Hybrid Deep Learning Models Using LSTM with Random Forest for Radio Frequency-Based Human Activity Recognition in Line-of-Sight and Non-Line-of-Sight Environments by Niko Andriano, Feddy Setio Pribadi

“…The model was evaluated using channel state information (CSI) and received signal strength indicator (RSSI) features under line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. synthetic minority over-sampling technique (SMOTE) was integrated to balance the dataset and K-fold cross-validation was employed to assess robustness. …”
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Analyzing the Impact of Synthetic Speech on Spoken Language Identification by Khaled lounnas, Abderrahmane Gamgani, Imad Feth-Ennour Aliane

“…The study utilized Multi-Layer Perceptron (MLP), Support Vector Machines (SVM), and Long Short-Term Memory networks (LSTM) to evaluate three distinct scenarios: identifying languages from natural speech, synthetic speech, and a mix of both. …”
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P05 | ENTERIC NERVOUS SYSTEM NEUROPLASTICITY IN COLON OF ANIMAL MODELS OF OBESITY

“…Also, the cholinergic and nitrergic networks appear affected by dysmetabolic conditions. …”
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W-Band Transverse Slotted Frequency Scanning Antenna for 6G Wireless Communication and Space Applications by Hurrem Ozpinar, Sinan Aksimsek, Nurhan Türker Tokan

“…Terahertz (THz) antennas are among the critical components required for enabling the transition to sixth-generation (6G) wireless networks. Although research on THz antennas for 6G communication systems has garnered significant attention, a standardized antenna design has yet to be established. …”
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The role of spectral characteristics of urine in bladder cancer diagnostics by Martina Velísková, Dominika Masarovičová, Iveta Waczulíková, Boris Kollárik, Juraj Jacko, L’uba Hunáková, Milan Zvarík

“…In both EEMs and chromatograms, statistically significant peaks and areas were identified, which were evaluated using various statistical methods and machine learning techniques (logistic regression, OPLS-DA, convolutional neural networks). …”
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Intrusion Detection System for Internet of Medical Things Using GRU with Attention Mechanism based Hybrid Deep Learning Technique by Naveen Saran, Nishtha Kesswani

“…To show how effectively the model performed in noisy environments, we also added noise to the features. Moreover, we used the K-Fold Cross Validation Technique to cross-validate the model's performance on both datasets, ensuring the reliability and applicability of the suggested IDS model for IoMT networks. …”
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Cognitive difference text classification in online knowledge collaboration based on SA-BiLSTM hybrid model by Fengjun Liu, Na Zhao, Guoqing Zhu

“…However, accurate extraction of semantic features and contextual patterns from such texts remains challenging in multi-dimensional discourse contexts. …”
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Characterization and Automated Classification of Underwater Acoustic Environments in the Western Black Sea Using Machine Learning Techniques by Maria Emanuela Mihailov

“…The framework evaluates Convolutional Neural Networks (CNNs), Random Forest, and Support Vector Machines (SVMs) for noise event classification, alongside Gaussian Mixture Models (GMMs) for anomaly detection. …”
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Explainable correlation-based anomaly detection for Industrial Control Systems by Ermiyas Birihanu, Imre Lendák

“…The proposed method utilizes a novel set of input features extracted using the Shapley Additive explanation (SHAP) framework to train and evaluate the MGD model. …”
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Effective Techniques for Handling Missing Values in Thyroid Disease Diagnosis: A Comparative Analysis by Dhekre Saber Saleh, Mohd Shahizan Othman, Wshyar Omar Khudhur, Eman Attallah Aljabarti

“…Five classifiers—Naïve Bayes, linear regression, support vector machines (SVM), LightGBM, and recurrent neural networks (RNN)—were assessed on imputed datasets, with performance evaluated through accuracy, F1 score, and recall. …”
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Application and feasibility analysis of knowledge-based machine learning in predicting fatigue performance of stainless steel by Jia Wang, Dongkui Fan, C.S. Cai

“…The feature parameter constructed through feature engineering has the most significant impact on the number of cycles. …”
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Sparse point annotations for remote sensing image segmentation by Sixian Chan, Wangjie Zhou, Yanjing Lei, Chao Li, Jie Hu, Feng Hong

“…These SAM-generated labels are then used as anchors in the pseudo-generation branch, which dynamically expands supervision signals by evaluating feature-space similarities. This synergistic mechanism allows PENet to progressively refine semantic labels despite sparse supervision. …”
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Continuous prediction of knee joint angle in lower limbs based on sEMG: a method combining an improved ZOA optimizer and attention-enhanced GRU by Jian Lv, Binhao Huang, Ligang Qiang

“…Experimental evaluations across three motion tasks—level walking, stair ascent, and stair descent—demonstrated that the proposed method achieved a minimum root mean square error (RMSE) of 1.31°, with over 50% reduction in feature dimensionality, significantly outperforming Genetic Algorithm (GA), Zebra Optimization Algorithm (ZOA), Liver Cancer Algorithm (LCA), and Pied Kingfisher Optimizer (PKO). …”
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Stress Interferences between Fractures and Fracturing Stages of a Horizontal Well in a Sandy Conglomerate Reservoir in Junggar Basin, Northwest China by Jianmin Li, Binghui Du, Junxiu Ma, Ruining Liu, Can Shi, Botao Lin

“…The sandy conglomerate reservoirs in the Mahu oilfield located in the Junggar Basin of Northwest China are featured by a significant horizontal stress difference between two directions, making formations easy to form double-wing fractures upon hydraulic fracturing instead of creating a complex fracture network. …”
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Detection of Q235 Mild Steel Resistance Spot Welding Defects Based on EMD-SVM by Yuxin Wu, Xiangdong Gao, Dongfang Zhang, Perry Gao

“…This study presents an online quality evaluation and defect classification method for Q235 low-carbon steel welding. …”
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Explainable AI-based suicidal and non-suicidal ideations detection from social media text with enhanced ensemble technique by Daniyal Alghazzawi, Hayat Ullah, Naila Tabassum, Sahar K. Badri, Muhammad Zubair Asghar

“…The prompt identification of sentiments on social networking platforms is crucial for timely intervention serving as a key tactic in suicide prevention efforts. …”
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Robust Anomaly Detection of Multivariate Time Series Data via Adversarial Graph Attention BiGRU by Yajing Xing, Jinbiao Tan, Rui Zhang, Jiafu Wan

“…Hence, this paper proposes a robust multivariate temporal data anomaly detection method based on graph attention for training convolutional neural networks (PGAT-BiGRU-NRA). Firstly, the parallel graph attention (PGAT) mechanism extracts the time-dependent and spatially related features of MTSD to realize the MTSD fusion. …”
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Deep Learning Method for Wetland Segmentation in Unmanned Aerial Vehicle Multispectral Imagery by Pakezhamu Nuradili, Ji Zhou, Guiyun Zhou, Farid Melgani

“…Our approach, involving meticulous image preprocessing, customized network architecture, and iterative training procedures, aims to refine wetland boundary delineation. …”
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Hybrid Model for Novel Attack Detection Using a Cluster-Based Machine Learning Classification Approach for the Internet of Things (IoT) by Naveed Ahmed, Md Asri Ngadi, Abdulaleem Ali Almazroi, Nouf Atiahallah Alghanmi

“…The hybrid CBC approach uses optimized k-means clustering to find commonalities across different abnormalities, intending to quickly identify and classify unknown harmful attacks in a varied IoT network. The technique is fine-tuned for eight-class and two-class classifications, supporting different attacks using the IoTCIC2023 dataset and SelectKBest feature selection. …”
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Comparison of RNN and LSTM Classifiers for Sentiment Analysis of Airline Tweets by Rogaia Yousif Ahmed, Noon Fahmi Yuosif, Sarmed Awad Ahmed, Al-Baraa Ali Mohammed

“…This study examines the application of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) models for sentiment analysis of airline-related tweets, focusing on customer feedback directed at U.S. airlines on the X platform (formerly Twitter). …”
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