Studying the influence of correction codes on coherent reception of M-PSK signals in the presence of noise and harmonic interference by V. D. Nguyen

“…One of the important requirements for the quality of data transmission is the system error tolerance. There are different ways of improving the quality of information transmission. …”
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StaEn-IDS: An Explainable Stacking Ensemble Deep Neural Network-Based Intrusion Detection System for IoT by Monika Vishwakarma, Nishtha Kesswani

“…With millions of connected devices from different manufacturers using various protocols and IoT applications, ensuring IoT security is challenging. …”
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Combustion Field Prediction and Diagnosis via Spatiotemporal Discrete U-ConvLSTM Model by Xiaodong Huang, Xiaojian Hao, Baowu Pan, Shaogang Chen, Shenxiang Feng, Pan Pei

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Ultra-short-term Multi-region Power Load Forecasting Based on Spearman-GCN-GRU Model by Junying WU, Xin LU, Hong LIU, Bin ZHANG, Shouliang CHAI, Yunchun LIU, Jianan WANG

“…Firstly, the Spearman correlation coefficient is used to analyze the spatial-temporal correlation of power load in different regions and construct the Spearman adjacency matrix. …”
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3D densely connected CNN with multi-scale receptive fields and hybrid loss for brain tumor segmentation by Fatemehzahra Adib, Maryam Amirmazlaghani, Mohammad Rahmati

“…This paper presents a 3D convolutional neural network (CNN) model to automatically segment brain tumors from MRI scans. …”
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A multi-dimensional data-driven ship roll prediction model based on VMD-PCA and IDBO-TCN-BiGRU-Attention by Huifeng Wang, Jianchuan Yin, Jianchuan Yin, Nini Wang, Lijun Wang, Lijun Wang

“…This model integrates data decomposition, dimensionality reduction, deep learning, and optimization techniques.MethodsThe model uses the variational mode decomposition (VMD) method to break down the ship’s roll motion data into components at different scales. This improves the smoothness of the data. …”
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Short-Term Prediction of Ship Heave Motion Using a PSO-Optimized CNN-LSTM Model by Guowei Li, Gang Tang, Jingyu Zhang, Qun Sun, Xiangjun Liu

“…The paper begins by establishing the ship heave motion model based on the P–M spectrum and slice theory, simulating the ship heave motion curve under different sea conditions on MATLAB. This simulation provides crucial data for the subsequent prediction model. …”
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Deep learning-based underwater metal object detection using input image data and corrosion protection of mild steel used in underwater study: A case study: Part A: Deep learning-ba... by Thankappan Sasilatha, Doss Hebciba Mary Suvakeen Amala, Rajendran Susai Santhammal, Časlav Lačnjevac, Gurmeet Singh

“…And also we compare the performance result by given the input images in different validation level. In first input image is initially preprocessed and that images is given to the KFCM-Segmentation. …”
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A Novel Electrical Load Forecasting Model for Extreme Weather Events Based on Improved Gated Spiking Neural P Systems and Frequency Enhanced Channel Attention Mechanism by Yuanshuo Guo, Jun Wang, Yan Zhong, Tao Wang, Zeyuan Sui

“…First, optimized variational mode decomposition (VMD) is used to decompose the load series and the sub-sequences are combined with relevant features, to form the different input sequences of the prediction model. …”
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Short-term Wind Power Forecasting Based on BWO‒VMD and TCN‒BiGRU by LU Jing, ZHANG Yanru, WANG Rui

“…In addition, experiments are conducted not only on the main dataset but also extended to January and August data, which represent seasonal differences, for generalization to verify the re-liability and broad applicability of the model. …”
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Detection of Apple Leaf Diseases using Faster R-CNN by Yunus Özen, Melike Sardoğan, Adem Tuncer

“…Leaf images were obtained from different apple orchards for two years. Inour observations, it was determined that apple trees of Yalova had black spot(venturia inaequalis) disease. …”
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Detection of Mild Moldy-Core Disease in Apples by Fusing Acoustic-Vibration Signals and Visible-Near-Infrared Transmission Spectroscopy by GU Jiahui, LAI Lisi, WANG Kai, ZHANG Hui

“…For the near-infrared spectral signals, the impacts of different preprocessing and feature extraction methods on modeling outcomes were analyzed to select the spectral feature bands. …”
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A Novel Optimization Approach for Revolutionizing Architectural Design in Chinese Cultural Heritage by Xueyong Li, Xiaoqing Yang

“…Using this approach, machine learning models may be taught to see patterns, fix errors, and make wise predictions under different conditions.   Doi: 10.28991/HIJ-2025-06-01-011 Full Text: PDF…”
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Bringing Intelligence to the Edge for Structural Health Monitoring: The Case Study of the Z24 Bridge by Ali Dabbous, Riccardo Berta, Matteo Fresta, Hadi Ballout, Luca Lazzaroni, Francesco Bellotti

“…To this end, we study the application of two convolutional neural network architectures that have emerged in the literature for efficient feature extraction from time series, namely WaveNet and MINImally RandOm Convolutional KErnel Transform (MiniRocket). …”
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Research on rock fracture evolution prediction model based on Adam-ConvLSTM and transfer learning by Runze Liu, Ziwei Wang, Yanbo Zhang, Xulong Yao, Shaohong Yan, Zhiyuan Chen, Shuai Wang, Hua Li, Qi Wang

“…Considering the spatiotemporal correlations among different rock fractures, one dataset was used to train the Adam-ConvLSTM model, yielding an initial model that accurately predicts fracture propagation for a single rock dataset. …”
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Monitoring and Analyzing Driver Physiological States Based on Automotive Electronic Identification and Multimodal Biometric Recognition Methods by Shengpei Zhou, Nanfeng Zhang, Qin Duan, Xiaosong Liu, Jinchao Xiao, Li Wang, Jingfeng Yang

“…Furthermore, the results emphasize the importance of personalizing adjustments based on individual driver differences for more effective monitoring.…”
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Extraction of typical operating scenarios of new power system based on deep time series aggregation by Zhaoyang Qu, Zhenming Zhang, Nan Qu, Yuguang Zhou, Yang Li, Tao Jiang, Min Li, Chao Long

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Short-Term Wind Speed Forecasting With Deep Learning by Zeynep Mine Alçin, Fatih Karaaslan, Muzaffer Aslan

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Detection and recognition of unsafe behaviors of underground coal miners based on deep learning by GUO Xiaoyuan, ZHU Meiqiang, TIAN Jun, ZHU Beibei

“…The high-resolution feature extraction network effectively extracted human keypoints at different scales, and the HRNet_w48 network, with more feature channels, outperformed HRNet_w32. …”
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Human Similar Activity Recognition Using Millimeter-Wave Radar Based on CNN-BiLSTM and Class Activation Mapping by Xiaochuan Wu, Zengyi Ling, Xin Zhang, Zhanchao Ma, Weibo Deng

“…Based on the data of four similar activities of different people collected by mm-wave radar, the experimental results show that the recognition accuracy of the proposed model reached 94.63%. …”
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