Generative AI-Enhanced Cybersecurity Framework for Enterprise Data Privacy Management by Geeta Sandeep Nadella, Santosh Reddy Addula, Akhila Reddy Yadulla, Guna Sekhar Sajja, Mohan Meesala, Mohan Harish Maturi, Karthik Meduri, Hari Gonaygunta

“…At its core, the anomaly detection engine integrates machine learning models, such as Random Forest and Support Vector Machines (SVMs), alongside deep learning techniques like Long Short-Term Memory (LSTM) networks, delivering robust performance across diverse domains. …”
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Wideband Reflectarray Antennas in the Microwave Range by L. М. Liubina, S. V. Ballandovich, G. A. Kostikov, Yu. G. Antonov

“…Measurements were carried out on printed, all-metal, and conformal reflectarrays using an Antast B3-1 near-field scanner and an Agilent N5230A PNA-L vector circuit analyzer. The phase error minimization algorithms were adapted to work in the extended frequency range.Results. …”
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Enhanced Superpixel-Guided ResNet Framework with Optimized Deep-Weighted Averaging-Based Feature Fusion for Lung Cancer Detection in Histopathological Images by Karthikeyan Shanmugam, Harikumar Rajaguru

“…Segmentation and feature selection enhance performance, improving diagnostic accuracy. Future work may explore further optimizations and hybrid models.…”
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Wearable Regionally Trained AI-Enabled Bruxism-Detection System by Anusha Ishtiaq, Jahanzeb Gul, Zia Mohy Ud Din, Azhar Imran, Khalil El Hindi

“…Sleep Bruxism (SB) and Awake Bruxism (AB) can cause severe discomfort, exhaustion, and problems with day-to-day functioning, including poor sleep and bad performance at work. This emphasizes the significance of early identification and treatment of bruxism. …”
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Feature Representation Using Deep Autoencoder for Lung Nodule Image Classification by Keming Mao, Renjie Tang, Xinqi Wang, Weiyi Zhang, Haoxiang Wu

“…This paper focuses on the problem of lung nodule image classification, which plays a key role in lung cancer early diagnosis. In this work, we propose a novel model for lung nodule image feature representation that incorporates both local and global characters. …”
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Satellite imagery, big data, IoT and deep learning techniques for wheat yield prediction in Morocco by Abdelouafi Boukhris, Antari Jilali, Abderrahmane Sadiq

“…We used GRU deep learning model for the best performance, the RMSE and R2 for this model was 0.00036 and 0.99 respectively.The main contribution of our paper is the development of a new system that can predict several crop yields, such as wheat, maize, etc., using IoT, satellite imagery for spatial data and the use of sensors for temporal data. …”
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Frequency Selection Based Separation of Speech Signals with Reduced Computational Time Using Sparse NMF by Yash Vardhan VARSHNEY, Zia Ahmad ABBASI, Musiur Raza ABIDI, Omar FAROOQ

“…It is assumed that the basis vectors of training data of individual speakers had been recorded. …”
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Adenovirus Nanoparticles Displaying RBD Induce a Protective Immune Response Against BA.5 in Mice by Mo C, Wang Z, Liu D, Yang X, Zhang Q, Ye L, Yuan S, Deng S, Lai Z, Huang D, Yang Y, Xu D, Yuan J, Zhu Y, Liu H, Zhou C, Liao X, Li X, Liu W, Zhou R, Tian X

“…Chuncong Mo,1,2,* Zhongfang Wang,1,2,* Donglan Liu,2,* Xiaoyun Yang,2,* Qiong Zhang,2 Lihua Ye,1 Shuai Yuan,3 ShiDong Deng,1 Zhulan Lai,2 Deyi Huang,1 Yujie Yang,1,2 Duo Xu,2 Jinwei Yuan,2 Yuhui Zhu,1 Haoyi Liu,1 Chengxing Zhou,2 Xiaohong Liao,2 Xiao Li,1 Wenkuan Liu,1 Rong Zhou,1,2 Xingui Tian1 1State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, National Clinical Research Center for Respiratory Disease, National Center of Respiratory Medicine, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong Province, 510182, People’s Republic of China; 2Guangzhou National Laboratory, Guangzhou, Guangdong Province, 510005, People’s Republic of China; 3Health and Quarantine Laboratory, Guangzhou Customs District Technology Center, Guangzhou, Guangdong Province, 510700, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xingui Tian, Email xgtian@gzhmu.edu.cn Rong Zhou, Email zhourong@gird.cnIntroduction: Adenovirus (Ad) vectors demonstrated significant efficacy as vaccine vectors during the COVID-19 pandemic. …”
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Estimation of the water content of needles under stress by Erannis jacobsoni Djak. via Sentinel-2 satellite remote sensing by Jiaze Guo, Xiaojun Huang, Xiaojun Huang, Xiaojun Huang, Debao Zhou, Junsheng Zhang, Gang Bao, Gang Bao, Siqin Tong, Siqin Tong, Yuhai Bao, Yuhai Bao, Dashzebeg Ganbat, Dorjsuren Altanchimeg, Davaadorj Enkhnasan, Mungunkhuyag Ariunaa

“…Multiple vegetation indices are screened via recursive feature elimination cross validation (RFECV), and then support vector regression (SVR) and back-propagation neural network (BP) models are used to predict the leaf weight content fresh (LWCF) and leaf weight content dry (LWCD) of needles over a large area. …”
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Chinese Massage (Tuina) Attenuates Knee Osteoarthritis by Modulating Autophagy-Related Cytokines: A Multidisciplinary Methodological Investigation by Wang Z, Zhao C, Li M, Zhang L, Diao J, Wu Y, Yang T, Shi M, Lei Y, Wang Y, Li M, Bian Y, Zhou Y, Xu H

“…A KOA rat model was established via intra-articular injections of L-cysteine–activated papain solution into the right knee. …”
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Formation of Bearings Parts Waviness in Centerless Mortise Grinding on Rigid Supports by Chalyj V., Moroz S., Tkachuk A., Zablotskyi V., Trokhymchuk I., Stelmakh O.

“…The formation of waviness on the working surfaces of bearing parts is associated with fluctuations in the size of the cut layer of metal and changes in the components of the cutting force. …”
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Optimizing encrypted search in the cloud using autoencoder-based query approximation by Mahmoud Mohamed, Khaled Alosman

“…This leads to an inherent tradeoff between privacy and usability that has motivated extensive research on enabling effective encrypted search. Recent work has explored using machine learning models like autoencoders to optimize similarity search under encryption. …”
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Handling data sparsity via item metadata embedding into deep collaborative recommender system by Gopal Behera, Neeta Nain

“…These vectors are concatenated together and fed as input to the second stage of the model. …”
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A Deep Neural Network-Based Approach for Sentiment Analysis of Movie Reviews by Kifayat Ullah, Anwar Rashad, Muzammil Khan, Yazeed Ghadi, Hanan Aljuaid, Zubair Nawaz

“…The model consists of an input layer called the embedding layer, which represents the dataset as a sequence of numbers called vectors, and two consecutive layers of 1D-CNN (one-dimensional convolutional neural network) for extracting features. …”
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A Systematic Analysis of Meteorological Parameters in Predicting Rainfall Events by Muhammad Salman Pathan, Pardhu Nadella, Yasin Ul Haq, Soumini Chaudhury, Jiantao Wu, Avishek Nag, Soumyabrata Dev

“…The study also conducts a thorough assessment of prediction performance of various ML and deep learning (DL) techniques such as Classification and Regression Trees (CART), Support Vector Machine (SVM) and Dense Neural Networks (DNN).The findings show that the models using only the important meteorological features in the dataset perform better than using all the features. …”
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Multiclass leukemia cell classification using hybrid deep learning and machine learning with CNN-based feature extraction by Sazzli Kasim, Sorayya Malek, JunJie Tang, Xue Ning Kiew, Song Cheen, Bryan Liew, Norashikin Saidon, Raja Ezman, Raja Shariff

“…This study presents a novel hybrid methodology that combines pre-trained CNN architectures, including VGG16, InceptionV3, and ResNet50, with advanced classification models such as Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), and the deep learning-based Multi-Layer Perceptron (MLP). …”
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Machine learning algorithms for manufacturing quality assurance: A systematic review of performance metrics and applications by Ashfakul Karim Kausik, Adib Bin Rashid, Ramisha Fariha Baki, Md Mifthahul Jannat Maktum

“…This systematic review analyzes over 300 peer-reviewed studies over the last two decades (mostly analyzing the recent works) to evaluate the effectiveness of widely used ML algorithms—Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), Random Forests (RFs), Decision Trees (DTs), and K-Nearest Neighbors (KNN)—in QA applications. …”
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The Analytical System for Determining the Attitude of Students to the University by Violeta Tretynyk, Mariia Pinda

“…Results. A component model of the system for determining the attitude of students to the university was built. …”
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Bidimensional Increment Entropy for Texture Analysis: Theoretical Validation and Application to Colon Cancer Images by Muqaddas Abid, Muhammad Suzuri Hitam, Rozniza Ali, Hamed Azami, Anne Humeau-Heurtier

“…To further validate our results, we employ a support vector machine model, utilizing multiscale entropy values as feature inputs. …”
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Cepharanthine Inhibits <i>Fusarium solani</i> via Oxidative Stress and CFEM Domain-Containing Protein Targeting by Yuqing Wang, Zenghui Yang, Jingwen Xue, Yitong Wang, Haibo Li, Zhihong Wu, Yizhou Gao

“…Its antifungal effect, however, has not been well studied. In this work, we used machine learning-based virtual screening with Random Forest, Neural Network, and Support Vector Machine models to identify potential inhibitors of <i>Fusarium solani</i>. …”
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