preprocessing stage to eliminate the effect of the interference on the ASI system. In the second model, we investigate the utilization of Deep Learning (DL) based on a Convolutional Neural Network (CNN) with speech signal spectrograms and their Radon transforms to increase the robustness of the ASI system against interference effects. One of this paper goals is to introduce a comparison between the two models and build a more robust ASI system against severe interference. The experimental results indicate that the two proposed models lead to satisfa

关键词： Additive noise

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An Injection Circuit Coupling Low-DC Voltage Impedance Matching System with Flexible Resonance Points for Square-Wave Voltage Power Amplifier in EM Exploration

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IEEE Transactions on Power Electronics 2025年第8期40卷 11032-11050页

作者： Pang, Ying Zhu, Yongji Ji, Yanju Li, Gang Xiang, Zeng Gong, Cheng Han, Rong Tian, Wei Guo, Qun Wong, Man-Chung Lin, Jun State Key Laboratory of Deep Earth Exploration and Imaging College of Instrumentation and Electrical Engineering Jilin University Chаngсhun China College of Instrumentation and Electrical Engineering Jilin University Changchun China Tongda Electromagnetic Energy Company Ltd. Changsha China State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau Macao China Institute of Microelectronics University of Macau Macao China Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macao China School of Optoelectronic Engineering and Instrumentation Science Dalian University of Technology Dalian China School of Electrical Engineering Guangxi University Nanning China College of Marine Electrical Engineering Dalian Maritime University Dalian China State Key Laboratory of Internet of Things for Smart City University of Macau Macao China

This paper focuses on reactive power compensation and impedance matching of square-wave voltages. Square-wave voltage is the operating voltage in electromagnetic method (EM) exploration. The characteristics of a square-wave voltage are very different from those of a sinusoidal voltage in the power grid. Although some papers proposed impedance matching converters for square-wave voltages, they solved the high DC voltage requirement problem. The problem is caused by square-wave voltage having multiple and variable spectral components. An impedance-matching converter with an injection circuit (IMFR) for square-wave voltage is proposed. IMFR is composed of a thyristor-controlled inductor and capacitor (TCLC) part and injection circuit coupling active Hbridge part. TCLC can be controlled to resonate at the highest energy fundamental frequency for damping the largest part of the DC voltage requirement. The use of TCLC offsets the varying fundamental frequency demand on the DC voltage. First, this paper gives a joint design and optimization approach for the lowest DC voltage requirement. Second, a synergistic control method of proposed IMFR is provided implementing IMFR. Third, two groups of comparative experiments show the proposed IMFR can enlarge the current by 11.8% – 38.5%. The effect on the current increase is 4.4% – 7.9% higher than using only the H-bridge of the previous method when they are operated with the same DC voltage. ©1986-2012 IEEE.

关键词： Natural frequencies

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Sensitivity of DC Network Representation for GIC Analysis

Sensitivity of DC Network Representation for GIC Analysis

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2025 IEEE Texas Power and Energy Conference, TPEC 2025

作者： Mishra, Aniruddh Barnes, Arthur K. Tabarez, Jose E. Mate, Adam University of Texas at Austin Department of Electrical and Computer Engineering AustinTX United States Information Systems and Modeling Group Los Alamos National Laboratory Los AlamosNM United States

ISBN: (纸本)9798331541125

Geomagnetic disturbances are a threat to the reliability and security of our national critical energy infrastructures. These events specifically result in geomagnetically induced currents, which can cause damage to transformers due to magnetic saturation. In order to mitigate these effects, blocker devices must be placed in optimal locations. Finding this placement requires a dc representation of the ac transmission lines, which this paper discusses. Different decisions in this process, including the method of representing the blocking devices, result in significant variations to the power loss calculations. To analyze these effects, we conclude the paper by comparing the losses on a sample network with different modeling implementations. © 2025 IEEE.

关键词： Transformer windings

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Intelligent Cyber Defense: Leveraging LLMs for Real-Time Threat Detection and Analysis 21st

Intelligent Cyber Defense: Leveraging LLMs for Real-Time Th...

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21st European, Mediterranean, and Middle Eastern Conference on Information systems, EMCIS 2024

作者： Kakoulli, Elena Zacharioudakis, Eleftherios Evripidou, Salomi Intelligent Systems Laboratory Department of Computer Science Neapolis University Pafos Pafos Cyprus Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine

ISBN: (纸本)9783031813214

This paper reviews the application of Large Language Models (LLMs) in addressing the growing sophistication of cybersecurity threats. By evaluating numerous studies, we delineate the role of LLMs in improving the detection, analysis, and response to cyber threats in real-time. Our findings demonstrate that LLMs significantly enhance the efficiency and accuracy of cybersecurity measures compared to traditional models. However, their deployment in cybersecurity frameworks involves critical considerations around ethics, privacy, and security. This review provides a succinct overview of LLMs’ current capabilities and practical implementations within the cybersecurity landscape, identifies research gaps, and suggests future research directions. The insights presented here highlight the vital contribution of LLMs to the advancement of cybersecurity solutions and adapting to evolving threat environments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Cyber attacks

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XMeta-OS: A Conceptual Framework for Unified Resource Management in Distributed Edge-Cloud Environments 3rd

XMeta-OS: A Conceptual Framework for Unified Resource Manag...

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3rd International Conference on Advances in Computing Research, ACR 2025

作者： Zacharioudakis, Eleftherios Kakoulli, Elena Evripidou, Salomi Intelligent Systems Laboratory Department of Computer Science Neapolis University Pafos Pafos Cyprus National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus

ISBN: (纸本)9783031876462

This paper introduces XMeta-OS, a meta-operating system specially designed with Linux as its foundation to unify and optimize resource management for the distributed edge-cloud when dynamic use of GPU resources is possible. This approach offer a new GPU abstraction layer and dynamic edge-cloud allocation model that offer enhanced flexibility and resource utilization over existing systems like Kubernetes and OpenStack. By using likely sensitive data, the model applied cloud-pushed deployment model. XMeta-OS manages computer resources in real-time. Therefore, fulfilling high performance various needs. It allocates CPU and GPU in real-time to workloads requiring massive parallel processing, such as machine learning, scientific simulations, real-time data analytics, and transportation tasks. Fabrication in the laboratory of an edge-cloud environment can help to assess the scalability, fault tolerance and efficiency of the system. It showcases the overall architectural design of XMeta-OS. Changes to the kernel and security solutions for safe and effective distribution are suggested. This article presents the design of the XMeta-OS. The future of XMeta-OS entails usage and testing with which we see latency, energy, computation and other such measurements in labs. XMeta-OS is a solution to cost performance, emerging application, large-scale edge-cloud deployments, and distributed GPU-enabled infrastructures. Meta-Operating System in Edge-Cloud Continuum for dynamic resource management of GPU. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Cluster computing

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Age of Information in Internet of Vehicles: A Discrete-Time Multisource Queueing Model

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IEEE Transactions on Communications 2025年第5期73卷 3298-3317页

作者： Zhang, Tianci Chen, Zhengchuan Tian, Zhong Wang, Min Zhen, Li Wu, Dapeng Oliver Li, Yonghui Quek, Tony Q. S. Chongqing University School of Microelectronics and Communication Engineering Chongqing400044 China Shaanxi Key Laboratory of Information Communication Network and Security Xi’an University of Posts and Telecommunications Xi’an710122 China Chongqing University of Posts and Telecommunications School of Optoelectronics Engineering Chongqing400065 China City University of Hong Kong Department of Computer Science Hong Kong The University of Sydney School of Electrical and Information Engineering SydneyNSW2050 Australia Singapore University of Technology and Design Department of Information Systems Technology and Design Tampines 487372 Singapore Yonsei University Yonsei Frontier Laboratory Seoul03722 Korea Republic of

This work studies information freshness of a V2I status updating link in IoV. The status updating link is modeled as a multi-source Ber/Geo/1/1 non-preemptive or preemptive queue. We focus on statistical characteristics of the age of information (AoI) and peak AoI (PAoI). To fully track the AoI evolutions under non-preemptive and preemptive policies, Markov three-dimensional age process (3DAP) and two-dimensional age process (2DAP) are respectively introduced. Their first element is the AoI process;The second one stands for if an update of the concerned source is in transmission and its current age;The third element of 3DAP denotes if an update of another source is in transmission. An analytical approach for studying the AoIs and PAoIs in discrete-time multi-source systems is presented. By studying the state transitions, balance equations, and stationary distributions of 3DAP and 2DAP, analytical expressions of the distributions and averages of AoIs and PAoIs under both queueing policies are derived. Moreover, the optimal probabilistic update selection mechanism (PUSM) that maximizes overall freshness is derived in closed-form for the two-source case. Numerical results validate effectiveness of the theoretical analyses and reveal usefulness of the retransmission. It is found that in terms of improving the overall freshness, the PUSM should be designed to make effective update generation probabilities of sources as close as possible. © 1972-2012 IEEE.

关键词： Queueing theory

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TopoEEG: A Timesformer-Based Topographic Image Representation Method for Single-Trial Early Detection of P300

TopoEEG: A Timesformer-Based Topographic Image Representatio...

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IEEE International Symposium on Biomedical Imaging

作者： Jiazhen Hong Laleh Najafizadeh Department of Electrical and Computer Engineering Integrated Systems and NeuroImaging Laboratory Rutgers University

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Detecting P300 event-related potentials (ERPs) from electroencephalography (EEG) finds applications in several domains including brain computer interfaces (BCIs). Due to the low signal-to-noise ratio (SNR), however, detecting P300 from single trials has been challenging. As a result, multiple repetitions are typically needed, extending the BCI decision time. To address this problem, in this paper, we present TopoEEG, a novel method that generates a sequence of topography-based images from EEG, to capture both spatial and temporal information. These sequences are subsequently processed using the state-of-the-art video classification technique, TimeSformer. Evaluated using the BCI Competition II (IIb) dataset, results demonstrate that TopoEEG achieves single-trial P300 detection with F1-scores of 0.6830 and 0.7134 within the first 500 ms and 600 ms, respectively. These results highlight TopoEEG's potential to enhance the efficiency and speed of BCIs by reducing the need for multiple repetitions and the time required for decision-making in single-trial P300 detection.

关键词： Electric potential Attention mechanisms Decision making Image representation Electroencephalography Brain-computer interfaces Signal to noise ratio Biomedical imaging

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Uncovering Spatiotemporal Differences in Cortical Activity Corresponding to two Tasks Using Data-Driven ADASSO Algorithm

Uncovering Spatiotemporal Differences in Cortical Activity C...

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IEEE International Symposium on Biomedical Imaging

作者： Siwei Mai Ali E. Haddad Laleh Najafizadeh Department of Electrical and Computer Engineering Integrated Systems and NeuroImaging Laboratory Rutgers University Department of Computer Engineering University of Basrah

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Identifying spatiotemporal differences in brain functional dynamics corresponding to two tasks is critical for under-standing how specific neural processes contribute to distinct tasks or cognitive functions. Traditional methods rely on imposing assumptions and limits on the location and timing of activities, while machine-learning-based methods generally lack offering interpretable insights. This highlights the need for new data-driven approaches to capture spatial and temporal differences in brain activity between two tasks, while also providing interpretable explanations of the neural processes underlying these differences. In this work, we formulate the problem of finding the spatial and temporal differences in the dynamics of brain function corresponding to two motor imagery (MI) tasks (left hand movement vs right hand movement) as a discriminative discrete basis problem (DDBP). We apply the data-driven asymmetric discriminative associative algorithm (ADASSO) to EEG data collected during these tasks to uncover the key functional components of the brain's functional dynamics that differentiate between them. Results suggest that hand movements are strongly associated with high-confidence activation in the motor cortex, verifying the effectiveness of the ADASSO algorithm in identifying the location and timing of cortical activities that distinguish between the two task classes.

关键词： Hands Brain Heuristic algorithms Motors Electroencephalography Brain-computer interfaces Spatiotemporal phenomena Timing Biomedical imaging

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A variable structure model of neurons’ application in computer vision

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Multimedia Tools and Applications 2025年 1-11页

作者： Sridi, Alaeddine Attia, Mouna Bouallegue, Kais Electronics and Micro-Electronics Laboratory Faculty of Sciences of Monastir University of Monastir Monastir Tunisia The Higher Institute of Computer Science and Communication Technologies of Hammam Sousse University of Sousse Sousse Tunisia Laboratory of Computer Science Parallelism and Intelligent Communicating Systems Faculty of Sciences of Tunisia University of Tunis ELManar Tunis Tunisia Department of Electrical Engineering Higher Institute of Applied Sciences and Technology of Sousse University of Sousse Sousse Tunisia

The neuron doctrine defines the neuron as the basic unit of the nervous system, which drives the dynamic behavior of our organs. This has led to neurons becoming the focus of modern neuroscience research and to the rise of neurocomputing, in which we try to digitally simulate human behavior. The goal being to better understand the human nervous system and gain more control over neuron-related diseases, helping doctors establish faster and more reliable medical diagnoses. In this context, we aim to simulate eye diseases and vision problems by convolving input images using a new class of neural networks based on a variable structure model of neurons presented in [1]. In this work, we focus on recreating the common convolution filters as a first step. This is the first time in neurocomputing literature that dendritic neurons have been used for dynamic convolution kernels generation and eye diseases simulation. We start with a presentation of our upgrades to the model’s flexibility and accuracy. Then, we propose a novel kernel generator algorithm to convolve the input images. Finally, we show its promising results in creating the outline, pixelization, and night convolution kernels, as well as control some metrics, including brightness and data retention. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Neurons

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Modeling of UV NLoS Communication Channels: From Atmospheric Scattering and Obstacle Reflection Perspectives

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IEEE Journal on Selected Areas in Communications 2025年第5期43卷 1590-1606页

作者： Wu, Tianfeng Yang, Fang Cao, Tian Cheng, Ling Chen, Yupeng Song, Jian Cheng, Julian Han, Zhu Department of Electronic Engineering Beijing100084 China State Key Laboratory of Widegap Semiconductor Optoelectronic Materials and Technologies Beijing100084 China Xidian University School of Telecommunications Engineering Xi’an710071 China University of the Witwatersrand School of Electrical and Information Engineering Johannesburg2000 South Africa Southern University of Science and Technology School of Microelectronics Shenzhen518055 China Tsinghua University Department of Electronic Engineering Beijing100084 China Tsinghua University Shenzhen International Graduate School Shenzhen518055 China The University of British Columbia School of Engineering KelownaBCV1V 1V7 Canada University of Houston Department of Electrical and Computer Engineering Houston77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

As transceiver elevation angles increase from small to large, existing ultraviolet (UV) non-line-of-sight (NLoS) models encounter two challenges: 1) cannot estimate the channel characteristics of UV NLoS communication scenarios when there exists an obstacle in the overlap volume between the transmitter beam and the receiver field-of-view (FoV), and 2) cannot evaluate the channel path loss for the wide beam and wide FoV scenarios with existing simplified single-scattering path loss models. To address these challenges, a UV NLoS scattering model incorporating an obstacle was investigated, where the obstacle’s orientation angle, coordinates, and geometric dimensions were taken into account to approach actual application environments. Then, a UV NLoS reflection model was developed combined with specific geometric diagrams. Further, a simplified single-scattering path loss model was proposed with a closed-form expression. Finally, the proposed models were validated by comparing them with the Monte-Carlo photon-tracing model, the exact single-scattering model, and the latest simplified single-scattering model. Numerical results show that the path loss curves obtained by the proposed models agree well with those attained by related NLoS models under identical parameter settings, and avoiding obstacles is not always a good option for UV NLoS communications. Moreover, the accuracy of the proposed simplified model is superior to that of the existing simplified model for all kinds of transceiver FoV angles. © 1983-2012 IEEE.

关键词： Radio transceivers

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