Machine Learning Model Coupled with Graphical User Interface for Predicting Mechanical Properties of Flax Fiber by T. Nageshkumar, Prateek Shrivastava, L. Ammayapan, Manisha Jagadale, L. K. Nayak, D. B. Shakyawar, Indran Suyambulingam, P. Senthamaraikannan, R. Kumar

“…In this study, a total of 432 patterns of input and output parameters obtained from laboratory experiments were used to develop machine learning algorithms (Random forest, support vector, and XGBoost). …”
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Supply chain management and optimization in transportation logistics by Saoussen Krichen

“…<p>Supply chain management (SCM) is the decision-making process that steers numerous activities in order to generate added values for all stakeholders. The aim of this process is to optimize each activity in terms of advantageous profits to the suppliers, retailers and customers. …”
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Of cattle and feasts: Multi-isotope investigation of animal husbandry and communal feasting at Neolithic Makriyalos, northern Greece. by Petra Vaiglova, Paul Halstead, Maria Pappa, Sevi Triantaphyllou, Soultana M Valamoti, Jane Evans, Rebecca Fraser, Panagiotis Karkanas, Andrea Kay, Julia Lee-Thorp, Amy Bogaard

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A Nondestructive Detection Method for the Muti-Quality Attributes of Oats Using Near-Infrared Spectroscopy by Linglei Li, Long Li, Guoyuan Gou, Lang Jia, Yonghu Zhang, Xiaogang Shen, Ruge Cao, Lili Wang

“…Subsequently, the optimal PLS model was obtained by integrating feature wavelength selection algorithms (CARS, SPA, UVE, LAR). …”
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Development and validation of a radiomics-based nomogram for predicting pathological grade of upper urinary tract urothelial carcinoma by Yanghuang Zheng, Hongjin Shi, Shi Fu, Haifeng Wang, Xin Li, Zhi Li, Bing Hai, Jinsong Zhang

“…Both LR and ML algorithms were utilized to develop predictive models. …”
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Research on the Inversion of Key Growth Parameters of Rice Based on Multisource Remote Sensing Data and Deep Learning by Jian Li, Jian Lu, Hongkun Fu, Wenlong Zou, Weijian Zhang, Weilin Yu, Yuxuan Feng

“…This study accurately inverts key growth parameters of rice, including Leaf Area Index (LAI), chlorophyll content (SPAD) value, and height, by integrating multisource remote sensing data (including MODIS and ERA5 imagery) and deep learning models. …”
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Evaluation of MODIS and VIIRS BRDF Parameter Differences and Their Impacts on the Derived Indices by Chenxia Wang, Ziti Jiao, Yaowei Feng, Jing Guo, Zhilong Li, Ge Gao, Zheyou Tan, Fangwen Yang, Sizhe Chen, Xin Dong

“…In addition, both MODIS and VIIRS have a large proportion of zero-valued pixels (volumetric and geometric-optical parameter layers), whereas the spatiotemporal distribution of zero-valued pixels in VIIRS is more widespread. …”
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A Robust Multispectral Reconstruction Network from RGB Images Trained by Diverse Satellite Data and Application in Classification and Detection Tasks by Xiaoning Zhang, Zhaoyang Peng, Yifei Wang, Fan Ye, Tengying Fu, Hu Zhang

“…However, the relatively high cost of multispectral sensors and lower spatial resolution limit the widespread application of multispectral data, and existing reconstruction algorithms suffer from a lack of diverse training datasets and insufficient reconstruction accuracy. …”
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Study on a Traditional Chinese Medicine constitution recognition model using tongue image characteristics and deep learning: a prospective dual-center investigation by Yongyue Liu, Linmiao Fan, Mei Zhao, Dongshen Wei, Menglan Zhao, Yihang Dong, Xiaoqing Zhang

“…Eight machine learning algorithms were employed to construct and evaluate the efficacy of the models. …”
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Binding Affinity Prediction for Pancreatic Ductal Adenocarcinoma Using Drug-Target Descriptors and Artificial Intelligence by Pragya, A. Amalin Prince, Jac Fredo Agastinose Ronickom

“…We achieved a mean square error (MSE) value of 1.5 using Morgan-RDKit-PubChem-Conjoint descriptors and 1D-CNN on the PDAC dataset. …”
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Prediction of Shield Tunneling Attitude Based on WM-CTA Method by GAO Su, CHEN Cheng

“…The Convolutional Neural Network (CNN) integrated with a channel-wise attention mechanism explored parameter weight differences and extracted local data features. …”
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Machine learning-based model for CD4+ conventional T cell genes to predict survival and immune responses in colorectal cancer by Zijing Wang, Zhanyuan Sun, Hengyi Lv, Wenjun Wu, Hai Li, Tao Jiang

“…These biomarkers may enhance therapeutic approaches and, in turn, elevate the clinical outcomes for patients with CRC by facilitating an integrated treatment strategy.…”
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Explainable Ensemble Learning Model for Residual Strength Forecasting of Defective Pipelines by Hongbo Liu, Xiangzhao Meng

“…Traditional machine learning algorithms often fail to comprehensively account for the correlative factors influencing the residual strength of defective pipelines, exhibit limited capability in extracting nonlinear features from data, and suffer from insufficient predictive accuracy. …”
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Inertial measurement unit technology for gait detection: a comprehensive evaluation of gait traits in two Italian horse breeds by Vittoria Asti, Michela Ablondi, Arnaud Molle, Andrea Zanotti, Matteo Vasini, Alberto Sabbioni

“…Overall, the GBM model exhibits the highest accuracy and the lowest error. In conclusion, integrating IMU technology into horse performance evaluation offers valuable insights, with implications for breeding and training.…”
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Implementasi Algoritma AES 256 CBC, BASE 64, Dan SHA 256 dalam Pengamanan dan Validasi Data Ujian Online by Ferzha Putra Utama, Gusman Wijaya, Ruvita Faurina, Arie Vatresia

“…One solution for maintaining the integrity of online-based exam results is to encrypt exam data with cryptographic methods. …”
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Identification and analysis of the endoplasmic reticulum stress hub genes in sepsis-associated ARDS by Ling Gao, Tingting Liu, Xiaoyan Li

“…The aim of this study was to identify and analyze hub genes related to ERS in sepsis-associated ARDS using bioinformatics and machine learning algorithms, which may serve as diagnostic markers and therapeutic targets. …”
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3D spectral CT-based fusion model predicts prognosis and postoperative adjuvant chemotherapy benefit in locally advanced rectal cancer by Shuxuan Fan, Jiaxin Liu, Xiaomeng Yang, Lisha Qi, Xiaomei Lu, Haiwei Liu, Xiaonan Cui

“…The SHapley Additive exPlanation (SHAP) algorithm was used to attribute interpretability to the optimal prediction model. …”
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Machine learning with the body roundness index and associated indicators: a new approach to predicting metabolic syndrome by Yaxuan He, Zekai Chen, Zhaohui Tang, Yuexiang Qin, Fang Wang

“…Objective To develop a non-invasive prediction model for MetS by integrating body roundness index (BRI), gender, age, height, and waist circumference with machine learning algorithms, and to validate its generalizability across different ethnic groups. …”
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USE OF METHODOLOGICAL TASKS IN PROFESSIONAL TRAINING OF FUTURE TEACHERS OF INFORMATICS by Nataliia S. Pavlova

“…It is established that the process of solving methodological tasks cannot be fully algorithmized in the form of a clear sequence of actions of all participants in the educational process, and, therefore, it must contain standard professional actions of teachers, elements of creative decisions, based on awareness of the value of knowledge and experience which are reached in these conditions. …”
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Computational analysis of reproducibility and image quality of 2011 and 2017 models of Heidelberg Spectralis SD-OCT machines by Kyoung A Viola Lee, Corey Tesdahl, Keith Zimmerman, Kimberly Jun, Sabrina Khalil, Alexander Shahin, Abdullah Abou-Samra, Ramesh Ayyala, Radouil Tzekov

“…Methods and testing: TRT measurements were performed using the Posterior Pole Algorithm (PPA) and Early Treatment Diabetic Retinopathy Study (ETDRS) grid protocols. …”
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