Evaluating machine learning-based intrusion detection systems with explainable AI: enhancing transparency and interpretability by Vincent Zibi Mohale, Ibidun Christiana Obagbuwa

“…Machine Learning (ML)-based Intrusion Detection Systems (IDS) are integral to securing modern IoT networks but often suffer from a lack of transparency, functioning as “black boxes” with opaque decision-making processes. …”
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Smart Fault Detection, Classification, and Localization in Distribution Networks: AI-Driven Approaches and Emerging Technologies by Jianxian Wang, Hazlie Mokhlis, Nurulafiqah Nadzirah Mansor, Hazlee Azil Illias, Agileswari K. Ramasamy, Xingyu Wu, Siqi Wang

“…However, with nations worldwide actively pursuing carbon neutrality and emission peak goals, sustainable energy sources such as solar and wind are increasingly penetrating distribution networks, posing significant challenges to conventional fault detection, classification, and localization techniques due to bidirectional power flows, dynamic fault currents, and rising network complexity. …”
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F-OSFA: A Fog Level Generalizable Solution for Zero-Day DDOS Attacks Detection by Muhammad Rashid Minhas, Qaisar M. Shafi, Shoab Ahmed Khan, Tahir Ahmad, Subhan Ullah, Attaullah Buriro, Muhammad Azfar Yaqub

“…The third component is a signature-based resource usage analyzer to counter attacks mimicking normal traffic. …”
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DNA-Based Nanobiosensor for the Colorimetric Detection of Dengue Virus Serotype 2 Synthetic Target Oligonucleotide by Michael Sandino C. Flores, Evangelyn C. Alocilja, Divina M. Amalin, Mae Joanne B. Aguila, Marynold V. Purificacion, Florinia E. Merca, Ma. Carmina C. Manuel, Mark Pierre S. Dimamay, Ma. Anita M. Bautista, Lilia M. Fernando

“…Being a developing country, most of the high-risk areas in the Philippines are resource-limited and cannot afford equipment for detection and monitoring. …”
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Effect of Cs atoms adsorption on the work function of the LaB6 (100) surface by Huaqing Zheng, Xin Zhang, Jun Hu, Yuhong Xu, Guangjiu Lei, Sanqiu Liu, Heng Li, Zilin Cui, Yiqin Zhu, Xiaolong Li, Xiaoqiao Liu, Shaofei Geng, Xiaochang Chen, Haifeng Liu, Xianqu Wang, Hai Liu, Jun Cheng, Changjian Tang

“…These results provide some reference for the selection of fusion plasma gird materials and the production of hydrogen negative ion sources for neutral beam injection.…”
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DECISION TREE WITH HILL CLIMBING ALGORITHM BASED SPECTRUM HOLE DETECTION IN COGNITIVE RADIO NETWORK by N Suganthi, R Meenakshi, A Sairam, M Parvathi

“…The approach integrates a Decision Tree (DT) algorithm for rapid initial classification of Primary User (PU) activity, followed by a Hill Climbing (HC) optimization algorithm that fine-tunes the detection based on a fitness function. Entropy and throughput metrics are employed as decision conditions at each sensing channel, enhancing uncertainty measurement and maintaining detection robustness under low Signal-to-Noise Ratio (SNR) conditions. …”
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DSFA-SwinNet: A Multi-Scale Attention Fusion Network for Photovoltaic Areas Detection by Shaofu Lin, Yang Yang, Xiliang Liu, Li Tian

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TCE-YOLOv5: Lightweight Automatic Driving Object Detection Algorithm Based on YOLOv5 by Han Wang, Zhenwei Yang, Qiaoshou Liu, Qiang Zhang, Honggang Wang

“…Finally, the EIOU loss function is introduced to measure the overlap between the predicted box and the real box more accurately and improve the detection accuracy. …”
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YOLOv8n-DDSW: an efficient fish target detection network for dense underwater scenes by Jinwang Yi, Wei Han, Fangfei Lai

“…Therefore, the YOLOv8n-DDSW fish target detection algorithm was proposed in this article to resolve the detection difficulties resulting from fish occlusion, deformation and detail loss in complex intensive aquaculture scenarios. (1) The C2f-deformable convolutional network (DCN) module is proposed to take the place of the C2f module in the YOLOv8n backbone to raise the detection accuracy of irregular fish targets. (2) The dual-pooling squeeze-and-excitation (DPSE) attention mechanism is put forward and integrated into the YOLOv8n neck network to reinforce the features of the visible parts of the occluded fish target. (3) Small detection is introduced to make the network more capable of sensing small targets and improving recall. (4) Wise intersection over union (IOU) rather than the original loss function is used for improving the bounding box regression performance of the network. …”
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SHIVA-CMB: a deep-learning-based robust cerebral microbleed segmentation tool trained on multi-source T2*GRE- and susceptibility-weighted MRI by Ami Tsuchida, Martin Goubet, Philippe Boutinaud, Iana Astafeva, Victor Nozais, Pierre-Yves Hervé, Thomas Tourdias, Stéphanie Debette, Marc Joliot

“…An increasing number of automated CMB detection methods being proposed are based on supervised deep learning (DL). …”
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Detecting Vegetation Stress in Mixed Forest Ecosystems Through the Joint Use of Tree‐Water Monitoring and Land Surface Modeling by C. D. Jiménez‐Rodríguez, G. Fabiani, R. Schoppach, K. Mallick, S. J. Schymanski, M. Sulis

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Rice-SVBDete: a detection algorithm for small vascular bundles in rice stem’s cross-sections by Xiaoying Zhu, Weiyu Zhou, Jianguo Li, Jianguo Li, Mingchong Yang, Mingchong Yang, Haiyu Zhou, Haiyu Zhou, Jiada Huang, Jiada Huang, Jiahua Shi, Jun Shen, Guangyao Pang, Lingqiang Wang, Lingqiang Wang, Lingqiang Wang

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Dual Function Radar and Communication Waveform Design Based on Sub-pulse Hybrid Modulation by Yu LIU, Junhao ZHANG, Xue YAO, Xianxiang YU, Guolong CUI

“…To address the low data rate issue in the design of Dual-Function Radar-Communication (DFRC) waveforms with radar detection as the primary function, this paper proposes an information modulation method for multiple sub-pulse structure waveforms called Sub-pulse Hybrid Modulation (SHM). …”
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Finite mixtures of functional graphical models: Uncovering heterogeneous dependencies in high-dimensional data. by Qihai Liu, Kevin H Lee, Hyun Bin Kang

“…In this work, we propose finite mixtures of functional graphical models (MFGM), which detect the heterogeneous subgroups of the population and estimate single graph for each subgroup by considering the correlation structures. …”
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Source Process Estimation for the 2024 Mw 7.1 Hyuganada, Japan, Earthquake and Forward Modeling Using N‐net Ocean Bottom Seismometer Data by R. Shibata, H. Kubo, W. Suzuki, S. Aoi, H. Sekiguchi

“…The N‐net seafloor seismograms of the mainshock with a frequency of ∼0.05 Hz recorded east of the source area were reproduced for several stations using the empirical Green's function approach based on the estimated source process data.…”
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STATISTICAL DATA AND ANALYSIS OF LITERATURE SOURCES ON PATHOPHYSIOLOGICAL MECHANISMS OF THE CROSSTALK BETWEEN ACUTE KIDNEY AND LIVER INJURY IN PRETERM NEWBORNS DURING THE EARLY NEO... by О. Оболонська, Л. Вакуленко

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Multimodal imaging analysis and structure-function correlation in patients exposed to pentosan polysulfate sodium by Sandra Hoyek, Eleni Konstantinou, Francesco Romano, Darren Chen, Celine Chaaya, Magdalena G. Krzystolik, Daniel Hu, Rachel Huckfeldt, Demetrios G. Vavvas, Leo A. Kim, Jason Lee, Elise De, John B. Miller, Nimesh A. Patel

“…Purpose: To study the anatomic and functional retinal changes in patients exposed to pentosan polysulfate (PPS) using multimodal imaging and mesopic microperimetry. …”
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Uncovering functional deterioration in the rhizosphere microbiome associated with post-green revolution wheat cultivars by Monique E. Smith, Vanessa N. Kavamura, David Hughes, Rodrigo Mendes, George Lund, Ian Clark, Tim H. Mauchline

“…Of the 113 functional genes that were differentially abundant between heritage and modern cultivars, 95% were depleted in modern cultivars and 65% of differentially abundant reads best mapped to genes involved in staurosporine biosynthesis (antibiotic product), plant cell wall degradation (microbial mediation of plant root architecture, overwintering energy source for microbes) and sphingolipid metabolism (signal bioactive molecules). …”
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Beach volleyball athlete training trends of Russian-language scientific resources: a systematic review by Sergii Iermakov, Tetiana Yermakova, Krzysztof Wnorowski, Abdelkrim Bensbaa

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Multivariate GWAS analysis reveals loci associated with liver functions in continental African populations. by Chisom Soremekun, Tafadzwa Machipisa, Opeyemi Soremekun, Fraser Pirie, Nashiru Oyekanmi, Ayesha A Motala, Tinashe Chikowore, Segun Fatumo

“…<h4>Conclusions</h4>Using multivariate GWAS method improves the power to detect novel genotype-phenotype associations for liver functions not found with the standard univariate GWAS in the same dataset.…”
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