A Coordinated Allocation Method for Right-Turn Strategy at Signalized Intersections with Optimal Pedestrian and Vehicle Delays by Yu Bai, Wanyan Luo

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Geochemical Influences on Carbon Nanotubes Transport in Subsurface Environments: Integrating Millifluidics, Spectral Induced Polarization, and Machine Learning by Yixin Yang, Pengfei Liu, Kexin Chen, Sheng Zhou, Longlong Meng, Chi Zhang, Junnan Cao, Bate Bate

“…SIP detected real‐time retention by chargeability (R2 = 0.82–0.96), while a DNN decoded SIP signals to predict spatially resolved CNT deposition (R2 = 0.926), outperforming phenomenological Cole‐Cole modeling. …”
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Research on an Ecological Sensitivity Evaluation of Mountain-Type National Parks Under Multi-Modal Optimization: A Case Study of Shennongjia, China by Xingyu Zhou, Huan Huang, Shi Dai, Duanya Zheng, Jie Zhao

“…The results demonstrate that the refined data structure enhances terrain coupling accuracy by transitioning from “Vegetation Type—Runoff Coefficient” to “Vegetation Density—Runoff Coefficient” conversions, with the optimized model exhibiting superior sensitivity in spatial element identification. …”
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Attention-based generative adversarial networks for aquaponics environment time series data imputation by Keyang Zhong, Xueqian Sun, Gedi Liu, Yifeng Jiang, Yi Ouyang, Yang Wang

“…In the downstream experiments, we used ATTN-GAN and baseline models for data imputation, and predicted the imputed data, respectively. …”
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A New Method for Joint Sparse DOA Estimation by Jinyong Hou, Changlong Wang, Zixuan Zhao, Feng Zhou, Huaji Zhou

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Construction of symbiosis corridors for heritage resources and optimization of conservation strategies in the basin: A case study of the Yellow River basin in Shandong, China by Ying Yu, Bin Yu, Xinwen Zhang, Lin Ma, Caijun Zhao, Yanyan Jia, Shujun Hou, Xin Han, Kun Li, Xinchuang Chen, Chuanrong Li, Bing Liu

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A fault diagnosis method for inter-turn short circuit based on magnetic field distribution by Bowen Wang, Lulu Wang

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Characterising the spatio-temporal patterns of water quality parameters in the cradle of humankind world heritage site using Sentinel-2 and random forest regressor by Sinesipho Ngamile, Sinesipho Ngamile, Mahlatse Kganyago, Sabelo Madonsela, Sabelo Madonsela, Vuyelwa Mvandaba

“…IntroductionWater quality assessment is essential for monitoring and managing freshwater resources, particularly in ecologically and culturally significant areas like the Cradle of Humankind World Heritage Site (COHWHS). This study aimed to predict and map the spatio-temporal patterns of both optically and non-optically active water quality parameters within small inland water bodies located in the COHWHS.MethodsHigh-resolution Sentinel-2 Multispectral Instrument (MSI) satellite data and two random forest models (Model 1 [consisting of sensitive spectral bands] and Model 2 [consisting of spectral bands + indices]) were used alongside In-situ measurements of chlorophyll-a, suspended solids, dissolved oxygen (DO), pH, Temperature, and electrical conductivity (EC) were integrated to establish empirical relationships and assess spatial variability across high-flow and low-flow conditions.ResultsThe results indicated that DO could be predicted with the highest accuracy under low-flow conditions, followed by EC. …”
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The Effect of Simulated Dose Reduction on the Performance of Artificial Intelligence in Chest Radiography by Hendrik Erenstein, Wim P. Krijnen, Annemieke van der Heij-Meijer, Peter van Ooijen

“…Chest imaging plays a pivotal role in screening and monitoring patients, and various predictive artificial intelligence (AI) models have been developed in support of this. …”
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Analysis of space solar array arc images based on deep learning techniques by Afaf M. Abd El-Hameed, Ahmed S. Farahat, Khaled Y. Youssef, M. Elfarran, I. M. Selim

“…Leveraging advanced Deep Learning (DL) methodologies, including Convolutional Neural Networks (CNN) and Transfer Learning, a robust predictive model has been developed to analyze arc behavior and identify defective cells based on image data. …”
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A topological approach to understanding crack initiation and propagation in carbon fiber reinforced polymer composites under an opening load by Mayrene Uy, Daiki Kido, Masao Kimura

“…From a materials perspective, this methodology allows integration of not just crack length but also 3D crack shape into predictive models, offering valuable insights for optimizing the performance and extending the lifetime of carbon fiber/epoxy composites.…”
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Comparing US state resident IQ, socioeconomic status, and racial-ethnic composition as predictors of state violent crime rates by Stewart J. H. McCann

“…Generally, the results underline the importance of evaluating potential crime rate predictors in a multiple regression model rather than testing their predictive capacities only as single variables.…”
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Forest Fire Hazard Assessment using Remote Sensing Data and Machine Learning, Case Study of Jijel, Algeria by Matougui Zakaria, Zouidi Mohamed

“…Evaluation metrics such as Receiver Operating Characteristic Area Under the Curve, F1 score and accuracy, supported by repeated cross-validation, were used to gauge performance. Both models performed well (with an average area under the curve of 0.977 and 0.984, respectively), with HGB maintaining a marginal but consistent advantage over KNN, with relatively low standard deviations, suggesting stability in its predictive capability. …”
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A Comprehensive Dataset of Surface Water Quality Spanning 1940-2023 for Empirical and ML Adopted Research by Md. Rajaul Karim, M. M. Mahbubul Syeed, Ashifur Rahman, Khondkar Ayaz Rabbani, Kaniz Fatema, Razib Hayat Khan, Md Shakhawat Hossain, Mohammad Faisal Uddin

“…This dataset can support meta-analysis of water quality models and can facilitate Machine Learning (ML) based data and model-driven investigation of the spatial and temporal drivers and patterns of surface water quality at a cross-regional to global scale.…”
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Network-based multi-omics integrative analysis methods in drug discovery: a systematic review by Wei Jiang, Weicai Ye, Xiaoming Tan, Yun-Juan Bao

“…Future developments should focus on incorporating temporal and spatial dynamics, improving model interpretability, and establishing standardized evaluation frameworks.…”
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MeDML: Med-Dynamic Meta Learning - A multi-layered representation to identify provider fraud in healthcare by Nitish Kumar, Deepak Chaurasiya, Alok Singh, Siddhartha Asthana, Kushagra Agarwal, Ankur Arora

“…We test the dynamically generated meta embedding using various downstream models and show that it outperforms all baseline algorithms for provider fraud prediction task.…”
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Cross-modal interactive and global awareness fusion network for RGB-D salient object detection. by Runqing Li, Ling Yu, Zijian Jiang, Fanglin Niu

“…It outperforms salient object detection methods that rely solely on RGB images by leveraging the geometric morphology and spatial layout information from depth images. However, the existing RGB-D detection model still encounters difficulties in accurately recognising and highlighting salient objects when facing complex scenes containing multiple or small objects. …”
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Beyond surveys: high-resolution mapping of rural wealth in China using satellite and street view imagery by Weipan Xu, Qiumeng Li, Yaofu Huang, Yu Gu, Xun Li

“…Centered on the intelligent interpretation of rural housing features, we extract wealth-related visual elements from imagery and regress them against benchmark survey-based household wealth indicators to develop a high-accuracy township-level wealth prediction model (R² = 71%). This model is used to generate a nationwide, township-scale rural household wealth map. …”
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Optimization for Metro Operation Scheme of Suburban Lines: A New Method for Dealing with the Imbalanced Passenger Flow by Xiaobing Ding, Gan Shi, Jiangang Jin, Lixing Yang, Zhigang Liu

“…Finally, a set of numerical experiments with operation data from Shanghai Metro Line 16 are conducted to verify the performance and effectiveness of the proposed model and algorithm. The experimental results show that the proposed approach can effectively realize the collaborative optimization of passenger OD prediction, train proportion, stop scheme, and travel time, so as to provide decision-making support and method guidance for the optimization of metro organizations in megacities.…”
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Single Vector Hydrophone DOA Estimation: Leveraging Deep Learning with CNN-CBAM by Fanyu ZENG, Yaning HAN, Hongyuan YANG, Dapeng YANG, Fan ZHENG

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