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Conference of Recent Trends and Applications of Soft Computing in engineering, RTASCE 2024

作者： Doma, Victor Berbić, Erna Almisreb, Ali Abd Hairuddin, Muhammad Asraf Imankulova, Binara Faculty of Computer Science and Engineering International University of Sarajevo Sarajevo Bosnia and Herzegovina College of Engineering Universiti Teknologi MARA Johor Masai Malaysia Universiti Teknologi MARA Shah Alam Malaysia Department of Computer Science Suleyman Demirel University Kaskelen Kazakhstan

ISBN: (纸本)9783031828805

In this work, we investigate the use of Natural Language Processing (NLP) approaches to categorize patient conditions based on drug reviews. We use a dataset from *** to focus on four particular conditions: birth control, depression, high blood pressure, and type 2 diabetes. The approach involves data preprocessing, feature extraction with TF-IDF, and the use of machine learning classifiers like Multinomial Naive Bayes and Passive Aggressive Classifier. Our findings show that natural language processing has the capacity to effectively diagnose medical situations, which can considerably improve patient care, drug effectiveness monitoring, and healthcare research. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Drug therapy

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Bifurcation analysis, phase portrait, and exploring exact traveling wave propagation of M-fractional (3 + 1) dimensional nonlinear equation in the fluid medium

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Optical and Quantum Electronics 2025年第4期57卷 1-23页

作者： Roshid, Md. Mamunur Uddin, Mahtab Abdalla, Mohamed Ullah, Md. Ahsan Department of Mathematics Hamdard University Bangladesh Munshigang Bangladesh Institute of Natural Sciences United International University Dhaka Bangladesh Department of Mathematics Faculty of Science King Khalid University Abha61471 Saudi Arabia Department of Computer Science and Engineering University of Liberal Arts Bangladesh Dhaka Bangladesh

This work studies the bifurcation analysis, phase portrait, and dynamics behavior of exact traveling wave solutions for the time M-fractional (3 + 1)-dimensional Painlevé integrable model. This model is used to describe some complex phenomena in nonlinear science and is crucial for addressing various practical challenges, including key models in areas like quantum mechanics, statistical physics, nonlinear optics, and celestial Mechanics. By bifurcation theory, we find the phase portrait of the proposed model. Bifurcation analysis in the proposed systems helps figure out how small changes in parameters can cause big changes in how the system behaves, like going from stable states to chaotic dynamics. It pinpoints critical thresholds where these transitions occur, aiding in the prediction and control of complex behaviors. We also present some traveling wave solutions according to the phase portrait orbit. Furthermore, the exact traveling wave solutions of the time M-fractional (3 + 1)-dimensional Painlevé integrable model are investigated by using the modified simple equation technique. This method provides the solutions directly without any predefined solutions. Under the condition, the solutions are real and complex valued in terms of exponential, trigonometric, and hyperbolic function form. For the special ideals of free parameters, we will include the bright bell wave, dark bell wave, interaction of kink and periodic lump wave, double periodic wave, double dark bell wave, and so on. By visualizing, the three, two-dimensional and density diagrams, the dynamic properties of the proposed model are examined and illustrated, enhancing the comprehension and application of time M-fractional (3 + 1)-dimensional Painlevé integrable model. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Hyperbolic functions

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Mechanistic switch in corrosion behavior of magnesium alloy diamond lattice structures induced by argon plasma treatment

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Journal of Magnesium and Alloys 2025年第1期13卷 101-119页

作者： Viviana M.Posadaa Alexandru Marin Tonny Naranjo Juan Ramírez Patricia Fernández-Morales Ken and Mary Alice Lindquist Department of Nuclear Engineering Pennsylvania State UniversityPA USA Department of Mechanical Engineering School of MinesUniversidad Nacional de ColombiaBogotáColombia Department of Nuclear Plasma and Radiological EngineeringCollege of EngineeringUniversity of Illinois at Urbana-ChampaignILUSA Medicine Faculty Universidad Pontificia BolivarianaAntioquiaColombia Corporación para Investigaciones Biológicas AntioquiaColombia Industrial Engineering Faculty Universidad Pontificia BolivarianaAntioquiaColombia Materials Science and Engineering Department Pennsylvania State UniversityUniversity ParkPA16802USA Surface Analysis Laboratory Institute for Nuclear Research PitestiMioveni15400Romania Department of Electronics and Computer Science Pontificia Universidad Javeriana de CaliColombia

Advancing 3D magnesium(Mg)development beyond current limitations requires controlling Mg alloy degradation in pre-designed,low-dimension *** study reveals a mechanistic switch in the corrosion behavior of Mg alloy(3.6%Al,0.8%Zn)diamond lattice structures,induced by plasma nanosynthesis(400 eV Ar^(+)ions,fluence 1×10^(17) ions/cm^(2)).Plasma treatment of the Mg alloy increases surface Mg from 1.5%to 14.5%,enhances carbonate formation,and generates a nanostructured surface with a Mg carbonate layer over an oxide/hydroxide *** vitro and in vivo analyses over 8 wk demonstrate how this treatment fundamentally alters the degradation process and stability of these 3D *** untreated samples initially formed a protective film that subsequently diminished,DPNS-treated samples demonstrated an inverse corrosion behavior.X-ray photoelectron spectroscopy(XPS)and electrochemical impedance spectroscopy(EIS)confirmed the presence of a stable,protective layer composed of magnesium oxide,magnesium hydroxide,and magnesium carbonate on the DPNS-treated *** 14 days,the DPNS-treated sample exhibited a more positive corrosion potential(-0.69 V versus-1.36 V)and a marginally lower current density(0.73 mA/cm^(2)compared to 0.75 mA/c^(2))relative to the *** protective layer,combined with modified surface topology,initiated a core-to-periphery degradation pattern that maintained structural integrity for up to 8 wk *** findings support the conclusion that the DPNS-treated scaffold demonstrates sustained improved corrosion resistance over time compared to the untreated ***-CT revealed plasma-treated samples retained larger struts(504.9±95.3μm at 8 wk)and formed larger H_(2) pockets extending 14.2 mm from the implant center,versus 4.9 mm in *** corrosion behavior switch enhances stability but risks pore clogging,offering insights for tailoring Mg alloy degradation and H_(2) evolution in 3D architectures

关键词： Mg Corrosion resistance Cellular materials Nanotopography Nano-medicine Diirected plasma nanosynthesis

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A New Benchmark and Algorithm for Clothes-Changing Video Person Re-Identification

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IEEE Transactions on Information Forensics and Security 2025年 20卷 1993-2005页

作者： Wang, Likai Zhang, Xiangqun Han, Ruize Wei, Yanjie Wang, Song Feng, Wei Tianjin University College of Intelligence and Computing Tianjin300350 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518107 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

Person re-identification (Re-ID) is a classical computer vision task and has significant applications for public security and information forensics. Recently, long-term Re-ID with clothes-changing has attracted increasing attention. However, existing methods mainly focus on image-based setting, where richer temporal information is overlooked. In this paper, we focus on the relatively new yet practical problem of Clothes-Changing Video-based Re-ID (CCVReID), which is less studied. First, given the dataset shortage, we build two new benchmark datasets for CCVReID problem, including a large-scale synthetic video dataset and a real-world one, both containing human sequences with various clothing changes. Moreover, we systematically study this problem by simultaneously considering the classical appearance feature and temporal feature contained in the video. We develop a dual-branch fusion framework that makes use of the information from both clothes-aware appearance feature and clothes-free gait feature. For better information fusion, a confidence-guided re-ranking strategy is proposed to adaptively balance the weight of these two categories of features. We have released the benchmark and code proposed in this work to the public at https://***/kkw98/CCVReID. © 2025 IEEE.

关键词： Reamers

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Effect of Submerged Vegetation Density on Flow Hydrodynamics, Bulk Drag Coefficient, and Bed Friction

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Iranian Journal of science and Technology - Transactions of Civil engineering 2025年 1-9页

作者： Derakhshan, Sadegh Afzalimehr, Hossein Nazari-Sharabian, Mohammad Karakouzian, Moses Faculty of Civil Engineering Iran University of Science and Technology Tehran 16846-13114 Iran Department of Mathematics Engineering and Computer Science West Virginia State University Institute 25112 WV United States Department of Civil and Environmental Engineering and Construction University of Nevada Las Vegas Las Vegas 89154 NV United States

In a laboratory flume, experiments were conducted to explore bulk flow characteristics in channels with submerged aquatic vegetation patches of finite length and width with varying densities. The experiments aimed to assess the significance of precise drag coefficients and understand the impact of vegetation on bed friction. Wooden rods were used as surrogates for vegetation. Different vegetation densities were featured in six experimental setups. The Boundary Layer Characteristics Method (BLCM) was employed to predict bed shear stress, and a force balance approach was used for calculating bulk drag coefficients. It was found that an increase in vegetation density leads to a rise in the bulk drag coefficient. The presence of vegetation was observed to significantly alter the flow field, causing a redirection of flow from vegetated to unvegetated areas. Contrary to the common assumption in many studies that the bulk drag coefficient equals one, the findings from these experiments suggested this assumption might not be accurate. Additionally, the impact of vegetation on bed friction, often overlooked, was investigated. Two classic bed friction models, which do not account for flow field heterogeneities due to vegetation, and the BLCM, which considers these heterogeneities, were used to estimate bed friction. These estimates were then used in a flow resistance model to predict total friction, including both bed and vegetation friction. The effectiveness of the BLCM over the classic models suggests inaccuracies in the assumption that vegetation does not impact bed friction. © The Author(s), under exclusive licence to Shiraz University 2024.

关键词： Bed friction Boundary layer characteristics method Drag coefficient Force balance Submerged aquatic vegetation

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Underwater Acoustic Communication Using Multi-Layer Vector Approximate Message Passing Evaluated on the Watermark Benchmark

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IEEE Access 2025年 13卷 90409-90417页

作者： Julian Winkler Sabah Badri-Hoeher Faculty of Computer Science and Electrical Engineering Kiel University of Applied Sciences Kiel Germany

The multi-layer vector approximate message passing algorithm is applied to the problem of channel estimation in underwater acoustic communication addressing the estimation of time-varying channel characteristics. A pre-trained artificial neural network is used as prior for the channel estimation. The communication receiver is designed as a factor graph with a low-density parity check decoder as factor node. The performance of the proposed communication scheme is evaluated by comparing the bit error rates with classical communication schemes. The bit error rate is significantly decreased on strongly time-varying channels. Different datasets are compared for training the channel estimator.

关键词： Channel estimation Receivers Underwater acoustics Vectors Signal processing algorithms Parity check codes Noise Message passing Approximation algorithms Deep learning

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Neural-XGBoost: A Hybrid Approach for Disaster Prediction and Management Using Machine Learning

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IEEE Access 2025年 13卷 86768-86780页

作者： Saleem, Muhammad Asim Javeed, Ashir Benjapolakul, Watit Srisiri, Wattanasak Chaitusaney, Surachai Kaewplung, Pasu Chulalongkorn University Center of Excellence in Artificial Intelligence Machine Learning and Smart Grid Technology Department of Electrical Engineering Faculty of Engineering Bangkok10330 Thailand Blekinge Institute of Technology Department of Computer Science Karlskrona Sweden

Effective disaster prediction is essential for disaster management and mitigation. This study addresses a multi-classification problem and proposes the Neural-XGBoost disaster prediction model (N-XGB), a hybrid model that combines neural networks (NN) for feature extraction with XGBoost for classification. The NN component extracts high-level features, while XGBoost uses gradient-boosted decision trees for accurate predictions, combining the strengths of deep learning and boosting techniques for improved accuracy. The N-XGB model achieves an accuracy of 94.8% and an average F1 score of 0.95 on a real-world dataset that includes wildfires, floods and earthquakes, significantly outperforming baseline models such as random forest, Support vector machine and logistic regression 85% accuracy. The balanced F1 scores for wildfires 0.96, floods 0.93, and earthquakes 0.96 demonstrate the model's robustness in multi-class classification. The Synthetic Minority Oversampling Technique (SMOTE) balances datasets and improves model efficiency and capability. The proposed N-XGB model provides a reliable and accurate solution for predicting disasters and contributes to improving preparedness, resource allocation and risk management strategies. © 2013 IEEE.

关键词： Risk management

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Approximate Message Passing for Spatial Modulation with Structured Sparsity

Approximate Message Passing for Spatial Modulation with Stru...

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International ITG Conference on Source and Channel Coding (SCC)

作者： Daniel Franz Volker Kühn Faculty of Computer Science and Electrical Engineering University of Rostock

ISBN: (数字)9798331522896

ISBN: (纸本)9798331522902

Multiple antennas at transmitter and receiver have significantly improved the performance of wireless communications systems. Traditionally, space-time coding, beamforming, or spatial multiplexing are applied to achieve diversity, SNR, and multiplexing gains, respectively. A different concept is pursued with Generalized Spatial Modulation (GSM). It conveys information through the selection of active antennas from a set of available antennas in addition to the transmission of conventional modulation symbols. This results in sparse transmit vectors, and detection algorithms known from compressed sensing can be applied. In this paper, Vector Approximate Message Passing (VAMP) is considered for the detection of GSM signals in massive Multiple-Input Multiple-Output (MIMO) systems. Its performance is improved by introducing structured redundancy in space or in time. In order to exploit this redundancy, the VAMP algorithm has to be extended by an additional graph layer. The resulting performance is evaluated by analyzing the error rates and the throughput obtained from Monte Carlo simulations.

关键词： GSM Correlation Message passing Redundancy Transmitting antennas Modulation Throughput Vectors MIMO Encoding

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Hyperbolic Distance Based on EMD and Diffusion for Hyperspectral Imaging

Hyperbolic Distance Based on EMD and Diffusion for Hyperspec...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Elad Lavi Amir Bourvine Ya-Wei Eileen Lin Ronen Talmon Taub Faculty of Computer Science Technion Viterbi Faculty of Electrical and Computer Engineering Technion

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

In this paper, we introduce EMD-Based Hyperbolic Diffusion Distance (EMD-HDD), a new method for constructing a meaningful distance metric for hierarchical data with latent hierarchical structure. Our method relies on hyperbolic geometry, diffusion geometry, and the Earth Mover’s Distance (EMD). Specifically, our method embeds data points into a product manifold of hyperbolic spaces, allowing us to recover the hidden hierarchical structure encoded by the mutual relationships between features. We demonstrate the effectiveness of EMD-HDD through experiments on five hyperspectral imaging datasets, showcasing its capability to capture and reveal the intrinsic hierarchical structures inherent in such data.

关键词： Manifolds Geometry Measurement Earth Imaging Signal processing Acoustics Speech processing Hyperspectral imaging

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Development of Additive Manufacturing Design Based on Machine Learning: A Biomedical engineering Approach 1

Development of Additive Manufacturing Design Based on Machin...

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1st International Conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Khan, Akbar Valivarthi, Dharma Teja Banik, Shampa Kakkad, Ashish Sujatha, B. Acharya, Deepak Nimra College of Engineering and Technology ECE Department Andhra Pradesh Vijayawada India Tek Leaders TX United States Dhaka Bangladesh Marwadi University Faculty of Physiotherapy Rajkot India Department of Computer Science and Engineering Tamilnadu Tiruchengode India The University of Alabama in Huntsville Department of computer science United States

ISBN: (纸本)9798331518578

Additive manufacturing (AM) is a versatile and complex manufacturing technique that is extensively employed in the production of personalized biopolymer-orientated items and sophisticated medical architecture. One of the most developed AM techniques is selective laser melting (SLM), which uses a laser as an energy resource to completely melt successive layers of granular resources. SLM produces titanium-oriented alloys that are highly biocompatible and have exceptionally excellent physical qualities, which have led to their widespread usage in biomedical uses. An artificial neural network-based optimizing approach was established to enhance the standard of Ti-6Al-4V SLM-based parts and assist manufacturing professionals in selecting optimum process settings. The approach relates 4 primary procedure settings to two target characteristics of the part. To improve the system's accuracy throughout neural network training, several techniques were employed to address undesirable issues. The denseness and surface hardness values of the system's R2 of 99 percent demonstrated its effectiveness. After that, a selection system was developed that lets users select the best process variables for manufactured goods whose attributes satisfy particular user requirements. The optimum part quality produced by tests using the ideal process variables suggested by the optimizing approach was almost the same as those specified by the user, with only 0.9 to 4.4 percent of mistakes at the high, significantly confirming the system's dependability. © 2025 IEEE.

关键词： Titanium alloys

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