Enhancing laser surface texturing with driving training-based optimization: A metaheuristic approach by Ishwer Shivakoti, Sunny Diyaley, Partha Protim Das, Abhijit Bhowmik, A. Johnson Santhosh

“…This paper investigates the capability of Laser Surface Textruing (LST) to induce texture on Ti-6Al-4V, aiming on optimizing process parameters viz. average power, pulse frequency, scanning speed, and gas pressure using the Driving Training-based Optimization (DTBO) algorithm. …”
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Machine learning-aided lattice optimization for ultra-lightweight 3D-printed aligners by Poom Narongdej, Bradley Yuhasz, Tianmin Kong, Diego Rojas, Qidi Peng, Ehsan Barjasteh

“…This study addresses this issue by investigating the use of additively manufactured photopolymer lattice structures for orthodontic thermoforming models, aiming to optimize physical strength while minimizing material usage and waste. …”
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End-to-end feature fusion for jointly optimized speech enhancement and automatic speech recognition by Mohamed Medani, Nasir Saleem, Fethi Fkih, Manal Abdullah Alohali, Hela Elmannai, Sami Bourouis

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Micro‐CT Analysis of Rodent Temporal Bones: Identifying Optimal Species for Otological Research by Hannah Daoudi, Evelyne Ferrary, Cerine Moula, Florence Agnely, Amélie Bochot, Catherine Cailleau, Yann Nguyen, Ghizlène Lahlou, Renato Torres

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Construction of optimal symmetric Z-complementary code set based on extended Boolean function by CHEN Xiaoyu, ZHANG Zhaoyu, DU Yuqiong

“…Aiming at the problem of the limited number of training sequences in the wideband generalized spatial modulation (GSM) system, the construction methods of the optimal symmetric Z-complementary code set (SZCCS) and the enhanced cross Z-complementary set (E-CZCS) were studied. …”
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Theoretical Analysis and Optimization Strategies of Wavefront Errors and Chromatic Aberrations Induced by Optical Coatings by Yang Gao, Liang Miao, Xin-Dong Chen, Xin Zhang, Cheng-Gang Mo

“…This study introduces novel optimization strategies for thin-film components through theoretical derivation, aiming to minimize wavefront errors by optimizing <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>G</mi><mi>D</mi></mrow></semantics></math></inline-formula>.…”
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Efficiently optimized multi-fillers for rain gardens: Long-term pollution control performance by Tianyin Huang, Zhixin Wang, Yiming Nie, Hanhan Liu, Peirong Li, Jingjing Yang, Bingdang Wu

“…To address this issue, this study employs the Analytic Hierarchy Process (AHP) to systematically evaluate 11 types of fillers, including 5 natural materials, 3 industrial wastes, and 3 artificial materials, aiming to optimize filler configurations and enhance the pollutant removal efficiency of rain gardens. …”
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Hybrid Feature and Optimized Deep Learning Model Fusion for Detecting Hateful Arabic Content by Karim Gasmi, Ibtihel Ben Ltaifa, Alameen Eltoum Abdalrahman, Omer Hamid, Mohamed Othman Altaieb, Shahzad Ali, Lassaad Ben Ammar, Manel Mrabet

“…The final prediction is obtained through a weighted fusion of individual model outputs, where the optimal weights are selected using the Grey Wolf Optimizer (GWO), aiming to maximize classification accuracy. …”
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Improved Lyrebird optimization for multi microgrid sectionalizing and cost efficient scheduling of distributed generation by Karthik Nagarajan, Arul Rajagopalan, Mohit Bajaj, Valliappan Raju, Vojtech Blazek, Lukas Prokop

“…This paper introduces the Improved Lyrebird Optimization Algorithm (ILOA) for optimal sectionalizing and scheduling of multi-microgrid systems, aiming to minimize generation costs and active power losses while ensuring system reliability. …”
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Research on formant estimation algorithm for high order optimal LPC root value screening by Hua LONG, Shumeng SU

“…The root determination threshold, optimal LP root value distribution, peak distribution of formant in spectral envelope and formant estimation error of speech digital resonance model constraints under different orders are investigated. …”
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Enhancing Diversity and Convergence in MMOPs with a Gaussian Similarity-Based Evolutionary Algorithm by Shizhao Wei, Da-Jung Cho

“…Multi-modal multi-objective optimization problems (MMOPs) are challenging due to multiple solutions sharing similar objective values. …”
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Quality Measurement and Optimization Prediction of Urban Waterfront Fitness Space Based on Behavior Simulation by Chunxia YANG, Ruoyao MIN

“…Based on the multi-agent behavior simulation technology and waterfront fitness quality assessment system, this research conducts a quality measurement of nine typical waterfront public spaces along the Huangpu River, and explores the possibility of further optimizing the spatial quality of the Minsheng Wharf area, aiming to provide a systematic method for quality assessment and optimization prediction. …”
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Parameter Sensitivity Analysis and Algorithm Improvement of Optimization Scheduling Model for Cascade Pumping Stations by LIU Xiaolian, LI Zhenrong, WANG Xue-ni, ZHAI Yu, ZHANG Lei-ke, GUO Weiwei, TIAN Yu

“…What's more, aiming at the lack of quantitative sensitivity analysis in the optimal scheduling of cascade pumping stations, the Sobol global sensitivity method was employed to quantitatively analyze the influence of each sensitive parameter on the carbon emissions of the cascade pumping stations. …”
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Optimizing energy flow in advanced microgrids: a prediction-independent two-stage hybrid system approach by Mohamad Javad Mohamadi, Mohammad Tolou Askari, Mahmoud Samiei Moghaddam, Vahid Ghods

“…Abstract This paper presents a two-stage optimization framework for long-term energy management in microgrids, aiming to efficiently integrate various energy sources, storage systems, and consumption elements while addressing uncertainties in load demand and renewable generation. …”
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Microservice combination optimisation based on improved gray wolf algorithm by Jingjing Hu, Xiaojun Xu, Jin Hao, Xiuqi Yang, Kefan Qiu, Yuanzhang Li

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Improved quadratic interpolation optimizer for stochastic short-term hydrothermal scheduling with integration of solar PV and wind power by Noor Habib Khan, Yong Wang, Raheela Jamal, Mohamed Ebeed, Salah Kamel, Guma Ali, Francisco Jurado, Abdel-Raheem Youssef

“…Abstract The quadratic interpolation optimization (QIO) introduces a novel approach inspired by the generalized quadratic interpolation (GQI) with dual mechanisms. …”
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Optimized deep learning models for stress-based stroke prediction from EEG signals by Sivasankaran Pichandi, Gomathy Balasubramanian, Venkatesh Chakrapani, J. Samuel Manoharan

“…The study utilizes EEG signals to categorize stress-related emotions, subsequently assessing stroke risk via an optimized deep learning model. The proposed model is distinguished by its optimized hybrid optimization technique for feature extraction, aimed at stress and stroke prediction. …”
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Multi-Objective Optimization Techniques in Cloud Task Scheduling: A Systematic Literature Review by Olanrewaju L. Abraham, Md Asri Bin Ngadi, Johan Bin Mohamad Sharif, Mohd Kufaisal Mohd Sidik

“…Task scheduling in cloud computing environment aims to identify alternative methods for effectively allocating competing cloud tasks to constrained resources, optimizing one or more objectives. …”
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Optimization of Agave-based pineapple vinegar fermentation through sequential fermentation and chemical characterization by Antika Boondaeng, Chanaporn Trakunjae, Nanthavut Niyomvong

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Optimization of a Newly Developed Chamber Setup for Spatial Dust Measurements in the Context of Containment by Hendrik Küllmar, Martin Schöler, Claudia S. Leopold

“…The optimization was aimed at a maximization of the amount of detected dust and a minimization of the required sample mass. …”
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