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

“…In the challenging portion of the dataset, our models demonstrated a 12% improvement in accuracy. …”
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Bioethical management of patients with epilepsy: sex and age-related aspects by E. P. Mikhalovska-Karlova

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Graphical Notation for Document Database Modeling by M. V. Smirnov, R. S. Tolmasov

“…However, the development of information technologies has led to an increase in the popularity of non-relational data models, primarily the document model. One of the problems of its application in practice is the lack of suitable tools that allow performing graphical modeling of the database, taking into account the features of the document model, at the stage of logical design. …”
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An Artificial Intelligence-Based Approach With Photoplethysmogram and Heart Rate Variability for Sleep Bruxism Diagnosis by Omer Eris, Mehmet Recep Bozkurt, Seval Bulut Eris, Cahit Bilgin

“…We evaluated the performance of the models using six criteria and validated them using leave-one-out (LOO). …”
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Sonar-based object detection for autonomous underwater vehicles in marine environments by Zhen Wang, Zhen Wang, Jianxin Guo, Shanwen Zhang, Yucheng Zhang

“…Specifically, our approach achieves a mean average precision (mAP) of 81.86%, an improvement of 7.85% compared to the best-performing existing model. These results highlight the superior performance of our method in marine environments.…”
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Boundary-Aware Cross-Level Multi-Scale Fusion Network for RGB-D Salient Object Detection by Zhijun Zheng, Yanbin Peng

“…During the decoding stage, a Bidirectional Cross-Level Multi-Scale Module (BCMM) is introduced to effectively integrate cross-level features and perform multi-scale learning. Finally, the output of the BCMM, combined with boundary-aware features, generates saliency prediction maps. …”
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Enhanced Fetal Arrhythmia Classification by Non-Invasive ECG Using Cross Domain Feature and Spatial Differences Windows Information by Gede Angga Pradipta, Putu Desiana Wulaning Ayu, Made Liandana, Dandy Pramana Hostiadi

“…The combination of dimensionality reduction using Mutual Information and oversampling with the Radius-SMOTE method achieved the highest performance, yielding an accuracy of 96.5%, precision of 95.2%, recall of 96.3%, and an F1-measure of 96.2%, while reducing the feature dimensionality to 100. …”
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A Multispectral Feature Selection Method Based on a Dual-Attention Network for the Accurate Estimation of Fractional Vegetation Cover in Winter Wheat by Runzhi Yang, Shanshan Li, Bing Zhang, Quanjun Jiao, Dailiang Peng, Songlin Yang, Ruyi Yu

“…Finally, the selected features were assessed based on their performance in FVC estimation using a CNN model with real data. …”
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Experimental Study on Loosening and Vibration Characteristics of Vibrating Screen Bolts of Combine Harvester by Lulu Yuan, Meiyan Sun, Guangen Yan, Kexin Que, Bangzhui Wang, Sijia Xu, Yi Lian, Zhong Tang

“…To address these issues, this study first established a bolt-tightening mechanical model. Secondly, a finite element simulation of the preload force was performed using Ansys Workbench software (2023R2). …”
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Establishment and characterization of a sigmoid colon cancer organoid with spinal metastasis by Jingyao Chen, Jingyao Chen, Shumin Cheng, Liang Gu, Liang Gu, Zhangsen Huang, Zhangsen Huang, Changhua Zhang, Changhua Zhang, Chunhui Sun, Chunhui Sun, Chunhui Sun, Songyao Chen, Songyao Chen

“…Moreover, we performed drug screening tests to evaluate the effects of chemotherapeutic drugs and targeted drugs.ConclusionThe sigmoid colon cancer organoid with spinal metastases was a favorable preclinical model to explore the clinicopathologic characteristics of colon cancer patients with spinal metastases.…”
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A Spatial and Semantic Alignment Fusion Network for SeaLand Port Segmentation by Bo Zhang, Yaxiong Chen, Weichong Dang, Shengwu Xiong, Xiaoqiang Lu

“…By the collaborative work of four submodules: spatial feature alignment, spatial feature fusion, semantic feature alignment, and semantic feature fusion, the dual-branch network achieves feature alignment and fusion. …”
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18F-FDG PET/CT Semiquantitative and Radiomic Features for Assessing Pathologic Axillary Lymph Node Status in Clinical Stage I–III Breast Cancer Patients: A Systematic Review by Anna Hwang, Sana Rashid, Selina Shi, Ciara Blew, Mark Levine, Ashirbani Saha

“…Two studies developed models using tumour radiomic features with high accuracy for predicting ALN metastases (81.2% and 80%) but scored low on the RQS. …”
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A hybrid approach for intrusion detection in vehicular networks using feature selection and dimensionality reduction with optimized deep learning. by Fayaz Hassan, Zafi Sherhan Syed, Aftab Ahmed Memon, Saad Said Alqahtany, Nadeem Ahmed, Mana Saleh Al Reshan, Yousef Asiri, Asadullah Shaikh

“…It also reduces the model size from 28.09 KB to 20.34 KB thus optimizing the model in terms of both classification performance and model size. …”
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APPLYING TRANSFORMER ARCHITECTURE TO ENHANCE ATTACK DETECTION PERFORMANCE IN INTRUSION DETECTION SYSTEMS by Vu Thi Phuong*, Hoang Thi Hong Ha, Dinh Gia Truong, Tran Thi Yen

“…In this study, we propose a Transformer-based intrusion detection model to enhance attack recognition performance. …”
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Predicting pathological response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer with two step feature selection and ensemble learning by Changshun Qian, Shuxin Yang, Yijing Chen, Ran Ge, Fangmin Shi, Chengnan Liu, Hui Wang, You Guo

“…In the validation cohort, the AUPRC was 0.785, with an accuracy of 0.898, indicating strong model performance. The study further demonstrated that BoostForest achieved superior overall performance compared to Random Forest, Support Vector Machine (SVM), and XGBoost. …”
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A Two-Stage Feature Selection Approach Based on Artificial Bee Colony and Adaptive LASSO in High-Dimensional Data by Efe Precious Onakpojeruo, Nuriye Sancar

“…High-dimensional datasets, where the number of features far exceeds the number of observations, present significant challenges in feature selection and model performance. …”
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Mathematical Modelling of Shear Cutting Process of Grain Oriented Electrical Steels Using Regression Modelling by Alaaddin Toktaş, Nihat Celık

“…The calculated coefficient of determination is close to almost 1.00 i.e., R2 = 0.9896 which means the factors are sufficient to model the response, and the model is obtained with a good prediction performance. …”
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BotCatcher:botnet detection system based on deep learning by Di WU, Binxing FANG, Xiang CUI, Qixu LIU

“…Machine learning technology has wide application in botnet detection.However,with the changes of the forms and command and control mechanisms of botnets,selecting features manually becomes increasingly difficult.To solve this problem,a botnet detection system called BotCatcher based on deep learning was proposed.It automatically extracted features from time and space dimension,and established classifier through multiple neural network constructions.BotCatcher does not depend on any prior knowledge which about the protocol and the topology,and works without manually selecting features.The experimental results show that the proposed model has good performance in botnet detection and has ability to accurately identify botnet traffic .…”
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Optimized small object detection in low resolution infrared images using super resolution and attention based feature fusion. by Weilun Wang, Jian Xu, Ruopeng Zhang

“…However, challenges such as low resolution, high noise, limited texture details, and restricted dynamic range hinder the performance of traditional object detection models. …”
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Enhanced air quality prediction using adaptive residual Bi-LSTM with pyramid dilation and optimal weighted feature selection by R. Sudha, Ajith Damodaran, Gunaselvi Manohar

“…At first, the data for predicting air quality are collected from the relevant data sources. The proposed model introduces a novel methodology for weighted feature selection utilizing an Improved Gannet Optimization Algorithm (IGOA) aimed at enhancing the performance of data classification. …”
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