Advancing Spike Sorting Through Gradient‐Based Preprocessing and Nonlinear Reduction With Agglomerative Clustering by Mohammad Amin Lotfi, Fatemeh Zareayan Jahromy, Mohammad Reza Daliri

“…The feature extraction process is centered around capturing inherent variations in spike waveforms, assuming that strong signal correlations enable the extraction of optimal features. …”
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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

“…Here, we present the SHIVA-CMB detector, a 3D Unet-based tool trained on 450 scans taken from seven acquisitions in six different cohort studies that included both T2*- and susceptibility-weighted MRI. …”
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Machine Learning-Based Acoustic Analysis of Stingless Bee (<i>Heterotrigona itama</i>) Alarm Signals During Intruder Events by Ashan Milinda Bandara Ratnayake, Hartini Mohd Yasin, Abdul Ghani Naim, Rahayu Sukmaria Sukri, Norhayati Ahmad, Nurul Hazlina Zaini, Soon Boon Yu, Mohammad Amiruddin Ruslan, Pg Emeroylariffion Abas

“…Among them, Linear Discriminant Analysis (LDA) demonstrated the best performance in improving class separability. The reduced feature set was used to train both Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) classifiers. …”
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Diagnosis of array antennas based on near-field data using Faster R-CNN by Boguang Yang, Yulun Wei, Jixiang Shi, Tao Hong, Liangyu Li, Kai-Da Xu

“…Four different excitation states are trained using the same neural network to compare the effects of excitation faults on feature extraction and classification accuracy. …”
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Physics-Based Noise Modeling and Deep Learning for Denoising Permanently Shadowed Lunar Images by Haiyan Pan, Binbin Chen, Ruyan Zhou

“…Among these images, those of the Moon’s permanently shadowed regions (PSRs) are highly noisy, obscuring the lunar topographic features within these areas. While significant advancements have been made in denoising techniques based on deep learning, the direct acquisition of paired clean and noisy images from the PSRs of the Moon is costly, making dataset acquisition expensive and hindering network training. …”
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NEW APPROACHES TO TRAINING OF ENGINEERING AND ADMINISTRATIVE PERSONNEL by A. Tikhonov, V. Stroev

“…Recommendations are given on the formation of a program for training managerial personnel based on the country's leading universities, which include a full range of engineering and technical specialties, training areas for management, and professionals who have advanced methods of business and communication training.…”
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Identification of quality problems staff vocational training by Vera V. Zhivaeva, Vadim A. Nikovaev, Svetlana N. Parfenova, Elena P. Tuponosova

“…Vocational training (VET) is a very complex and understudied system-object, the functioning of which is the subject to a continuous action of a large number of random (uncertain) factors. …”
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COMMUNICATIVE COMPETENCES FORMATION IN THE TRAINING MANAGERS PROCESS by O. N. Gromova

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It-consultant training in the context of issues of domestic consulting by G. N. Kalyanov

“…The article proposes the concept of the master’s program of training of IT-consultants based on the extension of the relevant sections of the higher professional education of the third generation in the direction of “Applied Informatics”. …”
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“To Have a Winning Way of a Russian Name About Us.” Conversation Between Ambassador Extraordinary and Plenipotentiary M. Konarovsky and Ambassador Extraordinary and Plenipotentiary... by М. A. Konarovsky, A. I. Kuznetsov

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Multiphase Computed Tomography Scan Findings for Artificial Intelligence Training in the Differentiation of Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma Based on In... by Nakarin Inmutto, Suwalee Pojchamarnwiputh, Wittanee Na Chiangmai

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Fostering experiential learning of neurocognitive skills in brain injury tele-rehabilitation: bridging gaps in remote training by integrating scenario-based digital experiences wit... by Fred Loya, Deborah Binder, Nicholas Rodriguez, Bruce Buchanan, Tatjana Novakovic-Agopian, Tatjana Novakovic-Agopian, Anthony J.-W. Chen

“…In this report, we present an innovative system of guided experiential skill learning of goal-directed SRS – one that rationally integrates experiential digital technology designed to practice applying and integrating SRS directly into goal-based functional challenges with therapist-led training to maximize skill learning, transfer, and generalization. …”
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Optimal dose of resistance training to improve handgrip strength in older adults with sarcopenia: a systematic review and Bayesian model-based network meta-analysis by Li Hua-Rui, Huang Shouliang, Yv Zhengze, Jiang Ning, Li Peihua, Zhai Yifei, Peng Fenglin

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pACP-HybDeep: predicting anticancer peptides using binary tree growth based transformer and structural feature encoding with deep-hybrid learning by Shahid, Maqsood Hayat, Wajdi Alghamdi, Shahid Akbar, Ali Raza, Rabiah Abdul Kadir, Mahidur R. Sarker

“…The selected feature vector is subsequently trained using a CNN + RNN-based deep learning model. …”
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Impact on the track from EMU commuter train by A. M. Brzhezovskiy

“…The following features were considered: comparative quantitative values and dependencies on the travel speed and the level of unbalanced accelerations of the experimental indicators of influence on the track of EMU train cars of the category “ЭП”, determined from the results of statistical processing of realizations of dynamic stresses in the throttle of rail sole and lateral forces; vertical and lateral (horizontal) forces transmitted from the wheels to the rail head; stability coefficients of assembled rails and sleepers from the transverse shift along the ballast, as well as the coefficients f of the transition from the axial stresses in the base of the rail to the stresses in the outer edge of the rail sole. …”
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Early detection of disease outbreaks and non-outbreaks using incidence data: A framework using feature-based time series classification and machine learning. by Shan Gao, Amit K Chakraborty, Russell Greiner, Mark A Lewis, Hao Wang

“…To address this gap, we propose a novel framework using a feature-based time series classification (TSC) method to forecast outbreaks and non-outbreaks. …”
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HAD-YOLO: An Accurate and Effective Weed Detection Model Based on Improved YOLOV5 Network by Long Deng, Zhonghua Miao, Xueguan Zhao, Shuo Yang, Yuanyuan Gao, Changyuan Zhai, Chunjiang Zhao

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Self-Supervised Feature Disentanglement for Deepfake Detection by Bo Yan, Pan Liu, Yumin Yang, Yanming Guo

“…To tackle these issues, we propose a self-supervised learning framework based on feature disentanglement, which enhances the generalization ability of detection models by uncovering the intrinsic features of forged content. …”
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annATAC: automatic cell type annotation for scATAC-seq data based on language model by Lingyu Cui, Fang Wang, Hongfei Li, Qiaoming Liu, Murong Zhou, Guohua Wang

“…This method primarily consists of three stages. During the pre-training stage, by training on a vast amount of unlabeled data, the model can learn the interaction relationships between peaks, thus building a preliminary understanding of the data features. …”
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Prediction of Breakdown Voltage of Long Air Gaps Under Switching Impulse Voltage Based on the ISSA-XGBoost Model by Zisheng Zeng, Bin Song, Shaocheng Wu, Yongwen Li, Deyu Nie, Linong Wang

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