Design of C24 fullerene-based sensors for gamma-butyrolactone detection as advanced tools for biomedical and pharmaceutical applications by Bader Huwaimel, Saad Alqarni

“…These results highlight MgC23 as a promising candidate for sensitive and efficient GBL detection in pharmaceutical and forensic applications.…”
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Anomaly Detection Model in Network Security Situational Awareness Based on Machine Learning: Limitation, Techniques, and Future Trends by Li Zhen, Nazhatul Hafizah Kamarudin, Ven Jyn Kok, Faizan Qamar

“…Finally, this study deepens the understanding of the anomaly detection problem in NSSA and provides both theoretical and practical guidance for the development of efficient and scalable anomaly detection systems.…”
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LCD-Net: A Lightweight Remote Sensing Change Detection Network Combining Feature Fusion and Gating Mechanism by Wenyu Liu, Jindong Li, Haoji Wang, Run Tan, Yali Fu, Qichuan Tian

“…While traditional CNN-based methods have improved detection accuracy, they often suffer from high computational complexity and large parameter counts, limiting their use in resource-constrained environments. …”
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A Unified Transformer–BDI Architecture for Financial Fraud Detection: Distributed Knowledge Transfer Across Diverse Datasets by Parul Dubey, Pushkar Dubey, Pitshou N. Bokoro

“…With the growing volume and complexity of digital transactions, the traditional rule-based and shallow learning models often fall short in detecting sophisticated fraud patterns. …”
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Signal Detection in Intelligent Reflecting Surface-Assisted NOMA Network Using LSTM Model: A ML Approach by Haleema Sadia, Hafsa Iqbal, Syed Fawad Hussain, Nasir Saeed

“…In this article, we propose a machine learning (ML)-based approach to perform joint channel estimation and signal detection in an IRS-enabled uplink NOMA network under efficient mitigation of SIC error propagation. …”
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Short and Medium-Term Power Load Anomaly Detection Method Based on Convolutional Neural Network and EL-DCC by Zhipeng Li, Shaobo Liu, Yang Zhang, Zhaowei Wang, Lu Wang, Lu Huang

“…With the increasing complexity of load patterns, it is difficult for traditional methods to meet the requirements of accurate detection. …”
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A new approach of anomaly detection in shopping center surveillance videos for theft prevention based on RLCNN model by Muhammad Sajid, Ali Haider Khan, Kaleem Razzaq Malik, Javed Ali Khan, Ayed Alwadain

“…In this article, we introduce a system for efficient anomaly detection that can function in surveillance networks with a modest level of complexity. …”
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A deep Reinforcement learning-based robust Intrusion Detection System for securing IoMT Healthcare Networks by Jamshed Ali Shaikh, Chengliang Wang, Muhammad Wajeeh Us Sima, Muhammad Arshad, Muhammad Owais, Dina S. M. Hassan, Reem Alkanhel, Mohammed Saleh Ali Muthanna

“…The system integrates Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) networks, and Reinforcement Learning (RL) techniques, namely Deep Q-Network (DQN) and Proximal Policy Optimization (PPO), to enhance the detection of evolving threats. The methodology begins with Enhanced Mutual Information Feature Selection (MIFS) to preprocess the CICIoMT2024 dataset, selecting the most relevant features while reducing noise and computational complexity. …”
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A Deep Learning Approach to Identify Rock Bolts in Complex 3D Point Clouds of Underground Mines Captured Using Mobile Laser Scanners by Dibyayan Patra, Pasindu Ranasinghe, Bikram Banerjee, Simit Raval

“…Addressing these challenges, this paper proposes an approach termed <i>DeepBolt</i>, which employs a novel two-stage deep learning architecture specifically designed for handling severe class imbalance for the automatic and efficient identification of rock bolts in complex 3D point clouds. …”
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Development and evaluation of KNLNTS-cement composites for use as piezoelectric sensors in structural health monitoring applications by Phongthorn Julphunthong, Pongsak Wiwatrojanagul, Pithiwat Tiantong, Theerachai Bongkarn, Rattiyakorn Rianyoi, Ruamporn Potong

“…Detailed investigations of dielectric properties revealed a consistent rise in piezoelectric coefficient (8.40–24.15 pC/N) with increasing KNLNTS content, making these composites suitable for sensitive detection of stress, strain, and cracking in concrete. …”
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LMSOE-Net: lightweight multi-scale small object enhancement network for UAV aerial images by Zhixing Ma, Peidong Luo, Xiaole Shen

“…To tackle this issue, we propose a lightweight multi-scale small object enhancement network (LMSOE-Net) based on the YOLOv8 architecture. To improve both detection performance and model efficiency, we introduce the Efficient Multi Scale Pyramid (EMSP) neck network. …”
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TECHNOLOGICAL INNOVATIONS FOR TREATMENT OF CASINGS by Vera V. Eveleva, Tatyana M. Cherpalova, Elena A. Shipovskaya

“…It was established that minimum effective concentration of solutions of technological aids for treatment of casings corresponds to concentration of the solution with maximum adsorption of the resulting complexes on the surface of the liquid-air phase boundary. …”
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SPL-YOLOv8: A Lightweight Method for Rape Flower Cluster Detection and Counting Based on YOLOv8n by Yue Fang, Chenbo Yang, Jie Li, Jingmin Tu

“…To address these challenges, this study proposes a lightweight rape flower clusters detection model, SPL-YOLOv8. First, the model introduces StarNet as a lightweight backbone network for efficient feature extraction, significantly reducing computational complexity and parameter counts. …”
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Abbreviated protocol for ultrasound duplex scanning of the carotid arteries in the evaluation of preclinical atherosclerosis in order to clarify cardiovascular risk by T. V. Balakhonova, O. A. Pogorelova, M. I. Tripoten, A. I. Ershova, M. V. Koshurnikova, А. N. Rogoza

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SODU2-NET: a novel deep learning-based approach for salient object detection utilizing U-NET by Hyder Abbas, Shen Bing Ren, Muhammad Asim, Syeda Iqra Hassan, Ahmed A. Abd El-Latif

“…The proposed SODU2-NET employs sophisticated background subtraction techniques and utilizes advanced deep learning architectures that can discern relevant foreground information when dealing with complex backgrounds. Firstly, an enriched encoder block with full feature fusion (FFF) with atrous spatial pyramid pooling (ASPP) varying dilation rates to efficiently capture multi-scale contextual information, improving salient object detection in complex backgrounds and reducing the loss of information during down-sampling. …”
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Efficient Design of a Terahertz Metamaterial Dual-Band Absorber Using Multi-Objective Firefly Algorithm Based on a Multi-Cooperative Strategy by Guilin Li, Yan Huang, Yurong Wang, Weiwei Qu, Hu Deng, Liping Shang

“…Terahertz metamaterial dual-band absorbers are used for multi-target detection and high-sensitivity sensing in complex environments by enhancing information that reflects differences in the measured substances. …”
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Lightweight vision transformer model for pine wilt disease detection using aerial RGB image and adversarial data augmentation by Qing Li, Wenhui Chen

“…While remote sensing (RS) offers potential for large-scale PWD detection, existing methods struggle to balance robustness and computational efficiency in complex forest environments. …”
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Emergence of concurrently transmissible mcr-9 and carbapenemase genes in bloodborne colistin-resistant Enterobacter cloacae complex isolated from ICU patients in Kolkata, India by Gourab Halder, Bhaskar Narayan Chaudhury, Priyanka Denny, Mandira Chakraborty, Subhranshu Mandal, Shanta Dutta

“…ABSTRACT Colistin resistance in carbapenem-resistant Enterobacter cloacae complex (CR-ECC) infections has grown expeditiously but detecting the underlying mechanism of resistance is often challenging in clinical settings. …”
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Research progress of genome-wide association study by Duan Zhongqu, Zhu Jun

“…Three possible factors were responsible for the failure of detecting the cause loci. First, the efficiency of detecting the small-effect loci is very low and more small-effect loci are undiscovered. …”
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Ghost Module-Enhanced MTCNN: A Lightweight Cascade Framework for High-Accuracy Face Detection in Edge-Deployable Scenarios by Chen Wang, Fen Liu

“…Face detection in complex environments remains challenging due to trade-offs between accuracy and computational efficiency, particularly for edge devices with limited resources. …”
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