Automatic vibration fault detection of coal mine explosion-proof electrical equipment based on One-Class Support Vector Machine by ZHENG Tiehua, WANG Fei, ZHAO Gelan, DU Chunhui

“…Experimental results showed that: ① When the number of iterations is 20, the OCSVM algorithm can complete convergence and achieve stability. ② In the electrical equipment signal classification experiment based on OCSVM, the use of the polynomial kernel function accurately classified samples for detection. ③ In the performance analysis of automatic vibration fault detection, the proposed method showed significantly higher accuracy across different sample sizes than infrared thermography and detection methods based on grey wolf optimization and support vector machine. …”
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Formation of a comprehensive rehabilitation program for patients considering the clinical and diagnostic features of the course of vertebral thoracic pain due to degenerative-dystr... by Ye. I. Maramukha

“…To determine the clinical and diagnostic features of the course of thoracic back pain syndrome, to investigate life quality data in patients with degenerative-dystrophic pathology of the thoracic spine (DDPS) depending on the indicators of vertebrodynamics in order to conduct differentiated kinesiotherapy technique. …”
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Leveraging self attention driven gated recurrent unit with crocodile optimization algorithm for cyberattack detection using federated learning framework by Manal Abdullah Alohali, Hatim Dafaalla, Mohammed Baihan, Sultan Alahmari, Achraf Ben Miled, Othman Alrusaini, Ali Alqazzaz, Hanadi Alkhudhayr

“…Initially, the Z-score normalization is utilized to scale and standardize data to improve analysis consistency and accuracy. Furthermore, the feature selection (FS) process uses the crocodile optimization algorithm (COA) model. …”
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AΚtransU-Net: Transformer-Equipped U-Net Model for Improved Actinic Keratosis Detection in Clinical Photography by Panagiotis Derekas, Charalampos Theodoridis, Aristidis Likas, Ioannis Bassukas, Georgios Gaitanis, Athanasia Zampeta, Despina Exadaktylou, Panagiota Spyridonos

“…The model incorporates Transformer blocks to enrich feature representations, which are passed through ConvLSTM modules within the skip connections. …”
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Color-Sensitive Sensor Array Combined with Machine Learning for Non-Destructive Detection of AFB₁ in Corn Silage by Daqian Wan, Haiqing Tian, Lina Guo, Kai Zhao, Yang Yu, Xinglu Zheng, Haijun Li, Jianying Sun

“…Key variables were selected using five feature selection algorithms: Competitive Adaptive Reweighted Sampling (CARS), Principal Component Analysis (PCA), Random Forest (RF), Uninformative Variable Elimination (UVE), and eXtreme Gradient Boosting (XGBoost). …”
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Characteristics, Analysis and Tackling of Terrorism in Uganda by NTEGE Edward

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A Novel Approach to Cognitive Load Measurement in N-Back Tasks Using Wearable Sensors, Empirical Mode Decomposition With Machine Learning, and Explainable AI for Feature Importance by Aakanksha Dayal, Ziaullah Khan, Kiramat Ullah, Hee-Cheol Kim

“…Combining both data types (ECG and Fingertip-PPG data) further improved recall to 94.87% and boosted overall accuracy to 87.50%, marking an improvement of approximately 13%. SHAP analysis identified key features contributing to this performance, revealing key features such as the waveform length of the first Intrinsic Mode Function (IMF) for the ECG signal, the mean of the second IMF for fingertip-PPG, and the waveform length of the second IMF for combined ECG and fingertip-PPG signals. …”
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PyGlaucoMetrics: A Stacked Weight-Based Machine Learning Approach for Glaucoma Detection Using Visual Field Data by Mousa Moradi, Saber Kazeminasab Hashemabad, Daniel M. Vu, Allison R. Soneru, Asahi Fujita, Mengyu Wang, Tobias Elze, Mohammad Eslami, Nazlee Zebardast

“…Permutation importance analysis revealed that the superior temporal sector was the most influential VF feature, with importance scores of 0.08 in Kang’s and 0.04 in HAP2_part1 models. …”
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Modeling the Analysis of the Financial Result of an Entity by Alexandra A. Derbicheva

“…Nevertheless all these approaches do not take into account the special features of a company’s functioning. There is a need for improvement of information base for analysis. …”
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The Problem of Grade Inflation: Measurement and Analysis by Andrei R. Markov, Natalia L. Shagas, Elena V. Merekina, Alexandra A. Moskaleva

“…The article includes qualitative and quantitative analysis of the undergraduate student assessment system features in one of the universities in Russia in order to define presence of grade inflation. …”
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Algorithm for the analysis of kinematic characteristics of running by N. S. Davydova, V. Е. Vasiuk, N. A. Paramonova, М. М. Mezhennaya, D. I. Guseinov

“…Biomechanics of motor actions solves the problems of analysis of external motor events - kinematic and dynamic movement parameters. …”
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Hyperspectral imaging-driven deep learning approach: Asymptomatic stage detection and severity grading of tomato yellow leaf curl disease by Junzhi Chen, Wenshan Zhong, Xuejun Yue, Ziyu Ding, Mengdan Du, Xuantian Li, Biao Chen, Haifeng Li, ZiFu He, Xiaoman She, Yafei Tang

“…This study proposes a spectral-spatial dual-branch residual network (SSDBRN) designed to fully extract and leverage complex features within hyperspectral images, aiming to achieve detection of TYLCD during its asymptomatic stage and classification of disease severity levels. …”
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A novel deep learning-based spider wasp optimization approach for enhancing brain tumor detection and physical therapy prediction by Suleiman Daoud, Ahmad Nasayreh, Khalid M.O. Nahar, Wlla k. Abedalaziz, Salem M. Alayasreh, Hasan Gharaibeh, Ayah Bashkami, Amer Jaradat, Sultan Jarrar, Hammam Al-Hawamdeh, Absalom E. Ezugwu, Raed Abu Zitar, Aseel Smerat, Vaclav Snasel, Laith Abualigah

“…We demonstrate the overall effectiveness of the proposed model by using it to select the optimal features extracted from the Resnet50V2 model for pediatric brain tumor detection. …”
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BlockDroid: detection of Android malware from images using lightweight convolutional neural network models with ensemble learning and blockchain for mobile devices by Emre Şafak, İbrahim Alper Doğru, Necaattin Barışçı, İsmail Atacak

“…Because these methods can automatically extract meaningful features from data and efficiently learn complex relationships, they can achieve better performance in malware detection as well as in solving many other problems. …”
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Hybrid Products for Enhanced and Unified Full and Compact Polarimetric SAR Data Exploitations by Ramin Sabry

“…These products include hybrid feature-based classification and detection maps. Hybrid multichannel ML-based, and phenomenology-based change detection and classification products are also developed and examined. …”
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Forensic Investigation of MP3 Audio Recordings by A. G. Boyarov, I. S. Siparov

“…Special aspects of MP3-recordings technical investigation are addressed. The following features of formation and research of MP3 phonograms are explained: traces of MP3 coding in time and spectral domain, special aspects of MP3-files structure analysis, detection methods of re-coding of MP3-recordings, methods of group identification of MP3-recorders and MP3-codecs.MP3 coding leaves certain traces of its usage. …”
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An IMU-Based Machine Learning System for Container Collision Position Identification by Xin Zhang, Zihan Song, Do-Myung Park, Byung-Kwon Park

“…Statistical analysis with the Friedman test confirmed significant differences in model and feature selection performance. …”
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Enterovirus D68 infection in cotton rats results in systemic inflammation with detectable viremia associated with extracellular vesicle and neurologic disease by Jorge C. G. Blanco, Fatoumata Y. D. Sylla, Sandra Granados, Alessio Noghero, Marina S. Boukhvalova, Adriana E. Kajon

“…We present a model of acute respiratory infection with a clinical isolate of EV-D68 of clade B3 in immunocompetent cotton rats featuring systemic dissemination of the virus. EV-D68 was detected in circulation and organs outside of the respiratory tract with the inflammatory response accompanying dissemination. …”
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Detection of volatile flavor compounds in leaf of Xiangyu pumpkin using headspace solid-phase microextraction-gas chromatography-mass spectrometry by LI Junxing, ZHONG Yujuan, LUO Jianning, HE Xiaoli, GONG Hao, WU Haibin, YAN Shijuan, HUANG Hexun

“…To further research, principal component analysis (PCA) was performed using the volatile compounds from the two samples of Xiangyu and non-Xiangyu pumpkins, and the total accumulative contribution rate of PC₁ and PC₂ accounted for 70.45%, which well reflected the excellent separations of Xiangyu pumpkin and non-Xiangyu pumpkin; four compounds detected in the leaves of Xiangyu pumpkin showing differences, 2-acetyl-1-pyrroline (2-AP), 2-acetylpyrrole, 1-undecanol and methyl salicylate, were identified. …”
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Whole genome uniparental isodisomy detected using single nucleotide polymorphism (SNP) microarray in molar pregnancy: a case report by Onyinye O. Okonkwo, Veronica Ortega, Sheila Kane, Galina Aldrete, Paulina Ramirez, Philip T. Valente, Gopalrao V.N. Velagaleti

“…High-resolution SNP microarray studies detected whole genome uniparental isodisomy. Conclusion We present a case of CHM with homozygous pericentric inversion on chromosome 9 and whole genome uniparental isodisomy. …”
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