Automatic cattle identification system based on color point cloud using hybrid PointNet++ Siamese network by Pyae Phyo Kyaw, Pyke Tin, Masaru Aikawa, Ikuo Kobayashi, Thi Thi Zin

“…The identification framework is built upon a hybrid PointNet ++ Siamese Network trained with a triplet loss function, ensuring the extraction of discriminative features for accurate cattle identification. …”
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A hybrid deep learning-based intrusion detection system for EV and UAV charging stations by Rosebell Paul, Mercy Paul Selvan

“…Deep recurrent neural networks (RNNs) are utilized to capture temporal dependencies in charging station data, allowing for more accurate predictions and adaptive control strategies. …”
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Compensated Neural Network Training Algorithm with Minimized Training Dataset for Modeling the Switching Transients of SiC MOSFETs by Ruwen Wang, Yu Chen, Siyu Tong, Congzhi Cheng, Yong Kang

“…This paper proposes a hybrid model for SiC MOSFET, in which the analytical model is treated as the basis to provide the fundamental waveforms (knowledge-driven), while the neural network (NN) is utilized to fit the high-order and nonlinear features (data-driven). …”
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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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Multiscale Information Fusion Based on Large Model Inspired Bacterial Detection by Zongduo Liu, Yan Huang, Jian Wang, Genji Yuan, Junjie Pang

“…Additionally, a newly designed feature fusion architecture, integrating Transformer modules, is proposed to enable the efficient fusion of global and multi-scale features, overcoming the bottlenecks posed by Feature Pyramid Networks (FPN) structures, which in turn reduces information transmission loss between feature layers. …”
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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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Public Opinion Propagation Prediction Model Based on Dynamic Time-Weighted Rényi Entropy and Graph Neural Network by Qiujuan Tong, Xiaolong Xu, Jianke Zhang, Huawei Xu

“…The model was validated on multiple public opinion datasets, and the results indicate that, compared to baseline methods, it exhibits significant advantages in several evaluation metrics such as AUC, thereby fully demonstrating the effectiveness of the dynamic time-weighted mechanism in capturing the temporal evolution of public opinion dissemination and the dynamic changes in network structure.…”
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Automatic Segmentation and Characterization of Structure Planes From Borehole Images Based on Deep Learning by Shuangyuan Chen, Zengqiang Han, Yi Cheng, Chao Wang

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Optimizing the dynamic treatment regime of outpatient rehabilitation in patients with knee osteoarthritis using reinforcement learning by Sijia Liu, Jiawei Luo, Chengqi He

“…Then, based on the key features screened out, a dynamic treatment recommendation system was constructed by using deep reinforcement learning algorithms, including Deep Deterministic Policy Gradien(DDPG), Deep Q-Network(DQN) and Batch-Constrained Q-learning(BCQ). …”
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SMA-YOLO: An Improved YOLOv8 Algorithm Based on Parameter-Free Attention Mechanism and Multi-Scale Feature Fusion for Small Object Detection in UAV Images by Shenming Qu, Chaoxu Dang, Wangyou Chen, Yanhong Liu

“…Firstly, a parameter-free simple slicing convolution (SSC) module is integrated in the backbone network to slice the feature maps and enhance the features so as to effectively retain the features of small objects. …”
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Hybrid Convolutional Neural Network-Transformer Model for End-to-End Binaural Sound Source Localization in Reverberant Environments by Xinyi Chen, Lijia Zhao, Jie Cui, Hua Li, Xiaodong Wang

“…The end-to-end binaural sound source localization model can implicitly extract features from the original signal waveforms and take full advantage of neural networks. …”
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Developing a Mathematical Model for Scheduling and Determining Success Probability of Research Projects Considering Complex-Fuzzy Networks by Gholamreza Norouzi, Mehdi Heydari, Siamak Noori, Morteza Bagherpour

“…This paper proposes a new method to solve research project scheduling problems (RPSP) containing Fuzzy Graphical Evaluation and Review Technique (FGERT) networks. Through the deliverables of this method, a proper estimation of project completion time (PCT) and success probability can be achieved. …”
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A Deep Learning Model Based on Bidirectional Temporal Convolutional Network (Bi-TCN) for Predicting Employee Attrition by Farhad Mortezapour Shiri, Shingo Yamaguchi, Mohd Anuaruddin Bin Ahmadon

“…In this study, we introduce a deep learning framework based on a Bidirectional Temporal Convolutional Network (Bi-TCN) to predict employee attrition. We conduct extensive experiments on two publicly available datasets, including IBM and Kaggle, comparing our model’s performance against classical machine learning, deep learning models, and state-of-the-art approaches across multiple evaluation metrics. …”
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Evaluation Method for Running State of Electricity Meters Based on Random Matrix Theory and Clustering Algorithm by Yingying CHENG, Jie DU, Quan ZHOU, Jiaming ZHANG, Xiaoyong ZHANG, Gang LI

“…With the expansion of intelligent distribution network and the increasing complexity of power grid structure, the amount of data in power system increases rapidly, and new challenges rise from the checking and monitoring evaluation of power equipment. …”
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Evaluating machine learning-based intrusion detection systems with explainable AI: enhancing transparency and interpretability by Vincent Zibi Mohale, Ibidun Christiana Obagbuwa

“…Machine Learning (ML)-based Intrusion Detection Systems (IDS) are integral to securing modern IoT networks but often suffer from a lack of transparency, functioning as “black boxes” with opaque decision-making processes. …”
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Tropical cyclone track prediction harnessing deep learning algorithms: A comparative study on the Northern Indian Ocean by Sabbir Rahman, M. Fahim Faisal, Prianka Mondal, Md. Mahfuzur Rahman

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Identification of Pyroptosis-Relevant Signature in Tumor Immune Microenvironment and Prognosis in Skin Cutaneous Melanoma Using Network Analysis by Yun Zhu, Dan Han, Hongjue Duan, Qi Rao, Yike Qian, Qiaoyun Chen, Xiao Du, Huanyu Ni, Siliang Wang

“…In addition, a prognostic pyroptosis-related signature (PPRS) model was constructed by performing Cox regression, weighted gene coexpression network analysis (WGCNA), and least absolute shrinkage and selection operator (LASSO) analysis to score SKCM patients. …”
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Determination of sexual dimorphism with CBCT images of the frontal sinus using a predictive formula and an artificial neural network by Julyana de Araújo OLIVEIRA, Natália Rogério BORELLA, Flávia Maria de Moraes RAMOS-PEREZ, Andrea dos Anjos PONTUAL, Maria Alice Andrade CALAZANS, Felipe Alberto Barbosa Simão FERREIRA, Francisco MADEIRO, Maria Luiza dos Anjos PONTUAL

“…Abstract Objective this study aims to evaluate the sexual dimorphism of the morphometric features of the frontal sinus via cone beam computed tomography (CBCT) reconstructions, using a predictive formula and an artificial neural network (ANN). …”
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Neonatal Mortality Surveillance System Evaluation, La-Nkwantanang Municipal Assembly, Greater Accra Region, Ghana, 2015-2019 by Dikena Jackson, Benedict Calys Tagoe, Donne Kofi Ameme, Charles Lwanga Noora, Basil Benduri Kaburi, Alice Sallar Adams, Ernest Kenu

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DDAM-Net: A Difference-Directed Multi-Scale Attention Mechanism Network for Cultivated Land Change Detection by Junbiao Feng, Haikun Yu, Xiaoping Lu, Xiaoran Lv, Junli Zhou

“…To effectively identify changes in agricultural land, we propose a Difference-Directed Multi-scale Attention Mechanism Network (DDAM-Net). Specifically, we use a feature extraction module to effectively extract the cropland’s multi-scale features from dual-temporal images, and we introduce a Difference Enhancement Fusion Module (DEFM) and a Cross-scale Aggregation Module (CAM) to pass and fuse the multi-scale and difference features layer by layer. …”
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