Design and Optimization of an FPGA-Based Infrared Dim Small Target Detection Network Under a Sky Cloud Background by Yongbo Cheng, Xuefeng Lai, Yucheng Xia

“…Experimental results indicate that the proposed network structure optimization methods reduce the hardware inference time by 15.78%. …”
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Intelligent Fault Detection and Self-Healing Mechanisms in Wireless Sensor Networks Using Machine Learning and Flying Fox Optimization by Almamoon Alauthman, Abeer Al-Hyari

“…This paper presents an intelligent framework based on Light Gradient Boosting Machine integration for fault detection and a Flying Fox Optimization Algorithm in dynamic self-healing. …”
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Accelerating Training of Convolutional Neural Networks With Hessian-Free Optimization for Detecting Alzheimer’s Disease in Brain MRI by Marios Pafitis, Maria Constantinou, Chris Christodoulou

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Optimizing deep belief network for concrete crack detection via a modified design of ideal gas molecular dynamics by Tan Qin, Gongxing Yan, Huaguo Jiang, Minqi Shen, Andrea Settanni

“…The present research concentrates on the development of crack diagnosis algorithms based on vision using an optimized version of Deep Neural Network (DNN). The DNN model employed in the current study is the deep belief network (DBN), while the optimization technique is based on a newly designed variant of the Ideal Gas Molecular Movement (MIGMM). …”
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Intrusion Detection for Wireless Sensor Network Using Particle Swarm Optimization Based Explainable Ensemble Machine Learning Approach by Shaikh Afnan Birahim, Avijit Paul, Fahmida Rahman, Yamina Islam, Tonmoy Roy, Mohammad Asif Hasan, Fariha Haque, Muhammad E. H. Chowdhury

“…This paper proposes a novel Intrusion Detection System (IDS) leveraging Particle Swarm Optimization (PSO) and an ensemble machine learning approach combining Random Forest (RF), Decision Tree (DT), and K-Nearest Neighbors (KNN) models to enhance the accuracy and reliability of intrusion detection in WSNs. …”
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Optimized LDPC Matrices: Reducing and Redistributing 1 bits for Enhanced MAP Detection in Bit-Patterned Media Recording Systems by Thien An Nguyen, Jaejin Lee, Jong-Ho Lee

“…This interference complicates signal interpretation, making accurate data recovery more challenging and necessitating advanced detection methods. To address these challenges, sophisticated algorithms such as maximum a posteriori (MAP) detection have shown promise in improving data recovery by accounting for the probabilistic nature of signals and noise. …”
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Improved smart city security using a deep maxout network-based intrusion detection system with walrus optimization by Wahid Rajeh, Majed Aborokbah, Manimurugan S., Umar Albalawi, Ahamed Aljuhani, Osama Shibl Abdalghany Younes, Karthikeyan Periyasami

“…Methods This research addresses the need for robust intrusion detection systems (IDS) tailored to the unique challenges of securing public transportation within smart cities. …”
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OPTIMIZATIONS OF DEEP LEARNING OBJECTS DETECTION MODELS FOR INFERENCE ACCELERATION ON GENERAL-PURPOSE AND HARDWARE-ACCELERATED SINGLE-BOARD PLATFORMS by Dmytro Myroniuk, Bohdan Blahitko

“…The concepts of deep learning model optimization are analyzed. Materials and Methods. …”
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Reinforcement Learning With Deep Features: A Dynamic Approach for Intrusion Detection in IoT Networks by Mohamad Khayat, Ezedin Barka, Mohamed Adel Serhani, Farag Sallabi, Khaled Shuaib, Heba M. Khater

“…Furthermore, an RL-based IDS (RL-IDS) that incorporates RNNs and autoencoders with a deep Q-network was proposed to enhance threat detection. Experimental outcomes emphasize the superiority of the method, obtaining 99.45% accuracy with 70% training data and 99.80% with 80%. …”
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Implementation of medication reviews to optimize the use of medications in Swiss nursing homes: a mixed-methods study by Stephanie Mena, Julie Dubois, Marie Schneider, Anne Niquille

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Optimized methods for the targeted surveillance of extended-spectrum beta-lactamase-producing Escherichia coli in human stool by Sarah Gallichan, Sally Forrest, Esther Picton-Barlow, Claudia McKeown, Maria Moore, Eva Heinz, Nicholas A. Feasey, Joseph M. Lewis, Fabrice E. Graf

“…In this study, we compared different laboratory methods to see which worked best for detecting extended-spectrum beta-lactamase (ESBL)-producing E. coli, a common cause of urinary tract or bloodstream infections, from human stool samples. …”
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Social Media Text Stance Detection Based on Large Language Models by LI Juhao, SHI Lei, DING Meng, LEI Yongsheng, ZHAO Dongyue, CHEN Long

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Establishment of a One–Pot RAA–CRISPR/Cas13a Assay-Based TGEV S Gene Detection by Lindan Lv, Hao Mu, Shaomei Li, Jieqi Gao, Mingni Liu, Shuizhu Niu, Guoyang Xu, Lizhi Fu, Zhenhui Song, Liu Yang

“…In this study, we developed a one–pot assay combining recombinase-aided amplification (RAA) and CRISPR/Cas13a technology, targeting the TGEV S gene. This method was optimized for sensitivity and specificity, with orthogonal tests determining the optimal reagent concentrations. …”
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Comparative Analysis and Optimal Selection of Calibration Functions in Pure Rotational Raman Lidar Technique by Yinghong Yu, Siying Chen, Wangshu Tan, Rongzheng Cao, Yixuan Xie, He Chen, Pan Guo, Jie Yu, Rui Hu, Haokai Yang, Xin Li

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Minimal Residual Disease Detection: Implications for Clinical Diagnosis and Cancer Patient Treatment by Meiling Song, Wenjing Pan, Xinjie Yu, Jie Ren, Congli Tang, Zhu Chen, Zhe Wang, Yan Deng, Nongyue He, Hongna Liu, Song Li

“…In hematological malignancies, MRD pose an increasingly serious threat to the health of Chinese people. Accurate MRD detection is essential for assessing relapse risk and optimizing therapeutic strategies, yet current methods such as flow cytometry, polymerase chain reaction (PCR), and next‐generation sequencing (NGS) each have distinct limitations, and significant gaps remain in achieving optimal sensitivity and specificity of these technologies. …”
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Logistics Hub Surveillance: Optimizing YOLOv3 Training for AI-Powered Drone Systems by Georgios Tepteris, Konstantinos Mamasis, Ioannis Minis

“…In this work, we propose methods to optimize the training of such high-performing systems. …”
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Catalytic test-method for determination of ruthenium microquantities based on methyl orange oxidation with potassium periodate by E. G. Khomutova, N. A. Maltseva, S. A. Zagorodnikova

“…The conditions for the indicator reaction performance were optimized. It is possible to determine ruthenium in the range of its concentrations 0.010 ÷ 0.55 µg/ml .The detection limit equals to 0.0035 µg/ml, the relative standard deviation (RSD) is not higher than 0.058. …”
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Joint Optimization of Carrier Frequency and PRF for Frequency Agile Radar Based on Compressed Sensing by Zhaoxiang Yang, Hao Zheng, Yongliang Zhang, Junkun Yan, Yang Jiang

“…The echo of optimized signals is subsequently reconstructed using the alternating direction method of multipliers (ADMM) algorithm. …”
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Research on Early Diagnosis Methods for Broiler Chicken Diseases Based on Swarm Intelligence Optimization Algorithms and Random Forest by X Peng, C Chen, L Yu, X Kong, B Sun

“…A baseline Random Forest (RF) model achieved 94.01% diagnostic accuracy for broiler diseases. To optimize performance, we developed RF_WOA_DBO-an integrated algorithm combining RF with enhanced Whale Optimization Algorithm (WOA) for global feature selection and modified Dung Beetle Optimizer (DBO) for local parameter tuning. …”
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Application of Doehlert design combined with chemometrics tools: Example of the optimization of the elution of neurotransmitters and metabolites by HPLC by Camille Rosier, Bruno P. Guiard, Guillaume Gotti

“…Moreover, the combination of parameters has been taken into account with chemometrics, allowing a highly effective enhancement of compound elution. The optimized method achieves low detection and quantification limits in the nanomolar range, making it suitable for precise neurotransmitter analysis in complex biological samples.…”
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