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Enhanced Emotion Recognition Using a Hybrid Autoencoder-LSTM Model Optimized with a Hybrid ACO-WOA Algorithm for Hyperparameter Tuning

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International Journal of Advanced computer science and Applications 2025年第4期16卷 861-876页

作者： Waiker, Vinod Ramesh, Janjhyam Venkata Naga Bala, Ms Kiran Krishnaiah, V.V. Jaya Rama Jackulin, T. Muniyandy, Elangovan Shahin, Osama R. Datta Meghe Institute of Management Studies Maharashtra Nagpur India Department of CSE Graphic Era Hill University Dehradun248002 India Department of CSE Graphic Era Deemed To Be University Uttarakhand Dehradun248002 India Department of Computer Science College of Engineering and Computer Science Jazan University Jazan Saudi Arabia Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram India Department of CSE Panimalar Engineering College Tamil Nadu Chennai India Department of Biosciences-Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai602 105 India Applied Science Research Center Applied Science Private University Amman Jordan Department of Computer Science College of Computer and Information Sciences Jouf University Saudi Arabia Physics and Mathematics Department Faculty of Engineering Helwan University Helwan Egypt

Emotion recognition is vital in the human computer interaction because it improves interaction. Therefore, this paper proposes an improved method for emotion recognition regarding the Hybrid Autoencoder-Long Short-Term Memory (LSTM) model and the newly developed hybrid approach of the Ant Colony Optimization (ACO) and Whale Optimization Algorithm (WOA) for hyperparameters tuning. In this case, Autoencoder can reduce input data dimensionality for input data and find the features relevant for the model’s work. In addition, LSTM is able to work with temporal structures of sequential inputs like speech and videos. The contribution of this research lies in the novel combination method of ACO-WOA which aims at tweaking hyperparameters of Autoencoder-LSTM model. Global aspect of ACO and WOA thereby improve the search efficiency and the accuracy of the proposed emotion recognition system and its generalization capacity. In context with the benchmark dataset for the experimentations of emotion recognition, it has established the efficiency of the proposed model in terms of the conventional methods. Recall rates in recognitive intended various emotions and different modalities were also higher in the hybrid Autoencoder-LSTM model. The optimization algorithms like the ACO-WOA also supported in reducing the computational cost which arose due to hyperparameters tuning. The implementation of this paper is done through Python Software. This implementation shows a high accuracy of 94.12% and 95.94% for audio datasets and image datasets respectively when compared with other deep learning models of Conv LSTM and VGG16. Therefore, the research shows that the presented hybrid approach can be a useful solution for successfully employing emotion recognition for enhancing the creation of the empathetic AI systems and for improving user interactions within various fields including healthcare, entertainment, and customer support. © (2025), (science and Information Organization). All rights

关键词： Ant colony optimization

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Microsphere-assisted super-resolution polarized light microscopy for polarization-sensitive materials

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Optics Letters 2025年第3期50卷 908-911页

作者： Ye, Ran Zhang, Xiangyu Zhi, Lingjie Cao, Yurong Melinte, Sorin Wang, Zengbo Yang, Songlin School of Computer and Electronic Information Nanjing Normal University Nanjing210046 China Institute of Information and Communication Technologies Electronics and Applied Mathematics Université Catholique de Louvain Louvain-la-Neuve1348 Belgium School of Computer Science and Engineering Bangor University BangorLL57 1UT United Kingdom

Polarization sensitivity is a fundamental phenomenon observed in nature, and its application is vital for advancing scientific discoveries. Here, we present a microsphere-assisted polarized light microscopy method that enables high-quality, label-free super-resolution imaging of polarization-sensitive materials. We investigated the imaging performance of this method using various samples, including colloidal crystals and grating structures. Both simulations and experiments were performed to explore the underlying physical mechanisms driving the enhancement in imaging quality. The results of this work have potential values for the fields of polarized light microscopy and super-resolution imaging. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Microspheres

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Modulation of blood pressure by dietary potassium and sodium: sex differences and modeling analysis

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American Journal of Physiology - Renal Physiology 2025年第3期328卷 F406-F417页

作者： Stadt, Melissa Layton, Anita T. Department of Applied Mathematics University of Waterloo Waterloo ON Canada Department of Biology University of Waterloo Waterloo ON Canada Cheriton School of Computer Science University of Waterloo Waterloo ON Canada School of Pharmacy University of Waterloo Waterloo ON Canada

High Naþ intake has been linked to elevations in blood pressure, whereas Kþ has the opposite effect. The underlying mechanisms involve complex interactions among renal function, fluid volume, fluid-regulator... 详细信息

High Na^þ intake has been linked to elevations in blood pressure, whereas K^þ has the opposite effect. The underlying mechanisms involve complex interactions among renal function, fluid volume, fluid-regulatory hormones, vasculature, cardiac function, and the autonomic nervous system. These mechanisms are likely modulated by sex, given the known sex differences in blood pressure regulation and the higher prevalence of hypertension in men. The source of these observed sex differences may be traced to organ and tissue levels, given that kidney function, intrarenal renin-angiotensin system components, renal sympathetic nervous activity, and nitric oxide bioavailability all exhibit sex differences. To assess the functional impact of each of these sex differences, we developed sex-specific computational models to simulate whole-body Na^þ, K^þ, and fluid homeostasis, and the effects on blood pressure. The models describe the interactions among the renal system, cardiovascular system, gastrointestinal system, renal sympathetic nervous system, and renin-angiotensin-aldosterone system. Model simulations suggest that women’s attenuated blood pressure response to hypertensive stimuli, including high Na^þ intake, may be largely attributable to the female renal transporter abundance pattern. In addition, we investigated the causal link between high K^þ intake and blood pressure reduction. The models simulate renal response to high K^þ intake, including the immediate gastrointestinal feedforward signals to the kidneys to increase K^þ excretion, and the longer-term response to decrease proximal fractional Na^þ reabsorption and distal K^þ reabsorption. With these assumptions, simulations of high K^þ intake yielded kaliuresis, natriuresis, and a substantial reduction in blood pressure, even when combined with high Na^þ intake. Copyright © 2025 the American Physiolo

关键词： blood pressure potassium handling sex differences sodium handling

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Yang-Lee zeros for real-space condensation

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Physical Review E 2025年第1期111卷 L012101-L012101页

作者： Zdzislaw Burda Desmond A. Johnston Mario Kieburg Faculty of Physics and Applied Computer Science AGH University of Krakow al. Mickiewicza 30 30-059 Kraków Poland School of Mathematical and Computer Sciences Heriot-Watt University Riccarton Edinburgh EH14 4AS United Kingdom and Maxwell Institute of Mathematical Sciences Edinburgh United Kingdom School of Mathematics and Statistics University of Melbourne Parkville VIC 3010 Australia Faculty of Physics and Applied Computer Science AGH University of Krakow al. Mickiewicza 30 30-059 Kraków Poland and Faculty of Physics Bielefeld University P.O. Box 100131 D-33501 Bielefeld Germany

Using the electrostatic analogy, we derive an exact formula for the limiting Yang-Lee zero distribution in the random allocation model of general weights. This exhibits a real-space condensation phase transition, which is induced by a pressure change. The exact solution allows one to read off the scaling of the density of zeros at the critical point and the angle at which the locus of zeros hits the critical point. Since the order of the phase transition and critical exponents can be tuned with a single parameter for several families of weights, the model provides a useful testing ground for verifying various relations between the distribution of zeros and the critical behavior, as well as for exploring the behavior of physical quantities in the mesoscopic regime, i.e., systems of large but finite size. The main result is that asymptotically the Yang-Lee zeros are images of a conformal mapping, given by the generating function for the weights, of uniformly distributed complex phases.

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Sampling List Packings 16

Sampling List Packings

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16th Innovations in Theoretical computer science Conference, ITCS 2025

作者： Camrud, Evan Davies, Ewan Karduna, Alex Lee, Holden Department of Mathematics and Statistics Middlebury College VT United States Department of Computer Science Colorado State University Fort CollinsCO United States Department of Applied Mathematics and Statistics Johns Hopkins University BaltimoreMD United States

ISBN: (纸本)9783959773614

We initiate the study of approximately counting the number of list packings of a graph. The analogous problem for usual vertex coloring and list coloring has attracted substantial attention. For list packing the setup is similar, but we seek a full decomposition of the lists of colors into pairwise-disjoint proper list colorings. The existence of a list packing implies the existence of a list coloring, but the converse is false. Recent works on list packing have focused on existence or extremal results of on the number of list packings, but here we turn to the algorithmic aspects of counting and sampling. In graphs of maximum degree ∆ and when the number of colors is at least Ω(∆2), we give a fully polynomial-time randomized approximation scheme (FPRAS) based on rapid mixing of a natural Markov chain (the Glauber dynamics) which we analyze with the path coupling technique. Some motivation for our work is the investigation of an atypical spin system, one where the number of spins for each vertex is much larger than the graph degree. © Evan Camrud, Ewan Davies, Alex Karduna, and Holden Lee.

关键词： Markov chains

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GPSOM: group-based particle swarm optimization with multiple strategies for engineering applications

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Journal of Big Data 2025年第1期12卷 1-40页

作者： Yan, Jialing Hu, Gang Jia, Heming Hussien, Abdelazim G. Abualigah, Laith Department of Applied Mathematics Xi’an University of Technology Xi’an710054 China School of Computer Science and Engineering Xi’an University of Technology Xi’an710048 China School of Information Engineering Sanming University Sanming365004 China Department of Computer and Information Science Linköping University Linköping58183 Sweden Faculty of Science Fayoum University Faiyum63514 Egypt Computer Science Department Al al-Bayt University Mafraq25113 Jordan

Particle Swarm Optimization (PSO) is a classic optimization algorithm;however, it has issues when solving high-dimensional complex optimization problems, such as sensitivity to initial parameters, insufficient population diversity, and susceptibility to becoming stuck in local optima. To this end, we propose a particle swarm optimization algorithm with multiple swarm strategies (GPSOM) that significantly improves the algorithm’s optimization performance by designing grouping and diversification strategies for the population. GPSOM divides the population into three subgroups and adopts targeted strategies based on different phases: sub-swarm 1 focuses on exploration and improves population diversity and local search ability by dynamically adjusting operators;sub-swarm 2 focuses on exploitation, introducing sine cosine factors and adaptive mechanisms to traverse the solution space efficiently;sub-swarm 3 achieves global and local balance, generating high-quality solutions through adaptive factors and position adjustment operators. The experimental results show that GPSOM performs significantly better than traditional algorithms on the Combinatorial Evolutionary Computing (CEC) 2020 benchmark test set (hereinafter referred to as 20TS), and its reliability and efficiency have been demonstrated in practical applications, such as 15 engineering examples, vehicle cruise control, and robot path optimization. GPSOM is an efficient, stable, practical optimization algorithm that effectively solves high-dimensional complex optimization problems. © The Author(s) 2025.

关键词： Particle swarm optimization (PSO)

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Data-Driven Bandwidth Selection in Kernel Density Estimation via Unsupervised Learning 8th

Data-Driven Bandwidth Selection in Kernel Density Estimatio...

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8th International Symposium on Modelling and Implementation of Complex Systems, MISC 2024

作者： Guidoum, Arsalane Chouaib Henider, Amel Department of Mathematics and Computer Science Faculty of Sciences and Technology University of Tamanghasset Tamanghasset11000 Algeria Department of Finance and Actuarial National Higher School of Statistics and Applied Economics Kolea42003 Algeria

ISBN: (纸本)9783031821110

The selection of optimal bandwidth bw in Kernel Density Estimation (KDE) is crucial for accurate density estimation. Traditional methods, such as unbiased and biased cross-validation and their variants, often suffer from performance and computational limitations. This study presents a novel, data-driven approach to bandwidth selection using unsupervised machine learning techniques. Synthetic samples are generated from the original data, a comprehensive set of statistical parameters is calculated, and bandwidth is estimated using a rule-of-thumb [2]. Feature importance is assessed through random forests (RF) to identify the most influential factors in bandwidth selection. Various unsupervised learning models are then applied to predict the optimal bandwidth for the original sample bwos. The results demonstrate that this machine learning-based approach achieves superior accuracy and computational efficiency compared to traditional cross-validation methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Adversarial machine learning

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Deformation of the Heisenberg–Weyl algebra and the Lie superalgebra : exact solution for the quantum harmonic oscillator with a position-dependent mass

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The European Physical Journal Plus 2025年第4期140卷 1-13页

作者： Jafarov, E. I. Nagiyev, S. M. Van der Jeugt, J. Institute of Physics Ministry of Science and Education Baku Azerbaijan Department of Applied Mathematics Computer Science and Statistics Ghent University Gent Belgium

We propose a new deformation of the quantum harmonic oscillator Heisenberg–Weyl algebra with a parameter $$a>-1$$ . This parameter is introduced through the replacement of the homogeneous mass $$m_0$$ in the definition of the momentum operator $$\hat{p}_x$$ as well as in the creation–annihilation operators $${\hat{a}}^\pm$$ with a mass varying with position x. The realization of such a deformation is shown through the exact solution of the corresponding Schrödinger equation for the non-relativistic quantum harmonic oscillator within the canonical approach. The obtained analytical expression of the energy spectrum consists of an infinite number of equidistant levels, whereas the wavefunctions of the stationary states of the problem under construction are expressed through the Hermite polynomials. Then, the Heisenberg–Weyl algebra deformation is generalized to the case of the Lie superalgebra $$\mathfrak {osp}\left( {1|2} \right)$$ . It is shown that the realization of such a generalized superalgebra can be performed for the parabose quantum harmonic oscillator problem, the mass of which possesses a behavior completely overlapping with the position-dependent mass of the canonically deformed harmonic oscillator problem. This problem is solved exactly for both even and odd stationary states. It is shown that the energy spectrum of the deformed parabose oscillator is still equidistant; however, both even- and odd-state wavefunctions are now expressed through the Laguerre polynomials. Some basic limit relations recovering the canonical harmonic oscillator with constant mass are also discussed briefly.

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Inter-Stream Dependencies in Time-Sensitive Networking 28

Inter-Stream Dependencies in Time-Sensitive Networking

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28th Conference on Innovation in Clouds, Internet and Networks, ICIN 2025

作者： Chahed, Hamza Yarvis, Mark Frick, Florian Kassler, Andreas Intel Deutschland GmbH Germany Intel Corporation United States Department of Mathematics and Computer Science Karlstad University Karlstad Sweden Institute for Control Technology of Machine Tools and Manufacturing Equipment University of Stuttgart Germany Faculty of Applied Computer Science Deggendorf Institute of Technology Deggendorf Germany

ISBN: (纸本)9798331542399

Effective configuration of Time-Sensitive Networks is crucial for providing timeliness and reliability guarantees for real-time industrial applications, where many inter-dependent streams may co-exist. However, existing methods for specifying the characteristics of real-time streams to the Centralized Network Configuration element (CNC) do not allow the specification of stream dependencies. Consequently, the CNC may schedule the real-time streams in a sub-optimal way, leading to low number of real-time applications supported. To address this pressing issue, we present methods that allow to model and express such inter-stream dependencies and propose extensions to the user network interface (UNI) to convey these dependencies to the CNC, transforming it into an intent-based UNI. We define a novel metric to evaluate a specific network configuration regarding the latency budget available for scheduling the transmission of a stream. Using a set of numerical simulations, we show that when exploiting the knowledge of inter-stream dependencies, we can derive better network schedules, which results in significant increase in applications onboarding up to 2.2x and increased network utilization for real-time streams up to 3x. © 2025 IEEE.

关键词： Budget control

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Latent Representation Learning for Multimodal Brain Activity Translation

Latent Representation Learning for Multimodal Brain Activity...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Afrasiyabi, Arman Bhaskar, Dhananjay Busch, Erica L. Caplette, Laurent Singh, Rahul Lajoie, Guillaume Turk-Browne, Nicholas B. Krishnaswamy, Smita Department of Computer Science Department of Applied Mathematics Department of Psychology Department of Genetics Department of Mathematics and Statistics Mila - Quebec AI Institute Canada Université de Montréal Canada Wu Tsai Institute United States Yale University United States

ISBN: (纸本)9798350368741

Neuroscience employs diverse neuroimaging techniques, each offering distinct insights into brain activity, from electrophysiological recordings such as EEG, which have high temporal resolution, to hemodynamic modalities such as fMRI, which have increased spatial precision. However, integrating these heterogeneous data sources remains a challenge, which limits a comprehensive understanding of brain function. We present the Spatiotemporal Alignment of Multimodal Brain Activity (SAMBA) framework, which bridges the spatial and temporal resolution gaps across modalities by learning a unified latent space free of modality-specific biases. SAMBA introduces a novel attention-based wavelet decomposition for spectral filtering of electrophysiological recordings, graph attention networks to model functional connectivity between functional brain units, and recurrent layers to capture temporal autocorrelations in brain signal. We show that the training of SAMBA, aside from achieving translation, also learns a rich representation of brain information processing. We showcase this classify external stimuli driving brain activity from the representation learned in hidden layers of SAMBA, paving the way for broad downstream applications in neuroscience research and clinical contexts. © 2025 IEEE.

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