Toward lightweight intrusion detection systems using the optimal and efficient feature pairs of the Bot-IoT 2018 dataset by Erman Özer, Murat İskefiyeli, Jahongir Azimjonov

“…Various intrusion detection systems approaches have been proposed previously based on data mining, fuzzy techniques, genetic, neurogenetic, particle swarm intelligence, rough sets, and conventional machine learning. …”
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Driving Anger States Detection Based on Incremental Association Markov Blanket and Least Square Support Vector Machine by Ping Wan, Chaozhong Wu, Yingzi Lin, Xiaofeng Ma

“…Meanwhile, three types of data sets including driver physiology, driving behaviors and vehicle motions, were collected by multiple sensors. …”
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Simulation analysis of stress-strain performance for a lightweight X-ray pulsar detection telescope frame structure by Qingyong Zhou, Qingyong Zhou, Zhiqiang Huang, Bin Xu, Yaohu Lei, Jianguo Lei, Hang Zhao, Chaojing Ye, Likuan Zhu

“…The findings provide a theoretical foundation and critical data reference for designing lens frame structures in space detection telescopes.…”
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Utilizing saliva for non-invasive detection of exercise-induced myocardial injury with point-of-care cardiac troponin-I by Aleksandr N. Ovchinnikov

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AI Driven Framework for Need-Based Insurance Plans Generation and Anomaly Detection Using Deep Learning Techniques by Rabia Rehman, Afia Mazhar, Ayesha Faheem, Irum Matloob, Shoab Ahmad Khan, Sumaira Shaukat, Muazzam A. Khan Khattak, Anwar Ahmed Khan, Muhammad Shoaib Siddiqui, Shama Siddiqui

“…The research demonstrates that the proposed AI driven framework can perform both coverage optimization using multiple patient data sets, as well as decision support in healthcare systems.…”
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Artificial intelligence versus manual screening for the detection of diabetic retinopathy: a comparative systematic review and meta-analysis by Hasan Nawaz Tahir, Naseer Ullah, Mursala Tahir, Inbaraj Susai Domnic, Ramaprabha Prabhakar, Semmal Syed Meerasa, Ahmed Ibrahim AbdElneam, Ahmed Ibrahim AbdElneam, Shahnawaz Tahir, Yousaf Ali

“…These results suggest that AI can be a reliable alternative in clinical settings, with increased early detection rates and reducing the burden on ophthalmologists. …”
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Prospective evaluation of plasma pTau217 stability for the detection of Alzheimer’s disease in a tertiary memory clinic by Javier Arranz, Rosa Ferrer, Nuole Zhu, Sara Rubio-Guerra, Íñigo Rodríguez-Baz, José Enrique Arriola-Infante, Lucía Maure-Blesa, Jesús Garcia-Castro, Judit Selma-González, María Carmona-Iragui, Isabel Barroeta, Ignacio Illán-Gala, Miguel Santos-Santos, Juan Fortea, Alberto Lleó, Mireia Tondo, Daniel Alcolea

“…Abstract Background Knowledge on the effect of analytical variability and storage conditions are essential for the successful implementation of plasma pTau217 in prospective settings. Aims To investigate the performance of plasma pTau217, measured in consecutive samples with LUMIPULSE, for detecting Alzheimer’s disease in a prospective memory clinic setting, along with evaluating its pre-analytical and analytical stability. …”
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Characterizing Continuous Gravitational Waves from Supermassive Black Hole Binaries in Realistic Pulsar Timing Array Data by Emiko C. Gardiner, Bence Bécsy, Luke Zoltan Kelley, Neil J. Cornish

“…We run Markov Chain Monte Carlo searches for CWs in these data sets and compare them to quicker detection statistics including the optimal signal-to-noise ratio (S/N), matched filter detection statistic, and reduced log-likelihood ratio between the signal and noise models calculated at the injected parameters. …”
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Secure Fusion with Labeled Multi-Bernoulli Filter for Multisensor Multitarget Tracking Against False Data Injection Attacks by Yihua Yu, Yuan Liang

“…First, a local estimate is generated from the measurements of each sensor based on the labeled multi-Bernoulli (LMB) filter. Then, a detection method for FDI attacks is derived based on the Kullback–Leibler divergence (KLD) between LMB random finite set (RFS) densities. …”
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Non-Linear Synthetic Time Series Generation for Electroencephalogram Data Using Long Short-Term Memory Models by Bakr Rashid Alqaysi, Manuel Rosa-Zurera, Ali Abdulameer Aldujaili

“…<b>Background/Objectives:</b> The implementation of artificial intelligence-based systems for disease detection using biomedical signals is challenging due to the limited availability of training data. …”
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Diagnosis of Chronic Kidney Disease Using Retinal Imaging and Urine Dipstick Data: Multimodal Deep Learning Approach by Youngmin Bhak, Yu Ho Lee, Joonhyung Kim, Kiwon Lee, Daehwan Lee, Eun Chan Jang, Eunjeong Jang, Christopher Seungkyu Lee, Eun Seok Kang, Sehee Park, Hyun Wook Han, Sang Min Nam

“…ResultseGFR-MMDL outperformed eGFR-RIDL in both the test and external validation sets, with area under the curves of 0.94 versus 0.90 and 0.88 versus 0.77 (P ConclusionsThe MMDL model integrating retinal images and urine dipstick data show significant promise for noninvasive CKD screening, outperforming the retinal image–only model. …”
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Performance Comparison Between Deep Learning Models for Fault Classification in Transmission Lines Using Time Series Data by Nadeem Ahmed Tunio, Mohsin Ali Tunio, Muhammad Amir Raza, Muhammad Faheem, Ashfaque Ahmed Hashmani, Rumaisa Nadeem

“…Leveraging a comprehensive data set encompassing diverse fault scenarios like single‐phase to ground fault (AG), double line to ground fault (ABG), three‐phase fault (ABC) from both simulated and real transmission line data, the study provides a rigorous evaluation of these models’ performance under realistic conditions. …”
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A Fast, Analytic Empirical Model of the Gaia Data Release 3 Astrometric Orbit Catalog Selection Function by Casey Y. Lam, Kareem El-Badry, Joshua D. Simon

“…We use a combination of analytic and empirical prescriptions to construct a function that computes the probability that a binary with a given set of properties would have been published in the Gaia Data Release 3 astrometric orbit catalog. …”
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Mapping landforms of a hilly landscape using machine learning and high-resolution LiDAR topographic data by Netra R. Regmi, Nina D.S. Webb, Jacob I. Walter, Joonghyeok Heo, Nicholas W. Hayman

“…Here we implemented such an objective approach applying a random forest machine learning algorithm to a set of observed landform data and 1m horizontal resolution bare-earth digital elevation model (DEM) developed from airborne light detection and ranging (LiDAR) data to rapidly map various landforms of a hilly landscape. …”
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LMAD-YOLO: A vehicle image detection algorithm for drone aerial photography based on multi-scale feature fusion. by Xue Xing, Fahui Luo, Le Wan, Kang Lu, Yuqi Peng, Xiujuan Tian

“…The model also showed good generalization ability on the VisDrone data set.…”
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Forecasting the Incidence of Mumps Based on the Baidu Index and Environmental Data in Yunnan, China: Deep Learning Model Study by Xin Xiong, Linghui Xiang, Litao Chang, Irene XY Wu, Shuzhen Deng

“…Among the 4 models, model IBE exhibited the best performance, achieving the coefficient of determination of 0.72, with mean absolute error, mean absolute percentage error, and root-mean-square error values of 0.33, 15.9%, and 0.43, respectively, in the test set. ConclusionsOur study developed model IBE to predict the incidence of mumps in Yunnan province, offering a potential tool for early detection of mumps outbreaks. …”
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Comparing Xenium 5K and Visium HD data from identical tissue slide at a pathological perspective by Mengping Long, Taobo Hu, Weixin Wang, Junshun Gao, Nan Wang, Mats Nilsson

“…While sequencing-based Visium HD features a refined bin size of 2 µm and transcriptome wide coverage, Xenium in-situ is a targeted imaging-based detection technology with sub-micron resolution. Herein we use a publicly available lung dataset which contains Visium-HD and Xenium-5K data generated on identical tissue slides to make a bona-fide technical comparison aligned with thorough pathological annotations. …”
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Multiparametric Optimization of Data-Dependent Acquisition Towards More Holistic Bacterial Metabolite Coverage Through Molecular Networking by Adivhaho Khwathisi, Amidou Samie, Asfatou Ndama Traore, Ntakadzeni Edwin Madala

“…Our study reveals that altering collision energy significantly enhances metabolite coverage compared to adjusting the DDA threshold of detection. Furthermore, the ability of global natural product social (GNPS)–based molecular network models to annotate metabolites is greatly influenced by data acquisition settings, particularly affecting MS2 data. …”
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Validated visual features of Multi-Perspective imagery with Explainable Machine learning for detecting rural vacant courtyards in North China by Zehao Qiao, Maojun Wang, Xuexia Zhang, Juanjuan Zhao, Xiaojie Zhang, Tao Liu, Guangzhong Cao

“…Existing methods for detecting VCs in China face significant challenges regarding data availability, spatial scale, resolution, and reliability, which hinder accurate assessment. …”
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DETECTION OF CLAMPING FORCES ON MOUNTING A CONSTRUCTION VIA NEURAL NETWORK FOR THE FINITE-ELEMENT MODEL OF COMPRESSOR-CONDENSING UNIT by S. V. Krasnovskaya, V. V. Naprasnikov

“…It examines the influence of pretension on the strain-stress state of a construction by means of finiteelement modeling. The arrangement of a set of input-output data for neural network is also considered. …”
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