Systematic Approach for Malware Detection in IoT Devices: Enhancing Security and Performance by Vasudeva Pai, B. H. Karthik Pai, G. S. Sudhiksha, Vandya Kamath, K. Varsha, S. Manjunatha

“…Using the IoT23 dataset, which contains a wide range of network traffic patterns from various IoT devices and malware families, the research explores and evaluates multiple machine learning techniques. …”
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SegAN for Recognition of Caries From 2D-Panoramic X-Ray Images by Parvathaneni Naga Srinivasu, Gorli L. Aruna Kumari, D. Jaya Kumari, Paolo Barsocchi, Akash Kumar Bhoi

“…The current study uses a Generative Adversarial Network (GAN) model named SegAN to segment the X-ray samples to recognize the caries. …”
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Metro Station Passenger Volume Prediction Algorithm Based on Improved LSTNet Model by XU Ling, GUAN Jianbo, XU Xiwei, BAN Yong

“…Building upon the LSTNet (long- and short-term time-series network) model, a Bi-LSTM (bidirectional long- and short-term memory) model and the attention mechanism are incorporated to establish an improved LSTNet prediction model. …”
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SHIFA: SBERT-Based Healthcare Information Focused Arabic Question Answering by Rahaf Alruwaithi, Sarah AlHumoud

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AI-Driven Plant Health Assessment: A Comparative Analysis of Inception V3, ResNet-50 and ViT with SHAP for Accurate Disease Identification in Taro by Valeria Maeda-Gutiérrez, Juan José Oropeza-Valdez, Luis C. Reveles-Gómez, Cristian Padron-Manrique, Osbaldo Resendis-Antonio, Luis Octavio Solís-Sánchez, Hector A. Guerrero-Osuna, Carlos Alberto Olvera Olvera

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A hybrid approach for cervical cancer detection: Combining D-CNN, transfer learning, and ensemble models by Abu Hanzala, Tanjila Akter, Md. Sadekur Rahman

“…Specifically, we evaluate the performance of four deep convolutional neural networks architectures: AlexNet, ZfNet, HighwayNet, and LeNet-5, as well as four transfer learning architectures: EfficientNetB0, ResNet50, MobileNetV2, and DenseNet201. …”
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An approach to arousal disorder classification using deformable convolution and adaptive multiscale features in EEG signals by Andia Foroughi, Fardad Farokhi, Fereidoun Nowshiravan Rahatabad, Alireza Kashaninia

“…To our knowledge, this is the first instance of such categorization achieved using a deformable convergence network. Our proposed model, a hierarchical multiscale deformable attention module, excels at detecting complex and abnormal patterns in EEG data. …”
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MangoLeafXNet: An Explainable Deep Learning Model for Accurate Mango Leaf Disease Classification by Md. Eshmam Rayed, Jamin Rahman Jim, Md Juniadul Islam, M. F. Mridha, Md Mohsin Kabir, Md. Jakir Hossen

“…Our proposed model comprises six layers optimized to capture intricate disease patterns, demonstrating superior performance compared with prevalent pre-trained models. …”
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Time-Domain Versus Frequency-Embedded EEG Sequences for Sensorimotor BCI Using 1D-CNN by Simanto Saha, Mathias Baumert, Alistair Mcewan

“…This study proposed a motor imagery (MI) classification pipeline featuring a 1−dimensional convolutional neural network (1D-CNN) with different time/frequency feature representation techniques. …”
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Impact of fractures on convective-mixing characteristics of carbon dioxide in saline aquifers by Qigui TAN, Jian TIAN, Ruichao TIAN, Haoping PENG

“…It also examines CO2 behavior in large-scale fractured saline aquifers with a discrete fracture network. The results show that fractures located in the middle of saline aquifers have a dual, time-dependent effect on CO2 dissolution and diffusion, which becomes more pronounced as fracture width increases. …”
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Prediction of Reservoir Flow Capacity in Sandstone Formations: A Comparative Analysis of Machine Learning Models by Micheal Ayodeji Ogundero, Taiwo Adelakin, Kehinde Orolu, Isaac Femi Johnson, Theophilus Akinfenwa Fashanu, Kingsley Abhulimen

“…Given a large number of input variables that enclose geological and environmental factors, the study set the correlation of these conditions to provide profound analysis and reveal profound patterns within the data. With the following supervised machine learning algorithms: Random Forest, Artificial Neural Network (ANN) and Support Vector Regression (SVR); the study modeled RFC. …”
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Transforming tabular data into images via enhanced spatial relationships for CNN processing by Hameedah A. Alenizy, Jawad Berri

“…Abstract Convolutional neural networks (CNNs), renowned for their efficiency in image analysis, have revolutionized pattern and structure recognition in visual data. …”
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Deep learning based identification of rock minerals from un-processed digital microscopic images of undisturbed broken-surfaces by M.A. Dalhat, Sami A. Osman

“…This study employed convolutional neural networks (CNNs) for the classification of rock minerals based on 3179 RGB-scale original microstructural images of undisturbed broken surfaces. …”
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CGFL: A Robust Federated Learning Approach for Intrusion Detection Systems Based on Data Generation by Shu Feng, Luhan Gao, Leyi Shi

“…The implementation of comprehensive security measures is a critical factor in the rapid growth of industrial control networks. Federated Learning has emerged as a viable solution for safeguarding privacy in machine learning. …”
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Combining Circular and Gauss-Markov Mobility Models for FANET Enhancement  by Suhad Faisal Behadili, Alyaa Safaa Abdulhameed

“…To achieve this realism and improve network performance metrics of the network, multiple Mobility Models (MMs) can be integrated, allowing UAVs to exhibit complex movement patterns that reflect real-world dynamics. …”
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Clinical and brain functional correlates of instrumental rigidity measurement in Parkinson’s disease by Yoshikazu Nakano, Shigeki Hirano, Mitsuyoshi Tamura, Yume Koizumi, Yoshihisa Kitayama, Michiko Izumi, Masahide Suzuki, Kosuke Yamagishi, Yutaro Suzuki, Shinobu Ikeda, Ayaka Arase, Tatsuya Yamamoto, Yoshitaka Yamanaka, Atsuhiko Sugiyama, Kazumoto Shibuya, Takuro Horikoshi, Takashi Uno, David Eidelberg, Satoshi Kuwabara

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Raman spectroscopy and bioinformatics-based identification of key genes and pathways capable of distinguishing between diffuse large B cell lymphoma and chronic lymphocytic leukemi... by Haoyue Liang, Haoyue Liang, Zhijie Cao, Zhijie Cao, Yansong Ren, Yansong Ren, Yihan Li, Yihan Li, Haoyu Wang, Haoyu Wang, Fanfan Sun, Fanfan Sun, Mei Xue, Guoqing Zhu, Guoqing Zhu, Yuan Zhou, Yuan Zhou

“…PPI network analyses and the evaluation of clustered network modules indicated the top 10 up- and down-regulated genes involved in disease onset and development. …”
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Qualitative changes in clinical records after implementation of pharmacist-led antimicrobial stewardship program: a text mining analysis by Keisuke Sawada, Shuji Kono, Ryo Inose, Yuichi Muraki

“…Using Python-based text mining with standardized technical terms and compound word extraction, we performed morphological analysis, co-occurrence network analysis, and hierarchical clustering to evaluate documentation patterns before and after ASP implementation in April 2018. …”
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Federated learning-enhanced generative models for non-intrusive load monitoring in smart homes by Yuefeng Lu, Shijin Xu, Yadong Liu, Xiuchen Jiang

“…In our method, each client trains its own generative neural network to estimate load power, while a discriminator network evaluates these estimates. …”
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An Investigation into the Utilisation of CNN with LSTM for Video Deepfake Detection by Sarah Tipper, Hany F. Atlam, Harjinder Singh Lallie

“…The integration of Convolutional Neural Network (CNN) with Long Short-Term Memory (LSTM) has proven to be a promising approach for improving video deepfake detection, achieving near-perfect accuracy. …”
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