Adaptive neuro-fuzzy inference systems for improved mastitis classification and diagnosis by Javad Shirani Shamsabadi, Saeid Ansari Mahyari, Mostafa Ghaderi-Zefrehei

“…To address this issue, an undersampling algorithm was applied to balance the class distribution by removing a portion of the majority class data. …”
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Forecasting Delivery Time of Goods in Supply Chains Using Machine Learning Methods by V. K. Rezvanov, O. M. Romakina, E. V. Zaytseva

“…The basic algorithm for the delivery forecasting model was the Decision Tree algorithm. …”
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Advanced Numerical Modeling and Experimental Analysis of Thermal Gradients in Gleeble Compression Configuration for 2017-T4 Aluminum Alloy by Olivier Pantalé, Yannis Muller, Yannick Balcaen

“…A user amplitude subroutine (UAMP) is implemented to regulate the heating based on a proportional–integral–derivative (PID) algorithm that modulates the current density to follow the specified temperature profile. …”
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A novel multiscale feature enhancement network using learnable density map for red clustered pepper yield estimation by Chenming Cheng, Chenming Cheng, Jin Lei, Jin Lei, Zicui Zhu, Lijian Lu, Lijian Lu, Zhi Wang, Zhi Wang, Jiali Tao, Jiali Tao, Xinyan Qin, Xinyan Qin

“…The proposed method provides an robust algorithmic support for efficient and intelligent yield estimation in RCP.…”
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Multi-Stage Data-Driven Framework for Customer Journey Optimization and Operational Resilience by Tzu-Chien Wang, Ruey-Shan Guo, Chialin Chen, Chia-Kai Li

“…This research highlights the practical value of integrating structured and unstructured data for improving customer analytics. …”
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Data asset valuation model based on generative artificial intelligence. by Yungang Tang, Yaoqian Liu, Daxin Liu

“…This paper constructed a data asset valuation model based on Generative AI, aimed at dynamically assessing the commercial value of data assets. The model integrates data feature extraction, value generation algorithms, and market adaptability evaluations to address the shortcomings of traditional valuation methods in dynamic market environments. …”
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Delay margin analysis of FOTID controller for RES based EV system using MMGPE optimization by Adhit Roy, Susanta Dutta, Soumen Biswas, Anagha Bhattacharya, Sajjan Kumar, Soham Dutta, Provas Kumar Roy

“…The simulation validation suggests a FOTID controller with a fractional order (n) range of 0.1 to 0.8 and a set of values for λ and μ that will be maintained within a specified delay margin. …”
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A clustering-based multi-setting overcurrent protection approach with optimisation and experimental validation for distribution networks by Feras Alasali, Mohamed Salem, Haytham Y. Mustafa, Hassen Loukil, Naser El-Naily, Abdelaziz Salah Saidi, William Holderbaum

“…This work involves integrating clustering-based topology grouping with bio-inspired optimisation techniques, specifically the Water Cycle Algorithm (WCA) and the Transit Search Algorithm (TSA), to assign optimised Time Multiply Settings (TMS) values for each relay group, ensuring fast and coordinated protection without reliance on continuous communication or centralised control. …”
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Image Fusion and Target Detection Based on Dual ResNet for Power Sensing Equipment by Jie Yang, Wei Yan, Shuai Yuan, Yu Yu, Zheng Mao, Rui Chen

“…The image is preprocessed to a certain extent, using edge detection algorithms and corner detection algorithms to extract relatively stable feature points, and the feature vectors with excessive gradient values in the normalized visible light image are truncated and normalized again to eliminate the influence of nonlinear lighting. …”
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Groundwater–CO₂ emissions relationship in Dutch peatlands derived by machine learning using airborne and ground-based eddy covariance data by L. M. van der Poel, L. V. Bataille, B. Kruijt, W. Franssen, W. Jans, J. Biermann, A. Rietman, A. J. V. Buzacott, Y. van der Velde, R. Boelens, R. W. A. Hutjes

“…Using spatiotemporal data, we train and optimize a boosted regression tree (BRT) machine learning algorithm to predict immediate CO<span class="inline-formula">₂</span> fluxes and use Shapley values and various simulations to interpret the model's outputs. …”
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A novel model for predicting immunotherapy response and prognosis in NSCLC patients by Ting Zang, Xiaorong Luo, Yangyu Mo, Jietao Lin, Weiguo Lu, Zhiling Li, Yingchun Zhou, Shulin Chen

“…Routine blood tests, due to their advantages of being minimally invasive, convenient, and capable of reflecting tumor dynamic changes, have potential value in predicting the efficacy of ICIs treatment. …”
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Small Object Detection in UAV Remote Sensing Images Based on Intra-Group Multi-Scale Fusion Attention and Adaptive Weighted Feature Fusion Mechanism by Zhe Yuan, Jianglei Gong, Baolong Guo, Chao Wang, Nannan Liao, Jiawei Song, Qiming Wu

“…Experimental results indicate that the proposed IA-YOLOv8 model has a parameter quantity of 10.9 MB, attaining an average precision (mAP) value of 42.1% on the Visdrone2019 test set, an mAP value of 82.3% on the DIOR test set, and an mAP value of 39.8% on the AI-TOD test set. …”
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Detecting severe coronary artery stenosis in T2DM patients with NAFLD using cardiac fat radiomics-based machine learning by Mengjie Liang, Liting Fang, Xie Chen, Wendi Huang

“…This study confirms that the integrated application of cardiac fat radiomics features and clinical data using machine learning models, particularly the XGBoost algorithm, facilitates the detection of severe coronary artery stenosis in T2DM patients with NAFLD. …”
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Deep learning informed multimodal fusion of radiology and pathology to predict outcomes in HPV-associated oropharyngeal squamous cell carcinomaResearch in context by Bolin Song, Amaury Leroy, Kailin Yang, Tanmoy Dam, Xiangxue Wang, Himanshu Maurya, Tilak Pathak, Jonathan Lee, Sarah Stock, Xiao T. Li, Pingfu Fu, Cheng Lu, Paula Toro, Deborah J. Chute, Shlomo Koyfman, Nabil F. Saba, Mihir R. Patel, Anant Madabhushi

“…Methods: We investigate the prognostic value of an AI approach termed the swintransformer-based multimodal and multi-region data fusion framework (SMuRF). …”
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Optimization of endocrine pancreas fluorescence analysis using machine methods by T. V. Ivanenko, A. V. Abramov

“…Methods for machine selection of the region of interest by various algorithms of the ImageJ program lead to different estimates of its area, integral, and average fluorescence values. …”
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The Clinical Significance of Abnormal Electroencephalography (EEG) Patterns in Patients with Neuropsychiatric Disorders Due to Anti-NMDA Receptor Encephalitis: A Comparative Study by Alvaro Moreno-Avellán, Arely Juarez-Jaramillo, Maria del Carmen Fernandez Gonzalez-Aragon, Gerardo Quiñones-Pesqueira, Luz Maria Pineda-Centeno, Mariana Espinola-Nadurille, Victoria Martinez-Angeles, Francisco Martinez-Carrillo, Veronica Rivas-Alonso, Daniel San-Juan, Jose Flores-Rivera, Jesus Ramirez-Bermudez

“…These findings support the integration of EEG into diagnostic algorithms to guide early detection and management of autoimmune encephalitis.…”
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Editorial by Bulent Cavas

“…The findings support the pedagogical value of tiered problem-solving to promote equitable engagement. …”
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Mathematical modeling of the initial stage of a fire in the storage of military equipment and weapons by A. L. Akhtulo, L. N. Akhtulova, A. E. Lyubako, L. A. Ivanova

“…The article dwells on the basic models of a fire, allow to evaluate the influence of dangerous factors of fire: an integral model; differential (field) model. There was suggested an algorithm of a sequential and single occupancy for completing complex structure of an object’s fire fighting system. …”
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Enhancing shear strength predictions of UHPC beams through hybrid machine learning approaches by Sanjog Chhetri Sapkota, Ajad Shrestha, Moinul Haq, Satish Paudel, Waiching Tang, Hesam Kamyab, Daniele Rocchio

“…Results showcased high accuracy, with R2 values approaching 0.9912 in training and 0.9802 in testing phases using the LSA-XGB algorithm, indicating excellent model fit and predictive reliability. …”
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Prognostic prediction of gastric cancer based on H&E findings and machine learning pathomics by Guoda Han, Xu Liu, Tian Gao, Lei Zhang, Xiaoling Zhang, Xiaonan Wei, Yecheng Lin, Bohong Yin

“…The images were segmented using the Otsu algorithm, and features were extracted using the PyRadiomics package. …”
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