A plug and play fuzzy mask extraction module for single image deraining by Mingdi Hu, Yao Song, Songxin Zhang, Zejian Xie, Bingyi Jing

“…Comprehensive experiments show that combining the rain removal network with our proposed model not only improves the rain removal effect of the algorithm, but also gives clearer background details of the image. …”
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Research on fine-grained classification of rare metal granite lithology based on deep learning by ZHAO Hengqian, WANG Pan, LIU Zhiguo, MIAO Qunfeng, LI Zhibin, TANG Guanglong, QI Yunfei, XIE Yu, WANG Mengmeng

“…In the future, the accuracy of fine-grained classification of rare metal granite lithology can be further improved by improving the quantity and quality of rock samples and optimizing the model algorithm.…”
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Predicting Diabetic Retinopathy and Nephropathy Complications Using Machine Learning Techniques by D. R. Manjunath, J. J. Lohith, S. Selva Kumar, Abhijit Das

“…This paper shows the possibility of machine learning based frameworks in diabetic complication management by predicting accurately and in time. These models can be integrated into clinical decision support systems (CDSS) to give insights to clinicians, improve patient outcomes through personalized interventions and optimize resource allocation. …”
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Digital mapping of peat thickness and extent in Finland using remote sensing and machine learning by Jonne Pohjankukka, Timo A. Räsänen, Timo P. Pitkänen, Arttu Kivimäki, Ville Mäkinen, Tapio Väänänen, Jouni Lerssi, Aura Salmivaara, Maarit Middleton

“…Additionally, we provided an approach for evaluating spatial prediction uncertainty based on the models’ internal prediction agreement. Compared to existing superficial deposit maps, our peat predictions significantly improve the spatial detail of peatlands at the national level, offering new opportunities for land use planning and emission mitigation. …”
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MRI-based habitat analysis of vascular and nerve invasion in the tumor microenvironment: an advanced approach for prostate cancer diagnosis by Bo Guan, Cong Huang, Yalei Wang, Jialong Zhang, Xiaowei Li, Zongyao Hao, Zongyao Hao

“…PurposeThis study aims to detect vascular and neural invasion in prostate cancer through MRI, utilize habitat analysis of the tumor microenvironment, construct a radiomic feature model, thereby enhancing diagnostic accuracy and prognostic assessment for prostate cancer, ultimately improving patients’ quality of life.MethodsWe retrospectively collected records of 400 patients with pathologically verified prostate cancer from January to December 2023. …”
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Precise robust control method for charging manipulator considering dynamic disturbances by Sihua Liu, Xiaodong Zhu, Kai Kang, Li Wan, Yong Wang

“…Charging manipulator control technology is an important means of improving the efficiency and convenience of electric vehicle charging and reducing charging risks. …”
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Decoding Depression from Different Brain Regions Using Hybrid Machine Learning Methods by Qi Sang, Chen Chen, Zeguo Shao

“…To clarify the impact of brain region segmentation on the detection accuracy of moderate-to-severe major depressive disorder (MDD) and identify the optimal brain region for detecting MDD using electroencephalography (EEG), this study compared eight traditional single-machine learning algorithms with a hybrid machine learning model based on a stacking ensemble technique. …”
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Detecting sand gradation based on the two-dimensional sand particle features in sand images by Chuanyun Xu, Heng Wang, Yang Zhang, Song Sun, Gang Li

“…Images of sand particles with a single gradation are captured to extract five sand particle feature parameters, which are then used to train a mature network model. The equivalent volume of the sand particles is calculated by multiplying the equivalent projected area by the equivalent elliptical Feret short diameter, and the Feret short diameter is optimized using an optimization algorithm to enhance the volume calculation. …”
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Dynamic externalities of basic medical insurance compensation, health capital accumulation, and economic growth by Xinyue Yuan, Xujin Yang

“…A gradually declining medical insurance compensation rate not only improves population health and boosts economic output but also provides a viable strategy for labor market optimization and health system sustainability. …”
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Computer Vision-Based Robotic System Framework for the Real-Time Identification and Grasping of Oysters by Hao-Ran Qu, Jue Wang, Lang-Rui Lei, Wen-Hao Su

“…This optimization reduced the number of model parameters by 50% and lowered the computational load by 23% in terms of GFLOPS (Giga Floating-point Operations Per Second). …”
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MRI-based intratumoral and peritumoral radiomics for assessing deep myometrial invasion in patients with early-stage endometrioid adenocarcinoma by Jing Yang, Yang Liu, Xiaolong Liu, Yaoxin Wang, Xianhong Wang, Conghui Ai, Qiu Bi, Ying Zhao

“…Integrated models were constructed by ensemble and stacking algorithms based on the above radiomics models. …”
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Comparative Analysis of Bio-Inspired Enhancement Techniques for Localization in 2D Wireless Sensor Networks by Rabhi Seddik

“…This study conducts a comparative evaluation of three bio-inspired optimization algorithms for node localization: Particle Swarm Optimization (PSO), Fruit Fly Optimization Algorithm (FOA), and Drop Mongoose Optimization Algorithm (DMOA). …”
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Boundary Guidance Strategy and Method for Urban Traffic Congestion Region Management in Internet of Vehicles Environment by Chuanxiang Ren, Zhen Wang, Changchang Yin, Hui Xu, Li Wang, Luyao Guo, Juntao Li

“…Meanwhile, a method for the boundary guidance strategy is presented in which the macroscopic fundamental diagram (MFD) is used to determine the optimal accumulation, a traffic flow equilibrium model is established to calculate the real-time accumulation, and a fuzzy adaptive PID control algorithm is designed to calculate the optimal traffic inflow of the traffic congestion region. …”
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Integrated Train Rescheduling and Rerouting during Multidisturbances under a Quasi-Moving Block System by Peijuan Xu, Dawei Zhang, Jingwei Guo, Dan Liu, Hui Peng

“…Due to this complex NP-hard problem, a two-step algorithm with three scheduling rules based on a commercial optimizer is applied to solve the problem efficiently in a real-word case, and the efficiency, validity, and feasibility of this method are demonstrated by a series of experimental tests. …”
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Robust MPS-INS UKF Integration and SIR-Based Hyperparameter Estimation in a 3D Flight Environment by Juyoung Seo, Dongha Kwon, Byungjin Lee, Sangkyung Sung

“…This adaptive hyperparameter adjustment achieved improved navigation results compared to the default UKF settings, particularly in environments with high model uncertainty.…”
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How Gait Nonlinearities in Individuals Without Known Pathology Describe Metabolic Cost During Walking Using Artificial Neural Network and Multiple Linear Regression by Arash Mohammadzadeh Gonabadi, Farahnaz Fallahtafti, Judith M. Burnfield

“…Time series data from 10 subjects walking under 13 conditions, with and without hip exoskeletons, were analyzed. Six ANN models, each corresponding to a nonlinear metric, were trained using the Levenberg–Marquardt backpropagation algorithm and compared with MLR models. …”
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Estimation of Optimum Dilution in the GMAW Process Using Integrated ANN-GA by P. Sreeraj, T. Kannan, Subhashis Maji

“…In this study, artificial neural network (ANN) and genetic algorithm (GA) techniques were integrated and labeled as integrated ANN-GA to estimate optimal process parameters in GMAW to get optimum dilution.…”
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Hierarchically Federated Learning in Wireless Networks: D2D Consensus and Inter-Cell Aggregation by Jie Zhang, Li Chen, Yunfei Chen, Xiaohui Chen, Guo Wei

“…Based on the convergence analysis, we characterize the network topology of each cell, the communication interval of intra-cell consensus and inter-cell aggregation on the training performance. To further improve the performance of HDFL, we optimize the computation capacity selection and bandwidth allocation to minimize the training latency and energy overhead. …”
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Machine Learning Applications in Gray, Blue, and Green Hydrogen Production: A Comprehensive Review by Xuejia Du, Shihui Gao, Gang Yang

“…ML algorithms such as artificial neural networks (ANNs), random forest (RF), and gradient boosting regression (GBR) have been widely applied to predict hydrogen yield, optimize operational conditions, reduce emissions, and improve process efficiency. …”
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A novel double machine learning approach for detecting early breast cancer using advanced feature selection and dimensionality reduction techniques by Suganya Athisayamani, Tamilazhagan S, A. Robert Singh, Jae-Yong Hwang, Gyanendra Prasad Joshi

“…These DML models, when combined with dimensionality reduction (PCA) and feature selection, significantly improve the performance of breast cancer detection systems by leveraging both structured and sequential data with high accuracy of 0.99.…”
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