Refining Sparse Cell-ID Trajectory of Public Service Vehicles by Spatiotemporal Modelling by Kemin Zhu, Junli Liu, Xianfeng Song, Weifeng Wang, Hao Chen

“…The approach was finally tested using Beijing cellular network signaling datasets. The precision of PSV trajectory detection is 90%, and the recall is 88%. …”
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Exploring the influences of education, intelligence and income on mental disorders by Fuquan Zhang, Ancha Baranova, Hongbao Cao

“…However, the direct effects of each factor on major mental disorders are unclear.Aims We aimed to evaluate the overall and independent causal effects of the three psychosocial factors on common mental disorders.Methods Using genome-wide association study summary datasets, we performed Mendelian randomisation (MR) and multivariable MR (MVMR) analyses to assess potential associations between the 3 factors (EA, N=766 345; household income, N=392 422; intelligence, N=146 808) and 13 common mental disorders, with sample sizes ranging from 9907 to 807 553. …”
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Ensemble of semi-supervised feature selection algorithms to reinforce heuristic function in ant colony optimization by Fereshteh Karimi, Mohammad Bagher Dowlatshahi, Amin Hashemi

“…We have compared the performance of the ESACO using the KNN classifier with variant experiments with eight semi-supervised FS techniques and 15 datasets. Considering the obtained results, the efficiency of the presented method is significantly better than the competing methods. …”
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Spatial transcriptome reveals histology-correlated immune signature learnt by deep learning attention mechanism on H&E-stained images for ovarian cancer prognosis by Chun Wai Ng, Kwong-Kwok Wong, Barrett C. Lawson, Sammy Ferri-Borgogno, Samuel C. Mok

“…After validating the model with the testing datasets, pathway enrichment analysis showed that the H&E—based survival score significantly correlated with certain immune signatures and this was validated spatially using spatial transcriptome data generated from ovarian cancer FFPE samples by correlating the selected signature and attention signal. …”
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Cuproptosis related lncRNA signature as a prognostic and therapeutic biomarker in osteosarcoma immunity by Ziwei Gao, Siqi Chen, Wei Ye

“…Databases from TARGET were used to acquire osteosarcoma patient datasets, which included clinical information and RNA sequencing data. …”
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Deep Feature Learning for Intrinsic Signature Based Camera Discrimination by Chaity Banerjee, Tharun Kumar Doppalapudi, Eduardo Pasiliao, Tathagata Mukherjee

“…We conduct experiments using three custom datasets: the first containing two cameras in an indoor environment where each camera may observe different scenes having no overlapping features, the second containing images from four cameras in an outdoor setting but where each camera observes scenes having overlapping features and the third containing images from two cameras observing the same checkerboard pattern in an indoor setting. …”
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Machine learning-random forest model was used to construct gene signature associated with cuproptosis to predict the prognosis of gastric cancer by Xiaolong Liu, Pengxian Tao, He Su, Yulan Li

“…Transcriptome and clinical data of patients with GC were collected from The Cancer Genome Atlas and Gene Expression Omnibus datasets. Single sample gene set enrichment analysis (GSEA) and the randomized forest method were used to establish the prognostic model. …”
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Mapping the extent of unhealthy food advertising around schools in Tāmaki Makaurau/Auckland by Karolina Kneller, Kelly Garton, Daniel J. Exeter, Victoria Egli

“…Using a combination of datasets from separate studies, this research seeks to describe the extent of children’s unhealthy food/drink advertising exposure in all primary and intermediate school food zones (n = 381) in Tāmaki Makaurau, Auckland, and assess whether this exposure correlates with indicators of neighbourhood deprivation. …”
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Outbreak of Norovirus GII.P17-GII.17 in the Canadian Province of Nova Scotia by Jason J. LeBlanc, Janice Pettipas, Daniel Gaston, Robin Taylor, Todd F. Hatchette, Tim F. Booth, Russell Mandes, Andrew McDermid, Elsie Grudeski

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Transforming traffic accident investigations: a virtual-real-fusion framework for intelligent 3D traffic accident reconstruction by Yanzhan Chen, Qian Zhang, Fan Yu

“…., 3D Gaussian splatting (3D-GS), is utilized to construct 3D digitized traffic accident scenes from UAV-based image datasets collected in the traffic simulation environment. …”
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Open Issues in Statistical Forecasting of Solar Proton Events: A Machine Learning Perspective by Mirko Stumpo, Simone Benella, Monica Laurenza, Tommaso Alberti, Giuseppe Consolini, Maria Federica Marcucci

“…This is a critical issue of any statistical approach, which requires to perform the model validation by preserving the class distributions within the training and test datasets.…”
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Deep learning-based skin lesion analysis using hybrid ResUNet++ and modified AlexNet-Random Forest for enhanced segmentation and classification. by Saleem Mustafa, Arfan Jaffar, Muhammad Rashid, Sheeraz Akram, Sohail Masood Bhatti

“…The proposed hybrid deep learning model is intensively validated on the Ham10000 data set which is one of the most popular datasets for skin lesions analysis. The obtained results show that the utilized approach, compared to the previous ones, is more effective, giving better segmentation and classification results. …”
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Early Detection of Seasonal Outbreaks from Twitter Data Using Machine Learning Approaches by Samina Amin, Muhammad Irfan Uddin, Duaa H. alSaeed, Atif Khan, Muhammad Adnan

“…For experimental analysis, two datasets (dengue and flu) are analyzed individually. …”
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Open government data in health sector: a systematic literature review by Patrícia Nascimento Silva, Sarah Nascimento Silva

“…Results Of the 3,176 records initially identified, six studies were included describing initiatives to make available datasets or portals that publish OGD in the healthcare area between 2020 and 2023. …”
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Face Recognition Method for Underground Engineering Based on Dual-Target Domain Adaptation and Discriminative Feature Learning by Yongqiang Yu, Cong Guo, Lidan Fan, Jiyun Zhang, Liwei Yu, Peitao Li

“…Extensive experiments are conducted on public and self-built datasets to verify the proposed method. The results show that <xref ref-type="disp-formula" rid="deqn1">(1)</xref> dual domain adversarial loss, dual CORAL loss, Blur-to-Sharp and NIR-to-VIS image reconstruction, and face keypoints intermediate domain can improve the DTDA performance of the model. …”
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Revealing systematic changes in the transcriptome during the transition from exponential growth to stationary phase by Hyun Gyu Lim, Ye Gao, Kevin Rychel, Cameron Lamoureux, Xuwen A. Lou, Bernhard O. Palsson

“…This study demonstrates how the combination of genome-scale datasets and new data analytics reveals the fundamental characteristics of a key transition in the life cycle of bacteria.IMPORTANCENutrient limitations are critical environmental perturbations in bacterial physiology. …”
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Semi-Supervised Change Detection with Data Augmentation and Adaptive Thresholding for High-Resolution Remote Sensing Images by Wuxia Zhang, Xinlong Shu, Siyuan Wu, Songtao Ding

“…We verify the effectiveness and robustness of the proposed method on two high-resolution remote sensing image datasets, WHU-CD and LEVIR-CD. We compare our method to five state-of-the-art change detection methods and show that it achieves better or comparable results.…”
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Visual-inertial navigation assisted by a single UWB anchor with an unknown position by Haolong Luo, Danping Zou, Jiansheng Li, Ancheng Wang, Li Wang, Zidi Yang, Guangyun Li

“…Then, we conducted ablation experiments utilizing the open-source VIRAL and real-world datasets. The experimental results demonstrate that the proposed method exhibits superior positioning accuracy and robustness in contrast to the open-source VINS-MONO and VIR-SLAM methods.…”
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Obesity, Metabolic Health, and Diabetic Complications in People With Type 1 Diabetes by Yuanjie Mao, Jen‐Tzer Gau, Ning Jiang

“…ABSTRACT Aim The concept of metabolically healthy obesity (MHO) has not been studied in type 1 diabetes (T1D). By analysing datasets from the DCCT/EDIC study, we compared the development of diabetic complications by obesity and metabolic health over 30 years of follow up. …”
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Robust Time-Series InSAR Deformation Monitoring by Integrating Variational Mode Decomposition and Gated Recurrent Units by Peifeng Ma, Zeyu Jiao, Zherong Wu

“…Experiments on physical-based synthetic and real-world datasets demonstrate that the proposed VMD-GRU outperforms the existing methods. …”
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