Detection of VOCs and Biogenic Amines Through Luminescent Zn–Salen Complex-Tethered Pyrenyl Arms by Roberta Puglisi, Caterina Testa, Sara Scuderi, Valentina Greco, Giuseppe Trusso Sfrazzetto, Manuel Petroselli, Andrea Pappalardo

“…Biogenic amines, resulting from the natural decarboxylation of amino acids, are released into the environment from both natural and industrial sources. Several methods have been developed so far to detect amines in the environment. …”
Get full text

VRU-YOLO: A Small Object Detection Algorithm for Vulnerable Road Users in Complex Scenes by Yunxiang Liu, Yuqing Shi

“…Accurate detection of vulnerable road users (VRUs) is critical for enhancing traffic safety and advancing autonomous driving systems. …”
Get full text

Identification and functional analysis of novel precursor genes in cyclic peptide biosynthesis in Pseudostellaria heterophylla by Jiao Xu, Wei Zheng, Xiaohong Ou, Hua He, Changgui Yang, Lanping Guo, Chenghong Xiao, Weike Jiang, Guoping Shu, Tao Zhou

Get full text

Brain tumor detection through image fusion using whale optimization and edge preserving filter by Bhattiprolu Nagasirisha, Venkatesh Munagala, Ramakrishna Reddy Eamani, Mocherla Venkata Srikanth, Asileti Suneel Kumar, Varre Venkata Kanaka Durga Prasad

Get full text

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. …”
Get full text

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). …”
Get full text

A fuzzy method for improving the functionality of search engines based on user's web interactions by Farzaneh Kabirbeyk, Ali Harounabadi, Mostafa Sabzekar

Get full text

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. …”
Get full text

Asynchronous bearing only tracking management approach in distributed multi-function integrated sensors by ZHANG Wei, YANG Qiu, LI Hao

“…The distributed multi-function system requires only one integrated sensor to switch to electronic support measure (ESM) mode within each tracking cycle to update the angle measurement information of target radiation source, while the other integrated sensors still work in the original planned mode and task. …”
Get full text

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

Get full text

Relationships between vegetation indices and surface reflectance: Implications for detecting and monitoring sandification in arid regions by Yifan Yue, Wenzhi Zhao, Rentao Liu

Get full text

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. …”
Get full text

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. …”
Get full text

DSFA-SwinNet: A Multi-Scale Attention Fusion Network for Photovoltaic Areas Detection by Shaofu Lin, Yang Yang, Xiliang Liu, Li Tian

Get full text

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. …”
Get full text

Acoustic Emission as a Method for Analyzing Changes and Detecting Damage in Composite Materials During Loading by Katarzyna PANASIUK, Krzysztof DUDZIK, Grzegorz HAJDUKIEWICZ

“…The signal obtained from the sensor was then further processed and used to draw up diagrams of the AE hits, amplitude, root mean square of the AE source signal (RMS) and duration in the function of time. …”
Get full text

LMGD: Log-Metric Combined Microservice Anomaly Detection Through Graph-Based Deep Learning by Xu Liu, Yuewen Liu, Miaomiao Wei, Peng Xu

“…Therefore, there is an urgent need for fast and accurate anomaly detection capabilities. However, the existing microservice anomaly detection methods do not pay attention to the multi-source data of the microservice system and thus have low accuracy. …”
Get full text

Evaluation of a coastal acoustic buoy for cetacean detections, bearing accuracy and exclusion zone monitoring by Kaitlin J. Palmer, Sam Tabbutt, Douglas Gillespie, Jesse Turner, Paul King, Dominic Tollit, Jessica Thompson, Jason Wood

“…Field trials indicated maximum detection ranges from 4–7.3 km depending on source and ambient noise levels. …”
Get full text

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. …”
Get full text

FCMI-YOLO: An efficient deep learning-based algorithm for real-time fire detection on edge devices. by Junjie Lu, Yuchen Zheng, Liwei Guan, Bing Lin, Wenzao Shi, Junyan Zhang, Yunping Wu

“…The rapid development of Internet of Things (IoT) technology and deep learning has propelled the deployment of vision-based fire detection algorithms on edge devices, significantly exacerbating the trade-off between accuracy and inference speed under hardware resource constraints. …”
Get full text