Applications of Modified Sigmoid Functions to a Class of Starlike Functions by Muhammad Ghaffar Khan, Bakhtiar Ahmad, Gangadharan Murugusundaramoorthy, Ronnason Chinram, Wali Khan Mashwani

“…Due to its various uses in physics, engineering, and computer science, we discuss several geometric properties like necessary and sufficient conditions in the form of convolutions for functions to be in the special class SSG∗ earlier introduced by Goel and Kumar and obtaining third-order Hankel determinant for this class using modified sigmoid functions. …”
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Cross-Domain Carotid Artery Segmentation Using Folding Fan ResNet and Quadratic Mapping Loss by Zhaozheng Chen, Zhiyin Liu, Bernard Chiu

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MOD3NN: A Framework for Automatic Signal Modulation Detection Using 3D CNN by Vishal Perekadan, Chaity Banerjee, Tathagata Mukherjee, Eduardo Pasiliao, Hovannes Kulhandjian, Michel Kulhandjian

“…Raw I/Q signal data exhibits a special “helical” structure that can be exploited with three-dimensional convolutions (3D convolutions) to learn spatio-temporal features from the signal for the problem of modulation recognition. …”
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Deep Learning Based on Facial Expression Recognition from Images to Videos by Deng Rui

“…Employing a combination of literature review and experimental analysis, this study evaluates existing facial expression recognition algorithms. Special attention is given to advanced models based on Convolutional Neural Networks (CNNs), with a detailed comparison of their architectures and characteristics, analyzing their performance under various conditions. …”
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BeatProfiler: Multimodal In Vitro Analysis of Cardiac Function Enables Machine Learning Classification of Diseases and Drugs by Youngbin Kim, Kunlun Wang, Roberta I. Lock, Trevor R. Nash, Sharon Fleischer, Bryan Z. Wang, Barry M. Fine, Gordana Vunjak-Novakovic

“…We further apply Grad-CAM on our convolution-based models to identify signature regions of perturbations by these drugs in calcium signals. …”
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Digital mapping of soil electrical conductivity for paddy field by The Anh Anh, Luu Trong Hieu, Chi Ngon Nguyen

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An interpretable approach for trustworthy intrusion detection systems against evasion samples by Ngoc Tai Nguyen, Hien Do Hoang, The Duy Phan, Van-Hau Pham

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Super-Resolution Reconstruction Method of Face Image Based on Attention Mechanism by Chenglin Yu, Hailong Pei

“…In recent years, convolutional neural network in Single image super-resolution field show good results. …”
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Neural network-based symmetric encryption algorithm with encrypted traffic protocol identification by Jiakai Hao, Ming Jin, Yuting Li, Yuxin Yang

“…We investigate protocol identification for encrypted traffic data, proposing a novel scheme that integrates temporal and spatial features. Special emphasis is placed on the performance of algorithms within both symmetric and asymmetric frameworks. …”
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An Analytical Study of Creeping Flow of a Second-Order Fluid through a Small Diameter Leaky Tube with Linearly Diminishing Absorption by Zarqa Bano, Abdul Majeed Siddiqui, Kaleemullah Bhatti

“…Variation in flow variables with linear absorption parameter is analysed in detail. The special case of uniform absorption in creeping motion of second-order fluid is presented in a separate section. …”
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Digital mapping of soil electrical conductivity for paddy field by The Anh Anh, Luu Trong Hieu, Chi Ngon Nguyen

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An interpretable approach for trustworthy intrusion detection systems against evasion samples by Ngoc Tai Nguyen, Hien Do Hoang, The Duy Phan, Van-Hau Pham

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Machine Learning and Deep Learning-Based Atmospheric Duct Interference Detection and Mitigation in TD-LTE Networks by Rasendram Muralitharan, Upul Jayasinghe, Roshan G. Ragel, Gyu Myoung Lee

“…Additionally, we propose optimizing special subframe configurations in TD-LTE networks using machine learning-based methods to effectively reduce ADI.…”
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Optimising energy distribution and detecting vulnerabilities in networks using artificial intelligence by D. Koshkin, O. Sadovoy, A. Rudenko, V. Sokolik

“…The application of machine learning algorithms, such as convolutional and recurrent neural networks, significantly improved load forecasting accuracy and adaptability to changing network conditions. …”
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Comment on S Memon, et al. (J Pak Med Assoc. 74: 1163-1166, June 2024) Osmolar gap in hyponatraemia: An exploratory study by Muhammad Ramish Irfan

“…Tonicity inparticular requires special consideration as it denotes behaviourof solutions, relative to each other, separated by a semipermeablemembrane. …”
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A security data detection and management method in digital library network based on deep learning by Diyin Zhu, Yihang Wei, Jiali Cai, Jingwen Wang, Zhongshan Chen

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Volleyball technical action recognition based on CNN-LSTM by Zhigang Zhang, Yong Tian, Jinchong Qi

“…In response to the accuracy and efficiency issues of traditional camera technology in the special environment of volleyball sports, this study first uses millimeter wave radar to collect point cloud spatial data of athletes, and then extracts human spatial features from the data through convolutional neural networks to raise the resolution and accuracy of the data. …”
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YOLO-GML: An object edge enhancement detection model for UAV aerial images in complex environments. by Zhihao Zheng, Jianguang Zhao, Jingjing Fan

“…Finally, we propose a Lightweight layered Shared Convolutional BN(LLSCB) Detection Head based on LSCD, so that the detection heads share the convolutional layer, and the BN is calculated independently, which improves the detection accuracy and reduces the number of parameters. …”
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HUMAN EMOTION RECOGNITION SYSTEM USING DEEP LEARNING ALGORITHMS by Kateryna Yuvchenko, Valentyn Yesilevskyi, Olena Sereda

“…The work examines emotions as a special type of mental processes that express a person’s experience of his attitude to the surrounding world and himself. …”
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Review of Research on Trajectory Prediction of Road Pedestrian Behavior by YANG Zhiyong, GUO Jieru, GUO Zihang, ZHANG Ruixiang, ZHOU Yu

“…Based on these data, this paper systematically reviews both physics-based and data-driven prediction approaches, with a focus on the development of statistical models, deep learning, and reinforcement learning models. Special emphasis is placed on deep learning methods, categorized by network architecture into sequential models, convolutional neural networks, graph convolutional networks,  generative adversarial networks, etc. …”
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