Automatic titration detection method of organic matter content based on machine vision by Bingjie Zhang, Meng Li, Qing Song, Lujian Xu

“…First, by analysing the colour change characteristics during the titration process, machine learning techniques are used to classify the titration speed, and a titration experiment state recognition model is constructed to divide the titration speed into four categories and improve titration efficiency; Second, through a large number of titration experiments to collect relevant data and extract key feature parameters, an efficient titration algorithm based on histogram similarity was designed to accurately identify titration endpoints and improve detection accuracy. …”
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Proposal of a Methodology Based on Using a Wavelet Transform as a Convolution Operation in a Convolutional Neural Network for Feature Extraction Purposes by Nora Isabel Pérez-Quezadas, Héctor Benítez-Pérez, Adrián Durán-Chavesti

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A Model for Automated Business Writing Assessment by Daniil Dmitrievich Zafievsky, Nadezhda Stanislavona Lagutina, Oksana Andreyevna Melnikova, Anatoliy Yurievich Poletaev

“…This study is aimed at building an automated model for business writing assessment, based on 14 rubrics that integrate EFL teacher assessment frameworks and identify expected performance against various criteria (including language, task fulfillment, content knowledge, register, format, and cohesion). We developed algorithms for determining the corresponding numerical features using methods and tools for automatic text analysis. …”
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ACM-YOLOv10: Research on Classroom Learning Behavior Recognition Algorithm Based on Improved YOLOv10 by Beichen Qin, Haoyan Hu, Shaowen Du

“…To effectively integrate the research on learning engagement with teaching practices and accurately assess and analyze students’ learning behavior participation in the classroom to improve teaching quality, this paper proposes an improved YOLOv10 algorithm model, ACM-YOLOv10, targeting the issues of insufficient detection precision, missed detection, false detection, and slow speed of traditional recognition algorithms in classroom behavior detection under multi-scale scenarios and occluded targets. …”
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A Differential Biomarker Based on Recurrence Quantification Analysis of EEG Signal and Genetic Algorithm for Epilepsy Diagnosis by Vanithamani Palanisamy, A Ranichitra, Radhamani Ellapparaj

“…Experimental results showed that using the minimum norm and ε = 0.4 achieved a 100% discrimination rate for seizure detection. The transitivity recurrence feature proved highly effective in classifying normal and epileptic EEGs, making it an excellent biomarker for seizure detection with high diagnostic value.…”
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Composite fault feature extraction for gears based on MCKD-EWT adaptive wavelet threshold noise reduction by Yanchang LV, Jingyue Wang, Chengqiang Zhang, Jianming Ding

“…For the strong noise gear fault vibration signal is relatively weak, and the transmission path is complex and variable, in the case of composite faults, the modulation of different fault characteristics of the frequency, coupling, resulting in the actual acquisition of the fault characteristics are difficult to extract and separate. Aiming at fault feature extraction and separation, an adaptive threshold denoising fault detection method based on Maximum correlated kurtosis deconvolution (MCKD) and Empirical wavelet transform (EWT) is proposed. …”
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An Equipment Identification Method Based on Lightweight CenterNet from Multivariate Features Fusion for Distribution Area by WANG Wenbin, FAN Ruixiang, DENG Zhixiang, WAN Junbiao, PAN Jianbing

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Hybrid Paddy disease classification using optimized statistical feature based transformation technique with explainable AI by M Amudha, Brindha K

“…To enhance predictive performance by transforming features, an improved Owl Search Optimization (IOSO) algorithm is used. …”
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GB-SAR Engineering Interference Suppression Method Integrating Amplitude-Phase Feature Analysis and Robust Regression by Wenting Zhang, Tao Lai, Yuanhui Mo, Haifeng Huang, Qingsong Wang, Zhihua Zhou

“…Current research on addressing engineering interference in GB-SAR deformation monitoring remains preliminary, with existing methods exhibiting limitations in interference pattern coverage, feature extraction, and algorithm robustness. To address these challenges, this article proposes a joint processing method integrating amplitude-phase feature analysis and robust regression. …”
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End‐To‐End Deep Learning Temperature Prediction Algorithms of a Phase Change Materials From Experimental Photos by Mohammad Hassan Ranjbar, Kobra Gharali, Artie Ng

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Identification of Biomarkers Associated with Heart Failure Caused by Idiopathic Dilated Cardiomyopathy Using WGCNA and Machine Learning Algorithms by Mengyi Sun, Linping Li

“…Candidate genes were identified by intersecting the key module genes identified via WGCNA with DEGs and further screened via the support vector machine-recursive feature elimination (SVM-RFE) method and the least absolute shrinkage and selection operator (LASSO) algorithm. …”
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The Role of Artificial Intelligence in Enhancing Diabetic Retinopathy Lesion Detection: A Review by Lakshmi K Santhiya, Sargunam B

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Single-Image Superresolution for RGB Remote Sensing Imagery via Multiscale CNN-Transformer Feature Fusion by Xudong Yao, Haopeng Zhang, Sizhe Wen, Zhenwei Shi, Zhiguo Jiang

“…Single-image superresolution (SISR) of remote sensing images aims to improve image resolution through algorithmic means while restoring rich high-frequency detailed information. …”
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MDIGCNet: Multidirectional Information-Guided Contextual Network for Infrared Small Target Detection by Luping Zhang, Junhai Luo, Yian Huang, Fengyi Wu, Xingye Cui, Zhenming Peng

“…Experimental results on public datasets NUDT-SIRST, IRSTD-1k, and SIRST-Aug demonstrate that our algorithm outperforms other state-of-the-art methods in detection performance.…”
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Multi task detection method for operating status of belt conveyor based on DR-YOLOM by Yongan LI, Tengjie CHEN, Hongwei WANG, Zhihao ZHANG

“…The results show that compared to mainstream single detection algorithms, DR-YOLOM multi task detection algorithm has better comprehensive detection ability, and this algorithm can ensure high target recognition accuracy, segmentation accuracy, and appropriate inference speed with a small number of parameters. …”
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An Improved 2D Pose Estimation Algorithm for Extracting Phenotypic Parameters of Tomato Plants in Complex Backgrounds by Yawen Cheng, Ni Ren, Anqi Hu, Lingli Zhou, Chao Qi, Shuo Zhang, Qian Wu

“…However, segmentation-based methods are labor-intensive due to their requirement for extensive annotation during training, while object detection approaches exhibit limitations in capturing intricate structural features. …”
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Deep Learning-Based Detection and Identification Method for Sports Health Video Dissemination by Yajun Pang

“…To show the high efficiency of our method, we select three main databases for validation, and the results prove that AAEN outperforms by 13.96%, 16.90%, and 15.10% in precision, F1 score, and recall compared to the SOTA in sports health video detection and recognition. Our method also performs better overall in the same type of algorithms.…”
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A Context-Aware Android Malware Detection Approach Using Machine Learning by Mohammed N. AlJarrah, Qussai M. Yaseen, Ahmad M. Mustafa

“…Several combinations of API Calls, permissions, and contextual features were used. These combinations were fed into different machine-learning algorithms to show the significance of using the selected contextual features in detecting Android malware. …”
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Quantum behaved Intelligent Variant of Gravitational Search Algorithm with Deep Neural Networks for Human Activity Recognition by Sonika Jindal, Monika Sachdeva, Alok K. S. Kushwaha

“…The proposed intelligent variant is termed as INQGSA which optimizes the features by using the advantageous attributes of quantum computing (QC) and intelligent gravitational search algorithm (INGSA). …”
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Using multiple drug similarity networks to promote adverse drug event detection by Biswajit Padhi, Ruoqi Liu, Yuedi Yang, Xueqiao Peng, Lang Li, Pengyue Zhang, Ping Zhang

“…While post-market spontaneous reports of ADEs remain a cornerstone of pharmacovigilance, most existing signal detection algorithms rely on substantial accumulated data, limiting their applicability to early ADE detection when reports are scarce. …”
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