Estimation of climatological parameters using ANN and WEKA models in Diyala Governorate, Iraq by DHER I. BAKR, JASIM Al-KHALIDI, HAZIM NOMAN ABED

“…The WEKA method obtained better values in the estimation of the Tmin component than ANN while the estimation of the Tmax, RH, WV, the ANN method was better than the WEAK model in the estimation of the parameters. …”
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Assessment of the Maxillary Sinus Dimensions and Volume in Different Skeletal Malocclusion Classes: An Analytical Cross-Sectional Study by Zena Hekmat Altaee, Baraa Sahib Mahdi, Mohammed Nahidh, Ahlam Thabet Bdaiwi

“…The model for the comparison of class I vs. class III showed a weak model fit (pseudo-R square = 0.06). Lower volume (P = 0.040, odds ratio = 0.5) was significantly associated with the odds of class III malocclusion. …”
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Rolling Bearing Fault Diagnosis Method Based on Fusion of CNN and CSSVM by LI Yunfeng, LAN Xiaosheng, SHEN Hongchang, XU Tongle

“…Aiming at the problems of low classification accuracy and weak model generalization ability of traditional fault diagnosis classification methods in the fault diagnosis of rolling bearings in rotating machinery, an intelligent fault diagnosis model based on signal processing technology combined with deep learning algorithm was proposed. …”
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Modelling E-Government Maturity Determinants at the Local Level in Indonesia Using Technology-Organization-Environment Framework by Torontuan Keban Yeremias, Dian Cahyadi, Achmad Djunaedi

“…However, the assessment shows that the model quality measurement is only 31.9% accurate, which is considered weak. Model refinement by strengthening the organisational and environmental variables is needed, and fit-model testing is suggested for further research.…”
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Research and Construction of Knowledge Map of Golden Pomfret Based on LA-CANER Model by Xiaohong Peng, Hongbin Jiang, Jing Chen, Mingxin Liu, Xiao Chen

“…The dataset contains challenges such as long text processing, strong local context dependencies, and entity sample imbalance, which result in low information extraction efficiency, recognition errors or omissions, and weak model generalization. This paper proposes a novel named entity recognition model, LA-CANER (Local Attention-Category Awareness NER), which combines local attention mechanisms with category awareness to improve both the accuracy and speed of NER. …”
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An end-to-end mass spectrometry data classification model with a unified architecture by Yinchu Wang, Wei Zhang, Lin Guo, Fengyi Zhang, Zilong Liu, Xingchuang Xiong, Xiang Fang

“…Despite progress in classification methods/tools for data collection in the past decade, problems such as complex data processing, weak model characterization, and large interbatch differences persist. …”
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Mapping the landscape of machine learning in chronic disease management: A comprehensive bibliometric study by Shiying Shen, Wenhao Qi, Sixie Li, Jianwen Zeng, Xin Liu, Xiaohong Zhu, Chaoqun Dong, Bin Wang, Qian Xu, Shihua Cao

“…However, challenges such as limited collaboration, weak model generalization, and data privacy persist. …”
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Benchmarking AlphaFold‐enabled molecular docking predictions for antibiotic discovery by Felix Wong, Aarti Krishnan, Erica J Zheng, Hannes Stärk, Abigail L Manson, Ashlee M Earl, Tommi Jaakkola, James J Collins

“…We confirm extensive promiscuity, but find that the average area under the receiver operating characteristic curve (auROC) is 0.48, indicating weak model performance. We demonstrate that rescoring of docking poses using machine learning‐based approaches improves model performance, resulting in average auROCs as large as 0.63, and that ensembles of rescoring functions improve prediction accuracy and the ratio of true‐positive rate to false‐positive rate. …”
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YOLOX-S-TKECB: A Holstein Cow Identification Detection Algorithm by Hongtao Zhang, Li Zheng, Lian Tan, Jiahui Gao, Yiming Luo

“…Currently, cow identification faces challenges such as poor recognition accuracy, large data volumes, weak model generalization ability, and low recognition speed. …”
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Research on a traffic flow statistical algorithm based on YBOVDT and SAM2 by Yuanyuan Wang, Zheng Ding, Jiange Liu, Kexiao Wu, Md Sharid Kayes Dipu, Tingmei Ma, Yonghao Ma, Haiyan Zhang

“…The closed-set object detection algorithms they employ can only perform detections based on fixed categories, which leads to limited recognition scope and weak model generalization ability.Moreover, the tracking algorithms used are unstable and have low computational efficiency. …”
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RSPS-SAM: A Remote Sensing Image Panoptic Segmentation Method Based on SAM by Zhuoran Liu, Zizhen Li, Ying Liang, Claudio Persello, Bo Sun, Guangjun He, Lei Ma

“…Due to the lack of large-scale annotated datasets for panoramic segmentation, existing methods still suffer from weak model generalization capabilities. To mitigate this issue, this paper leverages the advantages of the Segment Anything Model (SAM), which can segment any object in remote sensing images without requiring any annotations and proposes a high-resolution remote sensing image panoptic segmentation method called Remote Sensing Panoptic Segmentation SAM (RSPS-SAM). …”
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SAI: A Spartina alterniflora Index Based on Sentinel-2 Multispectral Imagery for Spartina alterniflora Mapping by Yangyan Zuo, Gang Yang, Weiwei Sun, Ke Huang, Susu Yang, Binjie Chen, Lihua Wang, Xiangchao Meng, Yumiao Wang, Jialin Li, Yuanzeng Zhan

“…Consequently, these methods exhibit weak model transferability and poor generalization capabilities, rendering them unsuitable for the fine-scale identification of S. alterniflora across extensive regions. …”
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Hemoglobin state-flux: A finite-state model representation of the hemoglobin signal for evaluation of the resting state and the influence of disease. by Randall L Barbour, Harry L Graber, San-Lian S Barbour

“…<h4>Summary</h4>In this report we introduce a weak-model approach for examination of the intrinsic time-varying properties of the hemoglobin signal, with the aim of advancing the application of functional near infrared spectroscopy (fNIRS) for the detection of breast cancer, among other potential uses. …”
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Wellbore stability research based on transversely isotropic strength criteria in shale formation by Xiangsen Gao, Min Wang, Xian Shi, Peng Dai, Mingming Zhang

“…The patchy plane of weakness model offers intermediate and more realistic pressure predictions. …”
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The circular economy in Aotearoa New Zealand: a critical evaluation of policy and its current prospects by Shannon Hodge, Patrick Barrett, Priya Kurian

“…The analysis concludes that both ministries have articulated weak models of circularity that neglect the transformational potential of a circular economy agenda. …”
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Evaluating water-induced wellbore instability in shale formations: a comparative analysis of transversely isotropic strength criteria by Yuqi Zhang, Xuejia Du, Dingwen Jiang

“…Within the β1 to β2 range, both the Jaeger’s Plane of Weakness model (JPW) and Plane of Patchy Weakness Model (PPW) accurately predicted shale strength; however, below β1, the JPW criterion overestimated strength, while the PPW criterion better reflected strength variations. …”
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Fitting of anisotropic strength parameters of laminated shale and its influence on wellbore instability by Jinyou Zhang, Xiaobo Liu, Hongge Jia, Xuejia Du, Zhongmin Wang, Guoqiang Pan, Mingming Zhang

“…In contrast, the single plane of weakness model (SPW) and patchy plane of weakness model (PPW) criteria cannot distinguish the strength difference between vertical and horizontal bedding but have better predictive performance for the strength during shear slip failure along the bedding plane. …”
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Boosting Barlow Twins Reduced Order Modeling for Machine Learning‐Based Surrogate Models in Multiphase Flow Problems by T. Kadeethum, V. L. S. Silva, P. Salinas, C. C. Pain, H. Yoon

“…This algorithm sequentially trains a set of weak models (i.e., inaccurate models), improving prediction accuracy through ensemble learning. …”
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Non-Maximum Suppression for Rotated Object Detection During Merging Slices of High-Resolution Images by Lei Ge, Lei Dou

“…It has low requirements for the overlap gap of slices and shows a significant improvement in performance for weak models. Hence, it is more suitable for computing-constrained mobile platforms such as drones to detect objects on high-resolution images.…”
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PPFL-DCS: Privacy-Preserving Federated Learning Using Neural Transformer and Leveraging Dynamic Client Selection to Accommodate Data Diversity by Nakul Mehta, Nitesh Bharot, John G. Breslin, Priyanka Verma

“…However, FL-based techniques still have shortcomings, FedAvg equally weights weak models, risking suboptimal results; FL also faces Membership Inference privacy attacks. …”
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