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Sentiment Analysis and Deep Learning (ICSADL), International Conference on

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

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

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.

关键词： Training Emotion recognition Accuracy computational modeling Speech recognition Speech enhancement Predictive models Feature extraction Data models Convolutional neural networks

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Multi-Agent Systems for Autonomous IoT Network Management Using Distributed Reinforcement Learning

Multi-Agent Systems for Autonomous IoT Network Management Us...

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International Symposium on Advanced computing and Communication (ISACC)

作者： Neelamegam G Rajaram Venkatesan Ramya SR R.S. Ramya Akshya. J M. Sundarrajan Mani Deepak Choudhry Department of Computer Science and Engineering VSB College of Engineering and Technology Coimbatore Tamil Nadu India Department of Artificial Intelligence and Data Science Builders Engineering College Tirupur Tamil Nadu India Department of Computer Science and Engineering Dr NGP Institute of Technology Coimbatore Tamil Nadu India Department of Computer Science and Engineering Sri Ramakrishna Engineering College Coimbatore Tamil Nadu India Department of Computational Intelligence SRM Institute of Science and Technology Chennai Tamil Nadu India Department of Networking and Communications SRM Institute of Science and Technology Chennai Tamil Nadu India Department of Computing Technologies SRM Institute of Science and Technology Chennai Tamil Nadu India

ISBN: (数字)9798331523893

ISBN: (纸本)9798331523909

The ever-growing complexity of IoT networks ignited by their wide scale adoption in applications such as smart cities, the industrial automation, and health care, compelled to develop sophisticated yet resource efficient and scalable network management solution. Centralized systems are traditional in architecture, which leads to higher latency and bottlenecks, while decentralized systems can distribute workloads however the lack of adaptability to real time, along with the difficulty of extracting maximum resource usage, are limitations. In recent years, reinforcement learning (RL) based approaches have taken shape as a promising alternative to facilitate the automated learning and optimisation of task management. However, there are two challenges for existing RL based methods: slow convergence, inefficient priority assignment of tasks, and poor coordination amongst agents in the case of dynamic, large scale IoT environment. To solve these challenges, in this research we propose a distributed reinforcement learning based multi agent framework for managing IoT network. The framework also integrates a task prioritization mechanism to dynamically choose an optimal task allocation solution. Further validation was performed in a simulated IoT environment where real world inspired datasets were used. The proposed framework demonstrated 30% more task throughput than centralized, 25% less latency than decentralized, and 40% more energy efficiency than current RL based systems. The system was further validated using advanced visualizations such as anomaly detection maps and resource allocation efficiency graphs, demonstrating its capacity to manage dynamic load of tasks and resource allocation. The proposed framework addresses the critical limitations of current methods, through scalable, adaptive, and energy efficient framework for managing IoT network, and accordingly helps advancing the intelligent and autonomous IoT systems.

关键词： Smart cities Reinforcement learning Medical services Throughput Dynamic scheduling Energy efficiency Real-time systems Resource management Optimization Multi-agent systems

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Autoregressive Diffusion Networks for Trustworthy Node Identification and Optimized Routing in Wireless Sensor Networks

Autoregressive Diffusion Networks for Trustworthy Node Ident...

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Advancement in Computation & Computer Technologies (InCACCT), International Conference on

作者： M. Satheesh Kumar P. Ganesh Kumar S. Amudha T. Kavitha P. Ravikumar M. Raghini Department of CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of IT K.L.N. College of Engineering Department of Computational Intelligence School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electronics and Instrumentation K.L.N. College of Engineering Department of Artificial Intelligence and Data Science Velammal College of Engineering and Technology

ISBN: (数字)9798331543891

ISBN: (纸本)9798331543907

Finding and eliminating unwanted nodes is a foremost challenge in wireless sensor networks (WSNs). This paper proposes an Autoregressive Diffusion Network (ADN) to find and categorize the nodes in the network as affected or trustworthy. Here, the proposed ADN provides a strong foundation for finding uncommon or insecure actions by effectively recording the characteristics of the sensor over a period of time. Thus, using the capability to capture successive data. In addition, an improved routing mechanism is developed using the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocols. Then, the Pelican Optimisation Algorithm (POA) is used to optimize the cluster heads optimally. To further improve the routing mechanism using fitness proportional selection technique to transfer the data safely and effectively. Simulation results show that the proposed technique enhances the performance by reducing energy consumption and increasing the detection accuracy of affected nodes. The proposed LEACH + POA + ADN model shows the improved detection accuracy of 77%, false positive rate of 7.50%, average energy consumption of 8.02 J, network lifetime of 92.94 rounds, and packet delivery ratio of 92.97%, which is high compared to other benchmark models.

关键词： Wireless sensor networks Energy consumption Accuracy Protocols Simulation Clustering algorithms Routing Energy efficiency Security Reliability

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Secure Encryption of Satellite Images Using S-Box-Based Two-Fish Algorithm and A Novel Chaotic Map 3rd

Secure Encryption of Satellite Images Using S-Box-Based Two-...

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3rd International Conference on Signal and Data Processing, ICSDP 2023

作者： Jansi, R. Ashwini, K. Aishwarya, N. Muthulakshmi, M. Logeshwari, M. Kanna, Mukesh Department of Electronics and Communication Engineering Faculty of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur603203 India Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India Department of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Chennai India Department of Mathematics Sathyabama Institute of Science and Technology Semmancheri Tamil Nadu Chennai600119 India

ISBN: (纸本)9789819795772

In recent days, encryption of satellite imagery has attracted a wide range of researchers since these images contain confidential information. Thereby, it is necessary to preserve the privacy of this data to avoid unauthorized access. Two-fish algorithm is one of the widely used image encryption schemes. However, the main drawback of this scheme lies with the static nature of the S-box. To avoid this issue and to improve the quality of encryption, in this paper, we propose a novel algorithm based on chaotic map to create a dynamic S-box structure. In the proposed Chaotic S-Box-based Two-Fish (CSTF) algorithm, a novel chaotic map with improved Lyapunov exponent and approximate entropy has been proposed. The sequences produced by the proposed chaotic map are used to randomize the values inside the static S-box structure of Two-fish algorithm. This encryption scheme is suitable for the encryption of satellite images. The proposed algorithm is validated in terms of S-box evaluation metrics like nonlinearity, bit independence criteria-nonlinearity (BIC-nonlinearity), strict Avalanche criterion (SAC) and bit independence criteria-strict Avalanche criterion (BIC-SAC). To validate the proposed algorithm in terms of key sensitivity, tests like Unified Average Changing Intensity (UACI), Hamming Distance (HD) and Number of Pixels Change Rate (NPCR) have been performed. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Lyapunov functions

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Enabling All-to-Circular Polarization Up-Conversion by Nonlinear Chiral Metasurfaces with Rotational Symmetry

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Physical Review Letters 2025年第2期134卷 023804-023804页

作者： Dmitrii Gromyko Jun Siang Loh Jiangang Feng Cheng-Wei Qiu Lin Wu Science Mathematics and Technology (SMT) Singapore University of Technology and Design (SUTD) 8 Somapah Road 487372 Singapore Singapore Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 117583 Singapore Singapore Institute of High Performance Computing ASTAR (Agency for Science Technology and Research) 1 Fusionopolis Way No. 16-16 Connexis 138632 Singapore Singapore

We introduce a stacking strategy to design nonlinear chiral metasurfaces with high rotational symmetry, enabling degenerate quasi-bound-in-the-continuum resonances of absolute chirality. This symmetry allows for converting a circularly polarized pump into a circularly polarized nonlinear signal. Consequently, our rotation-symmetric bilayered metasurface design, tailored to respond solely to one specific circular polarization, can up-convert a linear or arbitrary polarized pump into circularly polarized nonlinear signals. The intensity ratios of these signals scale as the fourth (second) power of the chiral resonance amplitude for the second (third) harmonic.

关键词： Circular polarization

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Reverse time migration for reconstructing extended obstacles in planar acoustic waveguides

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science China mathematics 2015年第9期58卷 1811-1834页

作者： CHEN ZhiMing HUANG GuangHui LSEC Institute of Computational Mathematics and Scientific Engineering ComputingAcademy of Mathematics and Systems Science Chinese Academy of Sciences

We propose a new reverse time migration method for reconstructing extended obstacles in the planar waveguide using acoustic waves at a fixed frequency. We prove the resolution of the reconstruction method in terms of the aperture and the thickness of the waveguide. The resolution analysis implies that the imaginary part of the cross-correlation imaging function is always positive and thus may have better stability *** experiments are included to illustrate the powerful imaging quality and to confirm our resolution results.

关键词： reverse time migration planar waveguide resolution analysis extended obstacle

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Existence theory for Rosseland equation and its homogenized equation

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Applied mathematics and Mechanics(English Edition) 2012年第12期33卷 1595-1612页

作者：张乔夫崔俊芝 State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering ComputingAcademy of Mathematics and Systems ScienceChinese Academy of Sciences

The global boundness and existence are presented for the kind of the Rosseland equation with a general growth condition. A linearized map in a closed convex set is defined. The image set is precompact, and thus a fixed point exists. A multi-scale expansion method is used to obtain the homogenized equation. This equation satisfies a similar growth condition.

关键词： nonlinear elliptic equations fixed points mixed boundary conditions growthconditions maximal regularitys homogenized equation

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Analysis on a Superlinearly Convergent Augmented Lagrangian Method

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Acta Mathematica Sinica,English Series 2014年第1期30卷 1-10页

作者： Ya Xiang YUAN State Key Laboratory of Scientific/Engineering Computing Institute of Computational Mathematics and Scientific/Engineering ComputingAcademy of Mathematics and Systems ScienceChinese Academy of Sciences

The augmented Lagrangian method is a classical method for solving constrained ***,the augmented Lagrangian method attracts much attention due to its applications to sparse optimization in compressive sensing and low rank matrix optimization ***,most Lagrangian methods use first order information to update the Lagrange multipliers,which lead to only linear *** this paper,we study an update technique based on second order information and prove that superlinear convergence can be *** properties of the update formula are given and some implementation issues regarding the new update are also discussed.

关键词： Nonlinearly constrained optimization augmented Lagrange function Lagrange multiplier convergence

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Detection and Cancellation of Multiplicative FDI Attack on Bilateral Encrypted Control System in Variable Periodic Motion

Detection and Cancellation of Multiplicative FDI Attack on B...

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IEEE/SICE International Symposium on System Integration

作者： Katsumasa Kosha Tetsuro Miyazaki Kaoru Teranishi Kiminao Kogiso Kenji Kawashima Department of Information Physics and Computing The University of Tokyo Tokyo Japan Oden Institute for Computational Engineering and Sciences The University of Texas at Austin Austin Texas USA Japan Society for the Promotion of Science Tokyo Japan Department of Mechanical and Intelligent Systems Engineering The University of Electro-Communications Tokyo Japan

ISBN: (数字)9798331531614

ISBN: (纸本)9798331531621

Teleoperation of remote assist robots has recently advanced owing to the development of communication technology. However, anonymous malicious attacks may intercept or falsify the network control system. Therefore, it is necessary to improve the security against cyber-attacks. As a countermeasure, an encrypted control method has been applied to prevent intercepting and detect the falsification of control parameters, as well as control signals by performing control operations with encrypted signals and parameters. Furthermore, we have proposed the algorithm to detect and restore the attack exploiting a vulnerability of encryption, which falsifies the plaintext by multiplying a constant factor. However, the algorithm is only effective for periodic motions with a fixed operating frequency and amplitude. If the frequency or amplitude of the motion is smaller than those of the base motion, the algorithm cannot detect the attack. To solve the problem, we propose an improved algorithm to detect and restore the attack in periodic motion with variable operating frequency and amplitude. In the proposed method, the operating frequency and amplitude are obtained through the position frequency analysis. They contribute to update the base energy, which is the average energy of corresponding periodic motion. We verified the proposed method for the bilateral control system using ElGamal encryption and experimentally confirmed its effectiveness against the FDI attack in various periodic motion.

关键词： Networked control systems System integration Cyber-physical systems Approximation algorithms Polynomials Encryption Usability Robots Frequency control Cyberattack

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Observation of the interaction between Au− and CO2 in Au(CO2)n− anions: Physisorption as the dominant mechanism

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Journal of Chemical Physics 2025年第17期162卷 174310页

作者： Guo, Zonghui Du, Shihu Huang, Wei Zhao, Wenbao Han, Haiyan Zhao, Zhi Yan, Yongliang Fan, Zhihui Shi, Ruili Xie, Hua Jiang, Ling School of Mathematics and Physics Science and Engineering Hebei Computational Optical Imaging and Photoelectric Detection Technology Innovation Center Hebei International Joint Research Center for Computational Optical Imaging and Intelligent Sensing Hebei University of Engineering Handan056038 China School of Chemistry and Chemical Engineering Shandong University Jinan250100 China State Key Laboratory of Molecular Reaction Dynamics Dalian Institute of Chemical Physics Chinese Academy of Sciences Dalian116023 China

In this study, we investigated the structure and bonding of Au(CO2)n− (n = 2, 3) using photoelectron spectroscopy analysis, quantum chemical calculations, and weak interaction analysis. Quantum chemical calculations revealed that the geometries of the physisorbed structures closely aligned with experimental data, suggesting that these configurations were the most stable under the experimental conditions. Conversely, while chemisorbed structures exhibit stronger interactions and considerable CO2 activation, they show less agreement with the observed spectroscopic data. Using the interaction region indicator method, our weak interaction analysis confirmed that van der Waals forces were the dominant interaction in the physisorbed structures. Our experimental results indicate that these physically adsorbed structures are more stable under the conditions of this study. These findings shed light on the interaction mechanisms of Au(CO2)n− (n = 2, 3) at the molecular level and provide new insights into the potential for transition metals to catalytically activate CO2 © 2025 Author(s).

关键词： Van der Waals forces

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