Using artificial intelligence methods for the optimal synthesis of reversible networks by Taras Kyryliuk, Mykhailo Palahuta, Vitaly Deibuk

“…Reversible logic allows for a reduction in energy and information losses because logical reversible operations are performed without loss. …”
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A multi-objective improved horse herd optimizer based on convex lens imaging for stochastic optimization of wind energy resources in distribution networks considering reliability a... by Fude Duan, Ali Basem, Dheyaa J. Jasim, Mahdiyeh Eslami, Mustafa Okati

“…Also, the effect of incorporating uncertainties are evaluated on power loss and reliability using the MOIHHO. Moreover, the superiority of the MOIHHO is investigated in achieving better objective function value compared with conventional MOHHO, multi-objective particle swarm optimization (MOSPO), multi-objective gray wolf optimizer (MOGWO), and multi-objective gazelle optimization algorithm (MOGOA). …”
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DC-WUnet: An Underwater Ranging Signal Enhancement Network Optimized with Depthwise Separable Convolution and Conformer by Xiaosen Liu, Juan Li, Jingyao Zhang, Yajie Bai, Zhaowei Cui

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A Lightweight Deep Learning Network with an Optimized Attention Module for Aluminum Surface Defect Detection by Yizhe Li, Yidong Xie, Hu He

“…Furthermore, we employed the genetic K-means algorithm to optimize prior region selection, and a lightweight Ghost model to reduce network complexity by 14.3%, demonstrating the superior performance of the Ghost model in terms of loss function optimization during training and validation as well as in terms of detection accuracy, speed, and stability. …”
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Loss of Pleiotropic Regulatory Functions in Tannin1, the Sorghum Ortholog of Arabidopsis Master Regulator TTG1 by Anthony Schuh, Geoffrey P. Morris

“…We characterized genome‐wide differential expression of leaf tissue using RNA sequencing in near‐isogenic lines (NILs) that contrasted wildtype Tan1 and loss‐of‐function tan1‐b alleles, under optimal temperature and chilling stress. …”
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ESTIMATING THE PROPERTIES OF TECHNOLOGICAL SYSTEMS BASED ON FUZZY SETS by Vladimir Beskorovainyi, Heorhii Berezovskyi

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Targeting key angiogenic pathways with a bispecific CrossMAb optimized for neovascular eye diseases by Jörg T Regula, Peter Lundh von Leithner, Richard Foxton, Veluchamy A Barathi, Chui Ming Gemmy Cheung, Sai Bo Bo Tun, Yeo Sia Wey, Daiju Iwata, Miroslav Dostalek, Jörg Moelleken, Kay G Stubenrauch, Everson Nogoceke, Gabriella Widmer, Pamela Strassburger, Michael J Koss, Christian Klein, David T Shima, Guido Hartmann

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Transient expression of full-length and mature nattokinase in Nicotiana benthamiana reveals early necrosis from full-length form and functional activity of the mature enzyme by Kevin Wang, Hugh Mason, Kylie Hall, Ethan Slone, Kylie Tackett, Nan Wang

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Robust object counting through distribution uncertainty matching and optimal transport by Sabri Boughorbel, Fethi Jarray, Rachida Zegour, Nauman Ullah Gilal, Khaled Al Thelaya, Marco Agus, Jens Schneider

“…In this paper, we propose a method called DUMLO (Distribution Uncertainty Matching for Loss Optimization) that defines a loss function between a ground-truth density map and a target density map by modeling uncertainty over an augmented set of points. …”
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Systematic analysis and optimization of grain postproduction operation patterns in south China by YING Xia-fang, ZHENG Wen-zhong, HE Yong

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Scoop: An Optimization Algorithm for Profiling Attacks against Higher-Order Masking by Nathan Rousselot, Karine Heydemann, Loïc Masure, Vincent Migairou

“…These propositions are gathered in a new publicly available optimization algorithm, Scoop. Scoop combines second-order derivative of the loss function in the optimization process, with a sparse stochastic mirror descent. …”
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Trajectory Optimization of Hypersonic Periodic Cruise Using an Improved PSO Algorithm by Hesong Li, Yi Wang, Shangcheng Xu, Yunfan Zhou, Dan Su

“…Firstly, through theoretical analysis, it is determined that the optimal throttle curve can be parameterized as a switching function. …”
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Topology Optimization of Passive Constrained Layer Damping with Partial Coverage on Plate by Weiguang Zheng, Yingfeng Lei, Shande Li, Qibai Huang

“…The objective function is defined as a combination of several modal loss factors solved by finite element-modal strain energy (FE-MSE) method. …”
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Optimization method for educational resource recommendation combining LSTM and feature weighting by Meixia Yang

“…The constructed model exhibited a loss function value below 0.4, a response time of less than 400ms, and a recommendation accuracy of over 80 % on the relevant dataset. …”
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GAN-based solar radiation forecast optimization for satellite communication networks by Chao Chen, Xin Liu, Shizhong Zhao, Muhammad Bilal

“…This adversarial process, guided by a hybrid loss function and a discriminator treated as a learnable objective function, refines the forecast quality. …”
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Prediction of ball-on-plate friction and wear by ANN with data-driven optimization by Alexander Kovalev, Yu Tian, Yonggang Meng

“…Abstract For training artificial neural network (ANN), big data either generated by machine or measured from experiments are used as input to “learn” the unspecified functions defining the ANN. The experimental data are fed directly into the optimizer allowing training to be performed according to a predefined loss function. …”
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Search Guidance Network Assisted Dynamic Particle Swarm Optimization Algorithm by LIU Zhi, SONG Wei

“…Maintaining local and global diversity in dynamic environments can effectively avoid diversity loss. To this end, a search guidance network-based particle swarm optimization (SGN-PSO) is proposed. …”
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Optimizing capacitor size and placement in radial distribution networks for maximum efficiency by R. Arunjothi, K.P. Meena

“…After implementing the optimal capacitor placements at the identified candidate nodes, a significant reduction in losses within the radial distribution system is observed. …”
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Optimization Methodology for Meningioma and Acoustic Neuroma Detection Model Based on DCGAN by CHEN Jingcong, RAN Fengwei, ZHANG Haowei, LIU Ying

“…This paper proposes a DCGAN (deep convolutional generative adversarial networks) with improved loss function for data augmentation of meningioma and acoustic neuroma detection models to address the issues of scarce medical image datasets, imbalanced number of categories, and poor imaging quality. …”
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Calculation of Neural Network Weights and Biases Using Particle Swarm Optimization by Jerin Paul Selvan, Girish Pandurang Potdar

“…This technique aids in figuring out a loss function’s gradient for every network weight. …”
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