Research on Recommendation of Core Competencies and Behavioral Indicators of Pilots Based on Collaborative Filtering by Haiwen Xu, Yifan Kong, Hong Huang, Aimin Liang, Yunxiang Zhao

“…This paper proposes a new model of collaborative filtering that introduces a user difference factor to address the issue of less pronounced similarity performance in traditional algorithms. The algorithm is applied to the recommendation of pilots’ core competency behavior indicators to support pilots’ daily training arrangements, improve their core competencies, and ensure civil aviation flight safety. …”
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Optimized YOLOv8 for enhanced breast tumor segmentation in ultrasound imaging by Ayman Mohamed Mostafa, Alaa S. Alaerjan, Bader Aldughayfiq, Hisham Allahem, Alshimaa Abdelraof Mahmoud, Wael Said, Hosameldeen Shabana, Mohamed Ezz

“…These models were evaluated in two experimental setups—training on a combined dataset and training on separate datasets for benign and malignant classes. …”
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Comparative Analysis of Deep Learning Methods for Classification of Ablated Regions in Hyperspectral Images of Atrial Tissue by Yeva Gabrielyan, Arpi Hunanyan, Sona Bezirganyan, Lusine Davtyan, Ani Avetisyan, Narine Sarvazyan, Aram Butavyan, Varduhi Yeghiazaryan

“…For objective evaluation, per HSI cube, we limit the training and testing to rectangular areas of known classes (ablated/unablated), as reliable classification masks for whole HSI cubes are not available. …”
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Sustainable energy: Advancing wind power forecasting with grey wolf optimization and GRU models by Zainab Al-Ibraheemi, Samaher Al-Janabi

“…Applying the MEF-GWO algorithm further reduced the dataset to 109395, with a reduction rate of 0.385. …”
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Automated segmentation of brain metastases in T1-weighted contrast-enhanced MR images pre and post stereotactic radiosurgery by Hemalatha Kanakarajan, Wouter De Baene, Patrick Hanssens, Margriet Sitskoorn

“…Previous studies assessed several DL algorithms focusing only on training and testing the models on the planning MRI only. …”
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Study on privacy preserving encrypted traffic detection by Xinyu ZHANG, Bingsheng ZHANG, Quanrun MENG, Kui REN

“…Existing encrypted traffic detection technologies lack privacy protection for data and models, which will violate the privacy preserving regulations and increase the security risk of privacy leakage.A privacy-preserving encrypted traffic detection system was proposed.It promoted the privacy of the encrypted traffic detection model by combining the gradient boosting decision tree (GBDT) algorithm with differential privacy.The privacy-protected encrypted traffic detection system was designed and implemented.The performance and the efficiency of proposed system using the CICIDS2017 dataset were evaluated, which contained the malicious traffic of the DDoS attack and the port scan.The results show that when the privacy budget value is set to 1, the system accuracy rates are 91.7% and 92.4% respectively.The training and the prediction of our model is efficient.The training time of proposed model is 5.16 s and 5.59 s, that is only 2-3 times of GBDT algorithm.The prediction time is close to the GBDT algorithm.…”
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Monitoring of Indoor Air Quality in a Classroom Combining a Low-Cost Sensor System and Machine Learning by Ioannis D. Apostolopoulos, Eleni Dovrou, Silas Androulakis, Katerina Seitanidi, Maria P. Georgopoulou, Angeliki Matrali, Georgia Argyropoulou, Christos Kaltsonoudis, George Fouskas, Spyros N. Pandis

“…ML-based calibration was investigated for the CO, NO, NO₂, and O₃ sensors using measurements by reference instruments for training and evaluation. Among the eleven ML algorithms tested, the Support Vector Regression performed better for the calibration of the CO, NO₂, and O₃ sensors. …”
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Querying 3D point clouds exploiting open-vocabulary semantic segmentation of images by A. Alami, A. Alami, F. Remondino

“…However, these models are still relying on some data for training and fine-tuning for specific tasks. This requirement limits them to real-world applications. …”
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Artificial Intelligence in Wound Care: A Narrative Review of the Currently Available Mobile Apps for Automatic Ulcer Segmentation by Davide Griffa, Alessio Natale, Yuri Merli, Michela Starace, Nico Curti, Martina Mussi, Gastone Castellani, Davide Melandri, Bianca Maria Piraccini, Corrado Zengarini

“…However, many apps did not publish sufficient information on the segmentation methods or algorithms used, and most lacked details on the databases employed for training their AI models. …”
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Development and validation of a machine learning-based survival prediction model for Asian glioblastoma patients using the SEER database and Chinese data by Denglin Li, Luxin Zhang, Lifei Xu, Renhe Zhai, Hanyu Gao, Junlan Gao, Minghai Wei, Ningwei Che, Yeting He

“…Univariate and multivariate Cox regression analyses were performed to evaluate the prognostic factors. Predictive models for OS and CSS were established based on eight machine learning algorithms, including Lasso Cox, random survival forest, CoxBoost, generalized boosted regression modelling (GBM), stepwise Cox and survival support vector machine, eXtreme Gradient Boosting, supervised principal component and partial least squares regression for Cox, and the selected predictive models were evaluated by the area under the ROC curves (AUC) and 95% confidence interval (CI), calibration curves and decision curve analyses in the training set, validation set and test set. …”
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Integrating ultrasound radiomics and clinicopathological features for machine learning-based survival prediction in patients with nonmetastatic triple-negative breast cancer by Wenwen, Zekun Jiang, Jingyan Liu, Dingbang Liu, Yiyue Li, Yushuang He, Haina Zhao, Lin Ma, Yixin Zhu, Qiongxian Long, Jun Gao, Honghao Luo, Heng Jiang, Kang Li, Xiaorong Zhong, Yulan Peng

“…Methods and materials All patients, including retrospective cohort (training cohort, n = 306; internal validation cohort, n = 77) and prospective external validation cohort (n = 82), were diagnosed as locoregional TNBC and underwent pre-intervention sonographic evaluation in this multi-center study. …”
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Research on productivity prediction method of infilling well based on improved LSTM neural network: A case study of the middle-deep shale gas in South Sichuan by GUAN Wenjie, PENG Xiaolong, ZHU Suyang, YANG Chen, PENG Zhen, MA Xiaoran

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An echo state network based on enhanced intersecting cortical model for discrete chaotic system prediction by Xubin Wang, Pei Ma, Jing Lian, Jizhao Liu, Yide Ma

“…A Bayesian Optimization algorithm was employed for the selection of hyperparameters. …”
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SERLogic: A Logic-Integrated Framework for Enhancing Sequential Recommendations by Lihang Fan

“…s}$ </tex-math></inline-formula>; 3) parallel algorithm that applies the discovered <inline-formula> <tex-math notation="LaTeX">$\mathsf {TIE^{+}\!…”
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Advancing Agile Software Cost Estimation Through Data Synthesis: A Comparative Analysis of Five Generation Techniques by Xiaoyan Zhao, Zulkefli Mansor, Rozilawati Razali, Mohd Zakree Ahmad Nazri, Xin Xiong

“…While machine learning algorithms have performed better in this area, the lack of sufficient agile cost data hinders large-scale training and in-depth research. …”
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Machine learning models for reinjury risk prediction using cardiopulmonary exercise testing (CPET) data: optimizing athlete recovery by Arezoo Abasi, Ahmad Nazari, Azar Moezy, Seyed Ali Fatemi Aghda

“…Specifically, we sought to identify key physiological and performance variables that correlate with reinjury and to evaluate the performance of various ML algorithms in generating accurate predictions. …”
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Application of the U-Net Deep Learning Model for Segmenting Single-Photon Emission Computed Tomography Myocardial Perfusion Images by Ahmad Alenezi, Ali Mayya, Mahdi Alajmi, Wegdan Almutairi, Dana Alaradah, Hamad Alhamad

“…Background: Myocardial perfusion imaging (MPI) is a type of single-photon emission computed tomography (SPECT) used to evaluate patients with suspected or confirmed coronary artery disease (CAD). …”
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Evolutionary learning in neural networks by heterosynaptic plasticity by Zedong Bi, Ruiqi Fu, Guozhang Chen, Dongping Yang, Yu Zhou, Liang Tian

“…Overall, this research extends training approaches for biophysical neuron models, offering a robust alternative to traditional algorithms.…”
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Extracting organs of interest from medical images based on convolutional neural network with auxiliary and refined constraints by Fenghui Lian, Yingjie Sun, Meiyu Li

“…We evaluate the proposed framework on two public databases (NIH Pancreas-CT and MICCAI Sliver07). …”
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One round of azithromycin MDA adequate to interrupt transmission in districts with prevalence of trachomatous inflammation-follicular of 5.0-9.9%: Evidence from Malawi. by Khumbo Kalua, Alvin Chisambi, David Chinyanya, Michael Masika, Ana Bakhtiari, Rebecca Willis, Paul M Emerson, Anthony W Solomon, Robin L Bailey

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