Adaptive Symmetry Self-Matching for 3D Point Cloud Completion of Occluded Tomato Fruits in Complex Canopy Environments by Wenqin Wang, Chengda Lin, Haiyu Shui, Ke Zhang, Ruifang Zhai

“…In order to address the problem of missing point cloud data on fruits in a facility agriculture environment due to complex canopy structure, leaf shading and limited collection viewpoints, the traditional geometric fitting method makes it difficult to restore the real morphology of fruits due to the dependence on data integrity. This study proposes an adaptive symmetry self-matching (ASSM) algorithm. …”
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Support Vector Machine – Recursive Feature Elimination for Feature Selection on Multi-omics Lung Cancer Data by Nuraina Syaza Azman, Azurah A Samah, Ji Tong Lin, Hairudin Abdul Majid, Zuraini Ali Shah, Nies Hui Wen, Chan Weng Howe

“…In this study, the LUSC datasets first undergo data pre-processing, including checking for missing values, normalization, and removing zero variance features. …”
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Comparative assessment of the state of digitalisation in higher education institutions by N. I. Aksenova, O. V. Usacheva, M. K. Chernyakov

“…On the basis of the morphological matrix, the rating of a higher education institution was formed as an integral assessment, taking into account the weight values of its spheres. …”
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Voltage unbalance assessment in a distribution system incorporated with renewable‐based sources and electric vehicles in an uncertain environment by Nandini K. K., Jayalakshmi N. Sabhahit, Vinay Kumar Jadoun

“…The proposed problem is solved using two different optimization methods i.e., a modified version of JAYA and whale optimization algorithm (WOA) using MATLAB software. The modified WOA outperforms the other optimization method and the existing literature in minimizing the % VUF and VRP index in case 2 operation, with values of 1.7 and 8.89 respectively. …”
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LoD2 Building Reconstruction from Stereo Satellite Imagery using Deep Learning and Model-Driven Approach by Rojgar Qarani Ismael, Haval Sadeq

“…The best performance of deep learning algorithms (U-Net, FCN, and Mask R-CNN) for building boundary segmentation was selected and then integrated with model-driven technique for the purpose of accurate geometric building fitting employing digital surface model (DSM) generated by semi global matching. …”
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COMPLEXING IMAGES IN A TWO-CHANNEL OPTICAL-ELECTRONIC SYSTEM AS A METHOD OF REDUCING THE PROBABILITY OF DISAPPOINTING AN AUTOMATIC SURVEILLANCE OF LOW CONTRAST OBJECTS by A. V. Khizhniak

“…The paper discusses the work of the correlation algorithm for automatically tracking objects of interest in a two-channel optical-electronic system in a complex background-target environment and the presence of intentional interference. …”
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Using machine learning to develop a stacking ensemble learning model for the CT radiomics classification of brain metastases by Huai-wen Zhang, Yi-ren Wang, Bo Hu, Bo Song, Zhong-jian Wen, Lei Su, Xiao-man Chen, Xi Wang, Ping Zhou, Xiao-ming Zhong, Hao-wen Pang, You-hua Wang

“…By using various machine-learning algorithms, including random forest, support vector machine, gradient boosting machine, XGBoost, decision tree, artificial neural network, k-nearest neighbors, LightGBM, and CatBoost algorithms, a stacking ensemble model was developed to classify gross tumor volume (GTV), brainstem, and normal brain tissue based on radiomic features. …”
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Dempster Shafer-Empowered Machine Learning-Based Scheme for Reducing Fire Risks in IoT-Enabled Industrial Environments by Jayameena Desikan, Sushil Kumar Singh, A. Jayanthiladevi, Saurabh Singh, Byungun Yoon

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Optimization of Laser-Induced Hybrid Hardening Process Based on Response Surface Methodology and WOA-BP Neural Network by Qunli Zhang, Jianan Ling, Zhijun Chen, Guolong Wu, Zexin Yu, Yangfan Wang, Jun Zhou, Jianhua Yao

“…The laser-induced hybrid hardening process integrates laser quenching and electromagnetic induction heating to overcome traditional heat treatment limitations, enhancing the depth and properties of hardened layers for applications like wind turbine bearings. …”
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METRICS FOR DYNAMIC SCALING OF DATABASE IN CLOUDS by Alexander V. Boichenko, Dmitry K. Rogojin, Dmitry G. Korneev

“…In the article are analyzed different types of metrics and are included the basic metrics that characterize the functioning parameters and database technology, as well as sets the goals of the integral metrics, necessary for the implementation of adaptive algorithms for dynamic scaling databases in the cloud infrastructure. …”
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Analytical Solution of Fractional Oldroyd-B Fluid via Fluctuating Duct by Ying Qing Song, Aamir Farooq, Muhammad Kamran, Sadique Rehman, Muhammad Tamoor, Rewayat Khan, Asfand Fahad, Muhammad Imran Qureshi

“…This investigation focuses on the mixed initial boundary value problem with Caputo fractional derivatives. …”
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NeuroRF FarmSense: IoT-fueled precision agriculture transformed for superior crop care by Tarun Vats, Shrey Mehra, Uday Madan, Amit Chhabra, Akashdeep Sharma, Kunal Chhabra, Sarabjeet Singh, Utkarsh Chauhan

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Research on entity recognition and alignment of APT attack based on Bert and BiLSTM-CRF by Xiuzhang YANG, Guojun PENG, Zichuan LI, Yangqi LYU, Side LIU, Chenguang LI

“…Methods: An automatic extraction method of APT attack knowledge that integrates entity recognition and entity alignment is designed. …”
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Research on entity recognition and alignment of APT attack based on Bert and BiLSTM-CRF by Xiuzhang YANG, Guojun PENG, Zichuan LI, Yangqi LYU, Side LIU, Chenguang LI

“…Methods: An automatic extraction method of APT attack knowledge that integrates entity recognition and entity alignment is designed. …”
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Automatic Controversy Detection Based on Heterogeneous Signed Attributed Network and Deep Dual-Layer Self-Supervised Community Analysis by Ying Li, Xiao Zhang, Yu Liang, Qianqian Li

“…We introduce a deep dual-layer self-supervised algorithm for community detection and analyze controversy within this network. …”
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Digitized Cursive Handwriting for Determining FMS in Early School-Age Children by Nurul Zainal Fanani, Ika Widiastuti, Khamid, Laszlo T. Koczy

“…The data recording process generated substantial raw datasets. The random forest algorithm, renowned for its effectiveness in analyzing large datasets, was employed for classification. …”
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Graph convolution-based adaptive feature fusion method for MRI brain tumor segmentation by Ye ZHANG, Muqing ZHANG, Xuegang YUAN, Datian NIU

“…To address the issues of insufficient global information capture and inadequate deep semantic information fusion in the U-Net model for MRI brain tumor segmentation,a novel brain tumor segmentation network,ASGU-Net was proposed. The algorithm was based on 3D U-Net,incorporating a graph convolution inference module to capture additional long-range contextual features. …”
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Vase-Life Monitoring System for Cut Flowers Using Deep Learning and Multiple Cameras by Ji Yeong Ham, Yong-Tae Kim, Suong Tuyet Thi Ha, Byung-Chun In

“…Here, we developed a vase-life monitoring system (VMS) to automatically and accurately assess the post-harvest quality and vase life (VL) of cut roses. The VMS integrates camera imaging with the YOLOv8 (You Only Look Once version 8) deep learning algorithm to continuously monitor major physiological parameters including flower opening, fresh weight, water uptake, and gray mold disease incidence. …”
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Development of a machine learning-derived dendritic cell signature for prognostic stratification in lung adenocarcinoma by Fang Zhou, Fang Zhou, Meng Wang, Meng Wang, Zheng Wang, Zheng Wang, Wei Li, Wei Li, Xike Lu, Xike Lu

“…While dendritic cells (DCs) are essential mediators of antitumor immunity, their transcriptional diversity and prognostic value in LUAD remain underexplored.MethodsWe constructed a cellular atlas by integrating single-cell RNA sequencing (scRNA-seq) data from LUAD and normal tissues, emphasizing dendritic cells. …”
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Machine learning-based brain magnetic resonance imaging radiomics for identifying rapid eye movement sleep behavior disorder in Parkinson’s disease patients by Yandong lian, Yibin Xu, Linlin Hu, Yuguo Wei, Zhaoge Wang

“…Additionally, multi-factor logistic regression analysis identified clinical predictors associated with PD-RBD, and these clinical features were integrated with the radiomics signatures to develop predictive models using various machine learning algorithms. …”
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