Comparative evaluation of titanium-prepared platelet-rich fibrin with and without herbal extract: A histological study by Gummaluri Shiva Shankar, Gurumoorthy Kaarthikeyan, Damera Trinath Kishore, Boddeda Anusha, Kodem Tejaswi, Lekkala Sivaram

“…Histological analysis of titanium-prepared platelet-rich fibrin (T-PRF) injected with herbal extract, could help assess the appearance (pattern) and structural changes of T-PRF. The aim of the study was to evaluate the appearance of the fibrin network, cellularity, and fibrin border area of T-PRF alone and T-PRF injected with herbal extract. …”
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Transient Stability Assessment of Power Systems Built upon Attention-Based Spatial–Temporal Graph Convolutional Networks by Yu Nan, Weiping Niu, Yong Chang, Zhenzhen Kong, Huichao Zhao

“…However, existing methods fail to adequately exploit the spatiotemporal characteristics in power grid transient data, which constrains the evaluation performance of models. This paper proposes a TSA method built upon an Attention-Based Spatial–Temporal Graph Convolutional Network (ASTGCN) model. …”
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X-FASNet: cross-scale feature-aware with self-attention network for cognitive decline assessment in Alzheimer's disease by Wenhui Chen, Shunwu Xu, Yiran Peng, Yiran Peng, Hong Zhang, Jian Zhang, Huaihao Zheng, Hao Yan, Zhaowen Chen, Zhaowen Chen

“…Current multi-scale neural networks have limited cross-scale feature integration capabilities, which constrain their effectiveness in identifying early neurodegenerative markers. …”
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Multisensory BCI promotes motor recovery via high-order network-mediated interhemispheric integration in chronic stroke by Rongrong Lu, Zhen Pang, Tianhao Gao, Zhijie He, Yiqian Hu, Jie Zhuang, Qin Zhang, Zhengrun Gao

“…Granger causality analysis identified a distinct information flow pattern: signals from the lesioned motor cortex were relayed through transmodal networks to the intact motor cortex, promoting interhemispheric communication. …”
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Non-Rigid Cycle Consistent Bidirectional Network with Transformer for Unsupervised Deformable Functional Magnetic Resonance Imaging Registration by Yingying Wang, Yu Feng, Weiming Zeng

“…We implemented group ICA analysis in brain functional networks after registration. Functional consistency was evaluated on the resulting t-maps. …”
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Artificial Neural Network-Based Structural Analysis of 3D-Printed Polyethylene Terephthalate Glycol Tensile Specimens by Athanasios Manavis, Anastasios Tzotzis, Lazaros Firtikiadis, Panagiotis Kyratsis

“…The measurements were evaluated, and the process was modeled with the Artificial Neural Network (ANN) method, revealing a strong and robust prediction model for the tensile test, with the relative error being below 10%. …”
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Assessment of Scientific Creative-Potential by Near-Infrared Spectroscopy Using Brain-Network-Based Deep-Fuzzy Classifier by Sayantani Ghosh, Amit Konar, Atulya K. Nagar

“…The work presents a novel approach to assess the scientific creative ability of subjects by analyzing their brain connectivity patterns through functional Near-Infrared Spectroscopy (fNIRS) during participation in an analogical reasoning test. …”
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Bibliometric Analysis of microRNA: A Comprehensive Evaluation of Its Contribution to Acute Coronary Syndromes by Gao Y, Li T, Mu X, Ren X, Wang J, Fan J, Zhu H, Wang X

“…Visualization tools mapped collaboration networks, co-citation patterns, and keyword trends.Results: China contributed 60% of publications, followed by the United States (12.86%). …”
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Novel Quanvolutional Neural Network-Based COVID-19 Diagnosis From Raman Spectroscopic Signals of Human Serum by Shivanya Shomir Dutta, Sahil Sandeep, S. Sridevi, Rajiv Mistry, Jonathan Ortega, Gorkem Kar

“…The primary goal of this research is to accurately diagnose COVID-19 by analyzing Raman spectroscopic signals of serum samples with a novel quantum circuit-based Quanvolutional Neural Network (QNN). In this research, although the signals are initially in one dimension (1D), we applied wavelet transforms to convert Raman spectroscopic signals into 2D scaleogram images to capture intricate spectral patterns for efficient classification. …”
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Estimation and evaluation of iron reserves in the eastern area of Eileh1 mine, Razavi Khorasan province by Hamid Esmati Daroneh, Maryam Gholamzadeh

“…The existing drilling network in the region is based on local outcrops, with varying distances and trends. …”
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Networks of care for optimizing Primary Health Care Service Delivery in Ethiopia: Enhancing relational linkages and care coordination. by Gizachew Tadele Tiruneh, Nebreed Fesseha, Temesgen Ayehu, Tamar Chitashvili, Mesele Damte Argaw, Biruhtesfa Bekele Shiferaw, Mikias Teferi, Agumasie Semahegn, Biruk Bogale, Yibeltal Kifle, Hillina Tadesse, Chala Tesfaye, Dessalew Emaway

“…Routine program monitoring data, NoCs process evaluation, and facility service statistics were utilized for this study. …”
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Novel deep neural network architecture fusion to simultaneously predict short-term and long-term energy consumption. by Abrar Ahmed, Safdar Ali, Ali Raza, Ibrar Hussain, Ahmad Bilal, Norma Latif Fitriyani, Yeonghyeon Gu, Muhammad Syafrudin

“…The proposed model is capable of capturing complex temporal and spatial features to predict short-term and long-term energy consumption. CNNs discover patterns in data, LSTM identifies long-term dependencies and sequential patterns and Bi-LSTM identifies complex temporal relations within the data. …”
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Using the antibody-antigen binding interface to train image-based deep neural networks for antibody-epitope classification. by Daniel R Ripoll, Sidhartha Chaudhury, Anders Wallqvist

“…The high level of accuracies reached during these classification tests suggests that the DNN models were able to learn a series of structural patterns shared by Abs belonging to the same class. …”
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Combination of gray level features with deep transfer learning for copra classification using machine learning and neural networks by A. Stephen Sagayaraj, T. Kalavathi Devi

“…These concatenated features were evaluated using various machine learning classifiers and neural networks. …”
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Parallel convolutional neural network and empirical mode decomposition for high accuracy in motor imagery EEG signal classification. by Jaipriya D, Sriharipriya K C

“…However, decoding EEG signals poses significant challenges due to their complexity, dynamic nature, and low signal-to-noise ratio (SNR). Traditional EEG pattern recognition algorithms typically involve two key steps: feature extraction and feature classification, both crucial for accurate operation. …”
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Optimized predictive maintenance for streaming data in industrial IoT networks using deep reinforcement learning and ensemble techniques by K. Varalakshmi, J. Kumar

“…Abstract Predictive maintenance in Industrial IoT (IIoT) networks faces challenges due to dynamic conditions, device heterogeneity, and evolving data patterns. …”
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A Comparative Analysis of Support Vector Machine and K-Nearest Neighbors Models for Network Attack Traffic Detection by Han Zhuoxi

“…This research centers on the use of advanced machine learning methods, particularly Support Vector Machines (SVM) and K-Nearest Neighbors (KNN), to improve the detection of network attack traffic. The UNSW-NB15 dataset, which includes various attack types and normal traffic patterns, is used to evaluate the performance of these two models. …”
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A Multi-Area Software-Defined Vehicular Network Control Plane Deployment Mechanism Oriented to Traffic Prediction by Hao Li, Hongming Li, Yuqing Ji, Ziwei Wang

“…A comprehensive comparison of various machine learning and deep learning algorithms is then conducted to evaluate their efficacy in forecasting SDVN traffic patterns, which is crucial for system efficiency. …”
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A Hybrid CNN-LSTM Model With Attention Mechanism for Improved Intrusion Detection in Wireless IoT Sensor Networks by Pendukeni Phalaagae, Adamu Murtala Zungeru, Abid Yahya, Boyce Sigweni, Selvaraj Rajalakshmi

“…To address computational demands, an enhanced Particle Swarm Optimization (PSO) algorithm is implemented for dynamic feature selection, thereby optimizing the system’s efficiency in high-dimensional data environments characteristic of IoT networks. The proposed model enhances IoT intrusion detection by integrating a novel hybrid CNN-LSTM with an attention mechanism, thereby improving feature extraction and temporal pattern recognition. …”
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Real-time analysis of soccer ball–player interactions using graph convolutional networks for enhanced game insights by Fahad Majeed, Maria Nazir, Kamilla Swart, Marco Agus, Jens Schneider

“…Our method performs exceptionally well on both uni- and multi-directional player movements, uncovering unique patterns in soccer videos. Extensive experimental evaluations demonstrate the effectiveness of our approach, achieving 91% object detection accuracy, 90% tracking and action recognition accuracy, and 92% speed analysis accuracy on benchmark datasets. …”
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