Enhancing structural health monitoring with machine learning for accurate prediction of retrofitting effects by A. Presno Vélez, M. Z. Fernández Muñiz, J. L. Fernández Martínez

“…This research aimed to develop a methodology for training an artificial intelligence (AI) system to predict the effects of retrofitting on civil structures, using data from the KW51 bridge (Leuven). …”
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A Vision-Based Method for Detecting the Position of Stacked Goods in Automated Storage and Retrieval Systems by Chuanjun Chen, Junjie Liu, Haonan Yin, Biqing Huang

“…This paper proposes a novel machine vision-based detection algorithm that integrates a pallet surface object detection network (STEGNet) with a box edge detection algorithm. …”
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N-SOFT SETS ASSOCIATION RULE AND ITS APPLICATION FOR PROMOTION STRATEGY IN DISTANCE EDUCATION by Fatia Fatimah, Selly Anastassia Amellia Kharis, Fauzan Ihza Fajar

“…Based on the results, the NSSAR algorithm gave relationship patterns between the number of new students based on region, study program, diploma of origin, and information media. …”
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Identification and validation of efferocytosis-related biomarkers for the diagnosis of metabolic dysfunction-associated steatohepatitis based on bioinformatics analysis and machine... by Chenghui Cao, Chenghui Cao, Wenwu Liu, Xin Guo, Shuwei Weng, Yang Chen, Yonghong Luo, Shuai Wang, Botao Zhu, Botao Zhu, Yuxuan Liu, Yuxuan Liu, Daoquan Peng

“…To screen for biomarkers for diagnosis, we applied machine learning algorithm to identify hub genes and constructed a clinical predictive model. …”
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Influence of Source Shape on Semi-Airborne Transient Electromagnetic Surveys by Lei Liu, Jianghai Xie, Wentao Liu, Jianmei Zhou

“…The semi-airborne transient electromagnetic (SATEM) method has garnered increasing attention and research interest due to its superior detection depth and high efficiency. …”
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Machine learning approach for identifying and forecasting streamflow droughts in data limited basins of South Korea using threshold levels by Young-Ho Seo, Jang Hyun Sung, Byung-Sik Kim, Junehyeong Park

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Syllable-, Bigram-, and Morphology-Driven Pseudoword Generation in Greek by Kosmas Kosmidis, Vassiliki Apostolouda, Anthi Revithiadou

“…Pseudowords are essential in (psycho)linguistic research, offering a way to study language without meaning interference. …”
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Beyond accuracy: Multimodal modeling of structured speaking skill indices in young adolescents by Candy Olivia Mawalim, Chee Wee Leong, Guy Sivan, Hung-Hsuan Huang, Shogo Okada

“…The experimental results demonstrate that fusing interpretable features, including prosody, action units, and turn-taking, significantly enhances the accuracy of spoken English skill prediction, achieving an overall accuracy of 83% when a machine learning model based on the light gradient boosting algorithm is used. Furthermore, this research underscores the significant influence of external factors, such as interviewer behavior and the interview setting, particularly on the coherence aspect of spoken English proficiency. …”
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Hybrid deep learning for IoT-based health monitoring with physiological event extraction by Sivanagaraju Vallabhuni, Kumar Debasis

“…In this regard, the research also paves the way for designing next-gen IoT healthcare analytics and their actual clinical applications.…”
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Multimodal image fusion for ich detection and classification using parallel Dl models by Sri Sangepu Nagaraju, S. Prince Mary, V. Pavani Chandra, Nandam Gayatri

“…This paper introduces an innovative multimodal medical image fusion method using parallel Deep Learning (DL) models. The research uses a carefully chosen multimodal dataset, including CT and MRI, and a novel segmentation algorithm called DFA-UNet. …”
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An Explainable Machine Learning Model for Predicting Macroseismic Intensity for Emergency Management by Federico Mori, Giuseppe Naso

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Financial Technology and Financial Inclusion in Remote Areas of Algeria. Analytical Study Using Data Mining by Hassiba Hadouga

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AI and Human Resources in a Literature-Driven Investigation Into Emerging Trends by Cristina Iancu, Simona-Vasilica Oprea

“…The analysis brings out a steady growth in publication volume, with an average of 2,500 papers annually and a significant concentration of research within domains such as neural networks, algorithm optimization and digital transformation. …”
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Increased Extreme Precipitation in Western North America from Cut-Off Lows Under a Warming Climate by Henri Pinheiro, Tercio Ambrizzi, Kevin Hodges

“…Nonetheless, future changes in COL frequency, intensity, and precipitation patterns remain uncertain. This study examines projected COL changes and their drivers in western North America under a high greenhouse gas concentration pathway (SSP585) using a multi-model ensemble from CMIP6 and a feature-tracking algorithm. …”
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Enhanced residual attention-based subject-specific network (ErAS-Net): facial expression-based pain classification with multiple attention mechanisms by Mahdi Morsali, Aboozar Ghaffari

“…Through transfer learning and multiple attention mechanisms, the proposed deep learning model is designed to mimic human perception of facial expressions, thereby enhancing its pain recognition ability and capturing the unique features of each individual’s facial expressions based on their specific patterns. The UNBC-McMaster Shoulder Pain dataset is used to demonstrate the effectiveness of the proposed deep learning algorithm, which achieves impressive values of 98.77% accuracy for binary classification and 94.21% for four-level pain intensity classification using tenfold cross-validation. …”
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An Improvement of the Load Transfer Method for Energy Piles Under Thermo-Mechanical Loads by Haofan Yang, Haowen Pan, Chenfeng Zong, Ziyi Wang, Gang Jiang

“…Due to its widespread adoption, research on energy pile analysis theory has advanced significantly. …”
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sEMG-based gesture recognition using multi-stream adaptive CNNs with integrated residual modules by Yutong Xia, Dawei Qiu, Cheng Zhang, Jing Liu

“…This improves the model’s ability to extract and understand complex data patterns.ResultsThe experimental results demonstrated that the model achieved recognition accuracies of 98.24%, 93.52%, and 92.27% respectively on the Ninapro DB1, Ninapro DB2, and Ninapro DB4 datasets. …”
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Ultrahigh-throughput single-pixel complex-field microscopy with frequency-comb acousto-optic coherent encoding (FACE) by Daixuan Wu, Yuecheng Shen, Zhongzheng Zhu, Tijian Li, Jiawei Luo, Zhengyang Wang, Jiaming Liang, Zhiling Zhang, Yunhua Yao, Dalong Qi, Lianzhong Deng, Zhenrong Sun, Meng Liu, Zhi-Chao Luo, Shian Zhang

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Automatic Detection for Mining Subsidence Areas Using the CBAM-Enhanced VGG-UNet Model With Long Time Series InSAR Interferograms by Kegui Jiang, Keming Yang, Mengting Gao, Liuguo Zhu, Chuang Jiang

“…The technical theories of monitoring and preventing mining subsidence have long been key challenges and research priorities in the mining field. The rapid advancements in remote sensing technology and deep learning algorithms have enabled significant breakthroughs in monitoring and accurately identifying mining subsidence. …”
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Population status and impact of climate change on the distribution of vulnerable multipurpose plant Hippophae rhamnoides ssp. turkestanica for conservation in Trans-Himalaya, India by Shiv Paul, Shiv Paul, Khilendra Singh Kanwal, Anil Kumar, Sher Singh Samant, Sher Singh Samant, Indra Dutt Bhatt, Rakesh Chandra Sundriyal, Rakesh Chandra Sundriyal, Swaran Lata

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