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Improving ECAPA-TDNN Performance with Coordinate Attention

Journal of Shanghai Jiaotong University (science) 2024年 1-7页

作者： Liu, Shuanghong Song, Zhida He, Liang School of Computer Science and Technology Xinjiang University Urumqi830017 China Xinjiang Key Laboratory of Signal Detection and Processing Urumqi830017 China Department of Electronic Engineering and Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China

The current mainstream networks, such as squeeze and excitation residual neural network (SE-ResNet) and emphasized channel attention, propagation and aggregation based time delay neural network (ECAPA-TDNN), enhance the capability of speaker embedding extractors to extract more discriminative speaker embeddings by incorporating squeeze and excitation (SE) attention within the convolutional blocks. However, the SE attention focuses solely on encoding inter-channel information, overlooking the importance of spatial positional information and time-frequency information, which are crucial for the model’s performance. In this paper, we first experimentally compare the effectiveness of several mainstream attention mechanisms in the computer vision domain for the ECAPA-TDNN model. Next, we focus on the substantial improvements that coordinate attention (CA) brings to the ECAPA-TDNN model. The introduction of CA can help the model embed time-frequency information into the channel representation. Even without using AS-Norm, our proposed model achieves relative reductions of about 5.3% equal error rate (EER) and 5.5% minimum detection cost function (minDCF) on both the Voxceleb-O and Voxceleb-H test sets compared to the ECAPA-TDNN baseline model. In addition, the EER is relatively reduced by 9.46% on the CN-Celeb1 test set. This result strongly demonstrates that the CA module can effectively improve the generalization ability of the ECAPA-TDNN model. © Shanghai Jiao Tong University 2024.

关键词： Neural network models

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Synergistic Swarm Optimization Algorithm

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computer Modeling in engineering & sciences 2024年第6期139卷 2557-2604页

作者： Sharaf Alzoubi Laith Abualigah Mohamed Sharaf Mohammad Sh.Daoud Nima Khodadadi Heming Jia Faculty of Computer Sciences and Informatics Amman Arab UniversityAmman11953Jordan Computer Science Department Al Al-Bayt UniversityMafraq25113Jordan Department of Electrical and Computer Engineering Lebanese American UniversityByblos13-5053Lebanon Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan MEU Research Unit Middle East UniversityAmman11831Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan School of Computer Sciences Universiti Sains MalaysiaPulau Pinang11800Malaysia School of Engineering and Technology Sunway University MalaysiaPetaling Jaya27500Malaysia Department of Industrial Engineering College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia College of Engineering Al Ain UniversityAbu Dhabi112612United Arab Emirates Department of Civil and Architectural Engineering University of MiamiCoral Gables1251USA School of Information Engineering Sanming UniversitySanming365004China

This research paper presents a novel optimization method called the Synergistic Swarm Optimization Algorithm(SSOA).The SSOA combines the principles of swarmintelligence and synergistic cooperation to search for optimal solutions efficiently.A synergistic cooperation mechanism is employed,where particles exchange information and learn from each other to improve their search *** cooperation enhances the exploitation of promising regions in the search space while maintaining exploration ***,adaptive mechanisms,such as dynamic parameter adjustment and diversification strategies,are incorporated to balance exploration and *** leveraging the collaborative nature of swarm intelligence and integrating synergistic cooperation,the SSOAmethod aims to achieve superior convergence speed and solution quality performance compared to other optimization *** effectiveness of the proposed SSOA is investigated in solving the 23 benchmark functions and various engineering design *** experimental results highlight the effectiveness and potential of the SSOA method in addressing challenging optimization problems,making it a promising tool for a wide range of applications in engineering and *** codes of SSOA are available at:https://***/matlabcentral/fileexchange/153466-synergistic-swarm-optimization-algorithm.

关键词： Synergistic swarm optimization algorithm optimization algorithm metaheuristic engineering problems benchmark functions

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"Fiction to Function"Shaping Renewable Energy Education with MATLAB and ChatGPT-Driven Environments 21

"Fiction to Function"Shaping Renewable Energy Education with...

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21st International Learning and Technology Conference, L and T 2024

作者： Mohamed, Baher Babiker, Safia Aldybous, Alaa Kabbaj, Narjisse Brahimi, Tayeb Effat University Effat College of Engineering Electrical and Computer Engineering Department Jeddah Saudi Arabia Effat University Effat College of Engineering Energy and Technology Research Center Electrical and Computer Engineering Department Jeddah Saudi Arabia Effat University Natural Science Math and Tech Unit Effat College of Engineering Energy and Technology Research Center Jeddah Saudi Arabia

ISBN: (纸本)9798350393569

Addressing the gap in effective and engaging renewable energy education, this study, 'Fiction to Function,' transitions imaginative frameworks into practical educational tools, focusing on solar and wind energy in line with Sustainable Development Goals (SDGs). The goal is to empower users with deep insights into renewable energy through the novel integration of MATLAB and ChatGPT-driven environments, enhancing the analysis and exploration of these energy sources. The study employs a structured approach using MATLAB App Designer to develop a user-friendly GUI, aligning instructional content with the SDGs and integrating ChatGPT via the OpenAI API for dynamic, interactive learning experiences. This integration provides a multifaceted platform that not only educates but also engages users in practical scenarios, bridging the gap between theoretical knowledge and real-world application. The results demonstrate an enhanced understanding of renewable energy concepts among users, showcasing the efficacy of combining MATLAB's analytical capabilities with ChatGPT's AI-driven guidance. Ultimately, the study highlights the transformative potential of innovative technology in sustainable energy education, setting a precedent for future educational tools in this domain. © 2024 IEEE.

关键词： Integration

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Isolation Enhancement in a Compact Four-Element MIMO Antenna for Ultra-Wideband Applications

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computers, Materials & Continua 2023年第4期75卷 911-925页

作者： Awais Khan Shahid Bashir Salman Ghafoor Hatem Rmili Jawad Mirza Ammar Ahmad Department of Electrical Engineering University of Engineering and TechnologyPeshawar25000Pakistan Department of Electrical Engineering University of Science and TechnologyBannu28100Pakistan School of Electrical Engineering and Computer Science(SEECS) National University of Sciences and Technology(NUST)Islamabad44000Pakistan Electrical and Computer Engineering Department Faculty of EngineeringKing Abdulaziz UniversityJeddahSaudi Arabia K.A.CARE Energy Research and Innovation Center King Abdulaziz UniversityJeddah21589Saudi Arabia SEECS Photonic Research Group National University of Sciences and TechnologyIslamabad44000Pakistan

Mutual coupling reduction or isolation enhancement in antenna arrays is an important area of research as it severely affects the performance of an *** this paper,a new type of compact and highly isolated Multiple-Input-Multiple-Output(MIMO)antenna for ultra-wideband(UWB)applications is *** design consists of four radiators that are orthogonally positioned and confined to a compact 40×40×0.8 mm3 *** final antenna design uses an inverted L shape partial ground to produce an acceptable reflection coefficient(S11<−10 dB)in an entire UWB band(3.1–10.6)giga hertz(GHz).Moreover,the inter-element isolation has also been enhanced to>20 db for majority of the UWB *** antenna was fabricated and tested with the vector network analyzer(VNA)and in an anechoic chamber for scattering parameters and radiation ***,different MIMO diversity performance metrics are also measured to validate the proposed *** simulation results and the experimental results from the constructed model agree quite *** proposed antenna is compared with similar designs in recently published literature for various performance *** of its low envelope correlation coefficient(ECC<0.1),high diversity gain(DG>9.99 dB),peak gain of 4.6 dB,reduced channel capacity loss(CCL<0.4 b/s/Hz),and average radiation efficiency of over 85%,the proposed MIMO antenna is ideally suited for practical UWB applications.

关键词： Multiple input multiple output antennas envelope correlation coefficient defected ground structure ultra wide band diversity gain

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Blockchain Based Secured Load Balanced Task Scheduling Approach for Fitness Service

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computers, Materials & Continua 2022年第5期71卷 2599-2616页

作者： Muhammad Ibrahim Faisal Jamil YunJung Lee DoHyeun Kim Big Data Research Center Department of Computer Science and StatisticsJeju National UniversityKoreaJeju-si63243Korea Department of Computer Engineering(and Advanced Technology Research Institute) Jeju National UniversityJeju 63243Korea

In recent times,the evolution of blockchain technology has got huge attention from the research community due to its versatile applications and unique security *** IoT has shown wide adoption in various applications including smart cities,healthcare,trade,business,*** these applications,fitness applications have been widely considered for smart fitness *** users of the fitness system are increasing at a high rate thus the gym providers are constantly extending the fitness ***,scheduling such a huge number of requests for fitness exercise is a big ***,the user fitness data is critical thus securing the user fitness data from unauthorized access is also *** overcome these issues,this work proposed a blockchain-based load-balanced task scheduling approach.A thorough analysis has been performed to investigate the applications of IoT in the fitness industry and various scheduling *** proposed scheduling approach aims to schedule the requests of the fitness users in a load-balanced way that maximize the acceptance rate of the users’requests and improve resource *** performance of the proposed task scheduling approach is compared with the state-of-the-art approaches concerning the average resource utilization and task rejection *** obtained results confirm the efficiency of the proposed scheduling *** investigating the performance of the blockchain,various experiments are performed using the Hyperledger Caliper concerning latency,throughput,resource *** Solo approach has shown an improvement of 32%and 26%in throughput as compared to Raft and Solo-Raft approaches *** obtained results assert that the proposed architecture is applicable for resource-constrained IoT applications and is extensible for different IoT applications.

关键词： Load balancing resource scheduling task scheduling Internet of things blockchain fitness applications

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THE INCLUSION-EXCLUSION PRINCIPLE AND RECURRENCES FOR PARTITION NUMBERS

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2025年第1期87卷 97-106页

作者： Ballantine, Cristina Merca, Mircea Department of Mathematics and Computer Science College of The Holy Cross WorcesterMA01610 United States Department of Mathematical Methods and Models Fundamental Sciences Applied in Engineering Research Center National University of Science and Technology Politehnica Bucharest BucharestRO-060042 Romania Academy of Romanian Scientists BucharestRO-050044 Romania

The inclusion-exclusion principle together with Legendre type theorems for number of distinct restricted partitions weighted by the parity of their length are used to give several recurrence relations for restricted partition numbers as well as for overpartition numbers. In the case of overpartitions, POD partitions and 3-color partitions, we give combinatorial proofs for the Legendre type theorems and arrive to combinatorial proofs for the recurrence relations. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： Combinatorial mathematics

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Deep Learning in Remote Sensing for Climate-Induced Disaster Resilience: A Comprehensive Interdisciplinary Approach

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Remote Sensing in Earth Systems sciences 2024年第1期8卷 145-160页

作者： Padmaja, S.M. Naveenkumar, R. Kumari, N. P. Lavanya Pimo, Er. S. John Bindhu, M. Konduri, Bhagavan Jangir, Pradeep Department of Electrical and Electronics Engineering Shri Vishnu Engineering College for Women Bhimavaram India Department of Computer Science and Engineering Chandigarh Colleges of Engineering Chandigarh Group of Colleges Jhanjeri Punjab Mohali 140307 India Department of Computer Science and Systems Engineering AUCE Andhra University Visakhapatnam India Department of Computer Science and Engineering St. Xavier’s Catholic College of Engineering Nagercoil India Department of ECE Sri Venkateswara College of Engineering Sriperumbudur India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram India Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman 19328 Jordan

Climate-induced disasters pose significant threats to human lives, infrastructure, and ecosystems. Deep learning techniques, combined with remote sensing, offer powerful tools for predicting, detecting, and mitigating the impacts of such disasters. This study presents a comprehensive interdisciplinary approach using a hybrid cascaded CNN-RNN model to perform spatio-temporal analysis, enhanced image segmentation with U-Net and SegNet architectures, and a hybrid CNN-LSTM-XGBoost ensemble for multi-hazard prediction. The proposed CNN-RNN model achieves an accuracy of 96.78%, significantly outperforming traditional models in predicting flood-prone areas, wildfires, and droughts. Key metrics such as Intersection over Union (IoU), precision, recall, and F1-scores are used to evaluate model performance, highlighting the model’s ability to accurately identify disaster-prone areas and improve disaster resilience. This research not only demonstrates the efficacy of deep learning for climate-induced disaster prediction but also paves the way for future integration of socio-economic data to refine disaster risk assessment. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Climate-induced disasters CNN-RNN Deep learning Disaster resilience Hybrid ensemble Multi-hazard prediction Remote sensing SegNet Spatio-temporal analysis U-Net

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HERA: A Novel Heuristic Resource Allocator for Multi-SDM Multi-User Settings

HERA: A Novel Heuristic Resource Allocator for Multi-SDM Mul...

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2024 IEEE Conference on Standards for Communications and Networking, CSCN 2024

作者： Antoniadis, Christos Katsalis, Kostas Tyrovolas, Dimitrios Tegos, Sotiris A. Ioannidis, Sotiris Diamantoulakis, Panagiotis D. Karagiannidis, George K. Liaskos, Christos DOCOMO Euro-Labs Munich Germany Aristotle University of Thessaloniki Department of Electrical and Computer Engineering Thessaloniki54124 Greece Technical University of Crete Dept. of Electrical and Computer Engineering Chania Greece Artificial Intelligence & Cyber Systems Research Center Lebanon University of Ioannina Computer Science Engineering Department Ioannina Greece Institute of Computer Science Foundation for Research and Technology Hellas Greece

ISBN: (纸本)9798331507428

The advent of Programmable Wireless Environments (PWEs) has transformed the wireless propagation phenomenon into a software-defined resource, leveraging Software-defined metasurfaces (SDMs). These new technologies have shown that wireless waves can be routed within a space, contrary to the regular, chaotic wireless propagation, yielding considerable benefits to communication efficiency, and even completely new applications. A new topic has risen, in the context of modeling these capabilities as network resources, and allocating them to users. In this context, the present paper contributes HERA, a heuristic resource allocator that receives a setup with users and SDMs as input, and produces the necessary configuration of the latter, for efficient shared performance. Simulation results demonstrate considerable efficiency in this task, while the heuristic nature of HERA sets the basis for a flexible definition of complex user objectives in the future. © 2024 IEEE.

关键词： Resource allocation

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Gate-Attention and Dual-End Enhancement Mechanism for Multi-Label Text Classification

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computers, Materials & Continua 2023年第11期77卷 1779-1793页

作者： Jieren Cheng Xiaolong Chen Wenghang Xu Shuai Hua Zhu Tang Victor S.Sheng School of Computer Science and Technology Hainan UniversityHaikou570228China Hainan Blockchain Technology Engineering Research Center Hainan UniversityHaikou570228China School of Cyberspace Security Hainan UniversityHaikou570228China Department of Computer Science Texas Tech UniversityLubbock79409USA

In the realm of Multi-Label Text Classification(MLTC),the dual challenges of extracting rich semantic features from text and discerning inter-label relationships have spurred innovative *** studies in semantic feature extraction have turned to external knowledge to augment the model’s grasp of textual content,often overlooking intrinsic textual cues such as label statistical *** contrast,these endogenous insights naturally align with the classification *** our paper,to complement this focus on intrinsic knowledge,we introduce a novel Gate-Attention *** mechanism adeptly integrates statistical features from the text itself into the semantic fabric,enhancing the model’s capacity to understand and represent the ***,to address the intricate task of mining label correlations,we propose a Dual-end enhancement *** mechanism effectively mitigates the challenges of information loss and erroneous transmission inherent in traditional long short term memory *** conducted an extensive battery of experiments on the AAPD and RCV1-2 *** experiments serve the dual purpose of confirming the efficacy of both the Gate-Attention mechanism and the Dual-end enhancement *** final model unequivocally outperforms the baseline model,attesting to its *** findings emphatically underscore the imperativeness of taking into account not just external knowledge but also the inherent intricacies of textual data when crafting potent MLTC models.

关键词： Multi-label text classification feature extraction label distribution information sequence generation

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A Cost-Efficient Anonymous Authenticated and Key Agreement Scheme for V2I-Based Vehicular Ad-Hoc Networks

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IEEE Transactions on Intelligent Transportation Systems 2024年第9期25卷 12621-12630页

作者： Saleem, Muhammad Asad Li, Xiong Mahmood, Khalid Shamshad, Salman Alenazi, Mohammed J. F. Das, Ashok Kumar University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen518000 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan The University of Lahore Department of Software Engineering Lahore54590 Pakistan King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh11451 Saudi Arabia International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500032 India

The rise of smart cities is directly connected to the increasing use of vehicles. The growing vehicle utilization has driven the emergence of Vehicular Ad-hoc Networks (VANETs), facilitating instant information exchange among vehicles. The system provides essential information regarding road conditions, traffic patterns, and more relevant data. VANETs encompass two fundamental categories of communication exchanges, namely Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I). V2I technology facilitates the integration of cars and transportation infrastructure, enabling effective communication between vehicles and infrastructure. Nevertheless, the potential of V2I communication has various security concerns arising from prevalent security threats. Current authentication techniques encounter challenges regarding complexity, security, and privacy considerations. We designed a hash-based lightweight and anonymous authentication scheme to address the aforementioned restrictions and enhance the effectiveness of authentication in V2I architecture. This scheme effectively combines identity, password, and bio-metric to enhance resistance against impersonation, denial of service, and privileged insider attacks. The devised scheme distinguishes itself by a comparative analysis and security proofs, highlighting its superior capability in guaranteeing secure authentication in V2I communication. The comprehensive security analysis conducted formally and informally showcases the robustness of the proposed solution against several threats. The performance evaluation results show that our scheme demonstrates a decrease in the computational cost of 51.40% approximately and a reduction in communication overhead of around 22.57%. These results establish the efficiency and scalability of the proposed scheme as a viable solution for V2I architecture. © 2000-2011 IEEE.

关键词： Vehicular ad hoc networks

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