MFF: A Deep Learning Model for Multi-Modal Image Fusion Based on Multiple Filters by Yuequn Wang, Zhengwei Li, Jianli Wang, Leqiang Yang, Bo Dong, Hanfu Zhang, Jie Liu

“…The method involving low-frequency feature correlation and high-frequency feature non-correlation was used for image training and fusion purposes. …”
Get full text

Indoor Positioning Systems in Logistics: A Review by Laura Vaccari, Antonio Maria Coruzzolo, Francesco Lolli, Miguel Afonso Sellitto

“…Geometric methods, particularly multilateration, proved to be the most effective for positioning and are supported by advanced filtering techniques like the Extended Kalman Filter and machine learning models such as Convolutional Neural Networks. …”
Get full text

Multi-dimensional feature extraction of EEG signal and its application in stroke classification by Teng Wang, Wenhui Jia, Fenglian Li, Xirui Liu, Xueying Zhang, Fengyun Hu

“…Abstract Feature extraction based on EEG signals and construction of classification models using machine learning methods are key to intelligent assisted diagnosis of brain diseases (such as stroke classification). …”
Get full text

Exploring Process Heterogeneity in Environmental Statistics: Examples and Methodological Advances by Gregor Laaha, Johannes Laimighofer, Nur Banu Özcelik, Svenja Fischer

“…The first problem addresses flood frequency analysis, where floods are generated by different processes in catchment and atmosphere. …”
Get full text

Lorenz-PSO Optimized Deep Neural Network for Enhanced Phonocardiogram Classification by Awais Mahmood, Mousa Alhajlah, Habib Dhahri, Abdulaziz Almaslukh

“…The results are also compared to a fusion of instantaneous frequency-based features with random forest & KNN classifiers and other state-of-the-art methods on accuracy, precision, recall, F1-score, and fitness value. …”
Get full text

To Compare Incisional Fluid Loss During Different Stages of Phacoemulsification and its effect on Anterior Chamber Stability in Micro Coaxial and Bimanual Phacoemulsification by Dharmik Sharma, Dipan Desai, Kaushik Solanki

“…All patients were operated on the same phaco machine by the same surgeon. Intra-operative parameters were constant for all patients in each group. …”
Get full text

Vibration Tendency Prediction Approach for Hydropower Generator Fused with Multiscale Dominant Ingredient Chaotic Analysis, Adaptive Mutation Grey Wolf Optimizer, and KELM by Wenlong Fu, Kai Wang, Jiawen Tan, Kaixuan Shao

“…For this purpose, a novel hybrid approach combined with multiscale dominant ingredient chaotic analysis, kernel extreme learning machine (KELM), and adaptive mutation grey wolf optimizer (AMGWO) is proposed. …”
Get full text

Estimation of snow load and avalanche hazard assessment in Southeastern Afghanistan through remote sensing techniques by Nazir Khan Mohammadi, Mohammad Gul Arabzai, Zikui Wang

“…Due to the limited availability of ground-based observations, remote sensing techniques have been widely utilized to analyze snow cover, avalanche frequency, and climatic trends. The Snow Avalanche Frequency Estimation (SAFE) model, which employs Landsat satellite data, to emphasize remote sensing’s role in assessing climatic has successfully mapped zones susceptible to avalanches over a span of 32 years. …”
Get full text

Interpretability Study on the Fault Diagnosis Model of the Heat pipe/ Vapor Compression Composite Air Conditioning System by ZHANG Yiqi, HUANG Shuoquan, LI Xiuming, DI Yanqiang, SONG Mengjie, HAN Zongwei

“…This study develops a composite fault diagnosis model based on typical machine learning algorithms, compares the diagnostic performance of different models, and finally conducts interpretability research on the diagnostic models using the SHAP method. …”
Get full text

PMSM Sensorless Direct Torque Control System with Improved STSMO by LÜ Degang, JI Tanglong, JIANG Gouwei

Get full text

Robust Cross-Validation of Predictive Models Used in Credit Default Risk by Jose Vicente Alonso, Lorenzo Escot

“…Model validation is a challenging Machine Learning task, usually more difficult for consumer credit default models because of the availability of small datasets, the modeling of low-frequency events (imbalanced data), and the bias in the explanatory variables induced by the train/test sets split of the validation techniques (covariate shift). …”
Get full text

Cycle Time-Based Fault Detection and Localization in Pneumatic Drive Systems by Vladimir Boyko, Jürgen Weber

“…The applicability of the proposed method and its detection limits in an industrial environment are examined using pneumatic assembly machines.…”
Get full text

Graphs Constructed from Instantaneous Amplitude and Phase of Electroencephalogram Successfully Differentiate Motor Imagery Tasks by Maliheh Miri, Vahid Abootalebi, Hamid Saeedi-Sourck, Dimitri Van De Ville, Hamid Behjat

“…To determine the most discriminative subspace, an exploratory analysis was conducted in the spectral domain of the graphs by ranking the graph frequency components using a feature selection method. …”
Get full text

Application of Fractional Fourier Transform and BP Neural Network in Prediction of Tumor Benignity and Malignancy by Xuanyu Liu, Nan Gao, Shuoran He, Lizhen Wang

“…Experimental results show that the proposed model achieves an accuracy of 93.177% in classifying benign and malignant tumors, outperforming the support vector machine (SVM) method. The integration of FrFT improves feature distinguishability and reduces dependence on manual extraction. …”
Get full text

Recognition and classification techniques of marine mammal calls based on LSTM and expanded causal convolution by Wanlu Cheng, Wanlu Cheng, Hao Chen, Jiaming Jiang, Jiaming Jiang, Shuang Li, Shuang Li, Jingjing Wang, Jingjing Wang, Yanping Zhou

“…However, traditional machine learning methods struggle to capture complex acoustic patterns, while most existing deep learning approaches rely solely on frequency-domain features and require large datasets, which limits their performance on small-scale marine mammal datasets. …”
Get full text

Dynamic reconstruction of electroencephalogram data using RBF neural networks by Xuan Wang, Congcong Du, Xianjin Ke, Jian Zhang, Zheng Zheng, Yayan Yue, Ming Yu

“…IntroductionElectroencephalography (EEG) is widely used for analyzing brain activity; however, the nonlinear and nature of EEG signals presents significant challenges for traditional analysis methods. Machine has shown great promise in addressing these limitations. …”
Get full text

A synergistic approach for enhanced eye blink detection using wavelet analysis, autoencoding and Crow-Search optimized k-NN algorithm by M. Chandralekha, N. Priyadharshini Jayadurga, Thomas M. Chen, Mithileysh Sathiyanarayanan, Kasif Saleem, Mehmet A. Orgun

“…This optimization method actively samples the search space to balance exploration and exploitation to identify the optimal configuration for the model. …”
Get full text

3D convolutional neural network based on spatial-spectral feature pictures learning for decoding motor imagery EEG signal by Xiaoguang Li, Xiaoguang Li, Yaqi Chu, Xuejian Wu

“…Finally, through experiments, the proposed method is compared to various classic machine learning and deep learning techniques. …”
Get full text

User authentication of industrial internet based on HHT transform of mouse behavior by Yigong ZHANG, Qian YI, Jian LI, Congbo LI, Aijun YIN, Shuping YI

“…The rapid development of the industrial internet had caused widespread concern about the network security, and the end-user authentication technology was considered a research hotspot.According to the characteristics of human-computer interaction in industrial internet, an experimental website was designed.24 users' mouse behavior data in an uncontrolled environment were collected within 2.5 years to conduct case studies.Hilbert-Huang transform (HHT) was used to extract frequency domain features of mouse behavior signals, combined with time domain features to form a time-frequency joint domain feature matrix of 163-dimensional to characterize user mouse behavior patterns.Bagged tree, support vector machine (SVM), Boost tree and K-nearest neighbor (KNN) were used to build a user authentication model， and the comparison result showed that the Bagged tree had the best internal detection effect in this case, with an average false acceptance rate (FAR) of 0.12% and an average false rejection rate (FRR) of 0.28%.In external detection, the FAR was 1.47%.Compared with the traditional mouse dynamics method, the frequency domain information of mouse behavior extracted by HHT can better realize the user authentication, and provide technical support the security of the industrial internet.…”
Get full text

Simulation analysis of work posture and muscle fatigue in breaking and connecting contact terminal by Ruijian PAN, Xin LU, Conghan LIU, Chu CHEN, Lei LIU, Min LI

Get full text