DDoSNet: Detection and prediction of DDoS attacks from realistic multidimensional dataset in IoT network environment by Goda Srinivasa Rao, P. Santosh Kumar Patra, V.A. Narayana, Avala Raji Reddy, G.N.V. Vibhav Reddy, D. Eshwar

“…After feature selection, an echo-state network (ESN) classifier is employed for detection and prediction. …”
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Detection of Phosphorus in Water by Laser-Induced Breakdown Spectroscopy Based on Liquid-Solid Transformation of Graphite Substrate Combined with PLS-SVR Fusion Quantitative Analys... by Huijie Zhang, Yao Chen, Zongjie Bi, Xiaohua Che, Zhaoshuo Tian

“…To enhance sensitivity in detecting phosphorus in water via laser-induced breakdown spectroscopy (LIBS), this study integrates liquid–solid conversion on graphite substrates with a PLS-SVR fusion algorithm. …”
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Near Real-Time Flood Monitoring Using Multi-Sensor Optical Imagery and Machine Learning by GEE: An Automatic Feature-Based Multi-Class Classification Approach by Hadi Farhadi, Hamid Ebadi, Abbas Kiani, Ali Asgary

“…Land cover classification is then performed using the Random Forest algorithm with the automatically generated training samples. …”
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SAR Images Change Detection Based on Attention Mechanism-Convolutional Wavelet Neural Network by Jiahui E, Lu Wang, Chunhui Zhao, P. Takis Mathiopoulos, Tomoaki Ohtsuki, Fumiyuki Adachi

“…Comparing this algorithm with seven sets of contrast experiments on six real SAR datasets shows that the accuracy of detecting changes in small regions is 2% –9% better than the classical algorithm.…”
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Autoimmune gastritis detection from preprocessed endoscopy images using deep transfer learning and moth flame optimization by Fadiyah M. Almutairi, Sara A. Althubiti, Shabnam Mohamed Aslam, Habib Dhahri, Omar Alhajlah, Nitin Mittal

“…This study aims to develop a DL tool to assist clinicians during the AIG examination and hence better detection accuracy is preferred. The merit of the DL model is demonstrated in the individual deep-features and serially concatenated-features and the experimental outcome of this study provides a detection accuracy of 99.33% when the detection is performed with fused-features and K-Nearest Neighbor classifier. …”
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Ultrafast Laser Beam Profile Characterization in the Front-End of the ELI-NP Laser System Using Image Features and Machine Learning by Tayyab Imran

“…We use centroid tracking to monitor pointing fluctuations, statistical intensity analysis to detect energy instabilities, and Sobel-based edge detection to evaluate beam sharpness and extract structural features from the beam image. …”
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Low-Voltage Alternating Current Series Arc Fault Detection Using Periodic Background Subtraction and Linear Dividing Lines by Xiaofei Zhang, Jinjie Li, Bangzheng Han, Wei Wang, Guofeng Zou

“…To address the challenges in fully expressing the fault features of low-voltage series arcs and the limitations of existing detection algorithms, this paper proposes a novel method combining periodic background subtraction and linear dividing lines for detecting arc faults. …”
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Late-onset leukoencephalopathy with predominant damage to the brain stem, spinal cord and increased lactate (clinical observations) by M. I. Karpova, A. F. Vasilenko, D. G. Korotkova, I. V. Kochetkov, M. V. Shestakova, G. V. Buyanova, Z. Z. Zaripova

“…Genetic screening algorithms are proposed.…”
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Personal Identification Using Embedded Raspberry Pi-Based Face Recognition Systems by Sebastian Pecolt, Andrzej Błażejewski, Tomasz Królikowski, Igor Maciejewski, Kacper Gierula, Sebastian Glowinski

“…This study focuses on the development and validation of a facial recognition system utilizing a Haar cascade classifier and the AdaBoost machine learning algorithm. The system leverages characteristic facial features—distinct, measurable attributes used to identify and differentiate faces within images. …”
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Acoustic emission detection and defect identification method for micro-leakage in natural gas pipeline valves by Lizhen ZHANG, Wen'ao WANG

“…Conclusion The classified processing method for acoustic emission signals, based on acoustic emission technology, feature extraction, PCA, and clustering algorithms, can enhance the accuracy and stability of valve micro-leakage detection. …”
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Multi-convolutional neural network brain image denoising study based on feature distillation learning and dense residual attention by Huimin Qu, Haiyan Xie, Qianying Wang

“…The FDN extracts useful features through two feature distillation blocks, suppresses redundant information, and reduces computational complexity. …”
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LEAF-YOLO: Lightweight Edge-Real-Time Small Object Detection on Aerial Imagery by Van Quang Nghiem, Huy Hoang Nguyen, Minh Son Hoang

“…To address this, we propose LEAF-YOLO, a lightweight and efficient object detection algorithm with two versions: LEAF-YOLO (standard) and LEAF-YOLO-N (nano). …”
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Low Voltage AC Series Arc Fault Detection Method Based on Approximate Entropy for Low Computational Performance Device by Kyoung-Tak Kim, Min-Ho Yoon, Chan-Muk Park, Joung-Hu Park, Sung-Hun Lim

“…The computed Approximate Entropy values for each load and configuration are then used as features in the proposed algorithm. Finally, the algorithm’s performance is evaluated by assessing its series arc fault detection performance and its ability to minimize false detections during normal operation.…”
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Enhanced mask R-CNN for luminaire detection through brightness balancing and distribution-guided optimization in tunnels by Xiaoqiong Qin, Bintao Xu, Chenchen Wang, Lirui Liu, Linfu Xie, Rong Liu, Mingwei Hu, Xiangsheng Chen

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Real defect partial discharge identification method for power cables joints based on integrated PJS-M and GA-SVM algorithm with multi-source fusion by Ling-Xuan Zhang, Yi-Yang Zhou, Shen-Jiong Yao, Jia-Luo Chai, Ying-Jing Chen, Zhou-Sheng Zhang

“…These results demonstrate that the proposed method significantly improves the accuracy of identifying complex real-type defects in 10 kV cable intermediate joints under multi-source feature conditions, providing a reliable diagnostic basis and technical reference for partial discharge detection in industrial applications.…”
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The LED-ID Detection and Recognition Method Based on Visible Light Positioning Using Proximity Method by Canyu Xie, Weipeng Guan, Yuxiang Wu, Liangtao Fang, Ye Cai

“…In most researches about CMOS sensor based VLP, researchers always focus on the high-precision positioning algorithm but ignore that the accuracy of LED-ID detection and recognition plays a more important role in a VLP system. …”
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Integrating near-infrared hyperspectral imaging with machine learning and feature selection: Detecting adulteration of extra-virgin olive oil with lower-grade olive oils and hazeln... by Derick Malavi, Katleen Raes, Sam Van Haute

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A deep dive into artificial intelligence with enhanced optimization-based security breach detection in internet of health things enabled smart city environment by S Jayanthi, Sodagudi Suhasini, N. Sharmili, E. Laxmi Lydia, V. Shwetha, Bibhuti Bhusan Dash, Mrinal Bachute

“…This study presents a Securing Attack Detection through Deep Belief Networks and an Advanced Metaheuristic Optimization Algorithm (SADDBN-AMOA) model in smart city-based IoHT networks. …”
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Personalized machine learning models for noninvasive hypoglycemia detection in people with type 1 diabetes using a smartwatch: Insights into feature importance during waking and sl... by Yasmine M Mohamed, José Mancera, Andreas Brandenberg, Stefan Fischli, Michael M Havranek

“…Machine learning (ML) models were built using a tree-based ensemble algorithm to detect hypoglycemic events registered by CGMS. …”
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Enhanced Grey Wolf Optimization (EGWO) and random forest based mechanism for intrusion detection in IoT networks by Saad Said Alqahtany, Asadullah Shaikh, Ali Alqazzaz

“…Therefore, Enhanced Grey Wolf Optimization (EGWO) for Feature Selection (FS) is implemented. The function of EGWO is to remove unnecessary features from datasets used for intrusion detection. …”
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