A Simplified Fish School Search Algorithm for Continuous Single-Objective Optimization by Elliackin Figueiredo, Clodomir Santana, Hugo Valadares Siqueira, Mariana Macedo, Attilio Converti, Anu Gokhale, Carmelo Bastos-Filho

“…The SFSS also reduces the number of fitness evaluations per iteration and minimizes the algorithm’s parameter set. Computational experiments were conducted using a benchmark suite from the CEC 2017 competition to compare the SFSS with the traditional FSS and five other well-known metaheuristics. …”
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Hardware and Software Methods for Secure Obfuscation and Deobfuscation: An In-Depth Analysis by Khaled Saleh, Dirar Darweesh, Omar Darwish, Eman Hammad, Fathi Amsaad

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Assessing the Impact of Psyllid Pesticide Resistance on the Spread of Citrus Huanglongbing and Its Ecological Paradox by Runyun Gan, Youquan Luo, Shujing Gao

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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis by Basma Jumaa Saleh, Zaid Omar, Muhammad Amir As’ari, Vikrant Bhateja, Lila Iznita Izhar

“…To address this, we propose an efficient, modified radiomics feature processing method that integrates an optimal aerial perspective (OAP) parameter-based intensity dark channel prior (IDCP) with a 50-layer residual deep neural network (ResNet50 DNN) for autolesion segmentation (ALS-IOAP-DNN). …”
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Ensemble Transformer–Based Detection of Fake and AI–Generated News by Md. Ishraquzzaman, Mohammed Ashraful Islam Chowdhury, Shahreen Rahman, Riasat Khan

“…The proposed ensemble model is optimized by applying model pruning (reducing parameters from 265M to 210M, improving training time by 25%) and dynamic quantization (reducing model size by 50%, maintaining 95.68% accuracy), enhancing scalability and efficiency while minimizing computational overhead. …”
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Classifying the Mortality of People with Underlying Health Conditions Affected by COVID-19 Using Machine Learning Techniques by Rami Mustafa A. Mohammad, Malak Aljabri, Menna Aboulnour, Samiha Mirza, Ahmad Alshobaiki

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Materials-discovery workflow guided by symbolic regression for identifying acid-stable oxides for electrocatalysis by Akhil S. Nair, Lucas Foppa, Matthias Scheffler

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Student Performance Prediction Using Machine Learning Algorithms by Esmael Ahmed

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Research on action matching of skeletal point coordinates and sports teaching application based on Open-pose by Shunmin Su

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The siRNA Non-seed Region and Its Target Sequences Are Auxiliary Determinants of Off-Target Effects. by Piotr J Kamola, Yuko Nakano, Tomoko Takahashi, Paul A Wilson, Kumiko Ui-Tei

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SwinD-Net: a lightweight segmentation network for laparoscopic liver segmentation by Shuiming Ouyang, Baochun He, Huoling Luo, Fucang Jia

“…Additionally, we introduce Swin Transformer Blocks, which have a larger computational and parameter footprint, to extract global information and capture high-level semantic features. …”
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Tiny dLIF: a dendritic spiking neural network enabling a time-domain energy-efficient seizure detection system by Luis Fernando Herbozo Contreras, Leping Yu, Zhaojing Huang, Ziyao Zhang, Armin Nikpour, Omid Kavehei

“…Drawing inspiration from brain architecture, we investigate biologically plausible algorithms, specifically emphasizing time-domain inputs with low computational overhead. Our novel approach features two hidden layer dendrites with leaky integrate-and-fire spiking neurons, containing fewer than 300 K parameters and occupying a mere 1.5 MB of memory. …”
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RecurrentOcc: An Efficient Real-Time Occupancy Prediction Model with Memory Mechanism by Zimo Chen, Yuxiang Xie, Yingmei Wei

“…We introduce the Scene Memory Gate, a new temporal fusion module that condenses temporal scene features into a single historical feature map. This eliminates the need for repeated extraction and aggregation of multiple temporal images, reducing computational overhead. …”
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Adapting to time: Why nature may have evolved a diverse set of neurons. by Karim G Habashy, Benjamin D Evans, Dan F M Goodman, Jeffrey S Bowers

“…In more complex spatio-temporal tasks, an adaptable bursting parameter was essential. Overall, allowing adaptation of both temporal and spatial parameters enhances network robustness to noise, a vital feature for biological brains and neuromorphic computing systems. …”
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Speech emotion recognition using long-term average spectrum by Huerta-Hernández Luis David, Meléndez-Acosta Nayeli Joaquinita, Troncoso-Romero David Ernesto, Ramírez-Pacheco Julio César, León-Borges Jose Antonio

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Mine underground object detection algorithm based on TTFNet and anchor-free by Song Zhen, Qing Xuwen, Zhou Meng, Men Yuting

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Toward improving precision and complexity of transformer-based cost-sensitive learning models for plant disease detection by Manh-Tuan Do, Manh-Hung Ha, Duc-Chinh Nguyen, Oscal Tzyh-Chiang Chen, Oscal Tzyh-Chiang Chen

“…In particular, we introduced a transformer module, a fusion of the SPP and C3TR modules, to synthesize features in various sizes and handle uneven input image sizes. …”
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Electronic properties of stacking faults in Bernal graphite by Patrick Johansen Sarsfield, Sergey Slizovskiy, Mikito Koshino, Vladimir Fal’ko

“…Using a self-consistent tight-binding model of graphite, incorporating all Slonczewski-Weiss-McClure parameters, we compute the dispersion and quantum topological characteristics of the two dimensional band, we calculate the Landau level spectrum in magnetic field and the related Shubnikov-de Haas oscillation parameters, as well as the cyclotron mass of the two-dimensional carriers. …”
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A machine vision approach for classification and dimensional design of furniture panels using GMM-SVM by Yuan Tian, Li Zhao, Haoxin Li

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Spherical harmonics texture extraction for versatile analysis of biological objects. by Oane Gros, Josiah B Passmore, Noa O Borst, Dominik Kutra, Wilco Nijenhuis, Timothy Fuqua, Lukas C Kapitein, Justin M Crocker, Anna Kreshuk, Simone Köhler

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