Evaluation of Collapsibility of Compacted Loess Based on Resistivity Index by Yongpeng Nie, Wankui Ni, Haiman Wang, Kangze Yuan, Wenxin Tuo, Xiangning Li

“…Using resistivity to evaluate the collapsibility of loess is nondestructive and provides a new method to accurately and quickly evaluate the collapsibility of compacted loess.…”
Get full text

Vibration Reliability Evaluation of Main Fan Spindle Bearings by Xiaoxu Pang, Ming Qiu, Liang Ye, Lihai Chen

Get full text

Multivariate Evaluation of Flash Drought Across the United States by Jason A. Otkin, Yafang Zhong, Trent W. Ford, Martha C. Anderson, Christopher Hain, Andrew Hoell, Mark Svoboda, Hailan Wang

Get full text

Immunohistochemical Evaluation of Human Papilloma Virus in Lung Cancer by Abbas R. Ibraheem Al-Fatlawy, Liwaa H. Mahdi

Get full text

Using artificial intelligence techniques and econometrics model for crypto-price prediction by Abhidha Verma, Jeewesh Jha

“…To evaluate the performance of our chosen methods, we utilize daily historical data encompassing economic and global indices from the beginning of 2019 until the end of 2021. …”
Get full text

Predicting the Behavior of Road Users in Rural Areas for Self-Driving Cars by S. A. Ivanov, B. Rasheed

“…However, all modern prediction methods evaluate their performance only under urban conditions and do not consider their applicability to the domain of rural roads. …”
Get full text

Molecular Retrosynthesis Top‐K Prediction Based on the Latent Generation Process by Yupeng Liu, Han Zhang, Rui Hu

“…Moreover, sequence‐to‐sequence retrosynthetic prediction methods, although they enhance the flexibility of prediction, often overlook the complexity of molecular graph structures and the actual interactions between atoms, which limits the accuracy and reliability of the predictions. …”
Get full text

Trustworthy-constraint Deep Graph Learning for Enterprise Financial Risk Prediction by Wenting Ma

“…Deep learning-Based methods achieve encouraging the financial risk prediction performance due to the power ability of the feature learning. …”
Get full text

Machine Learning Algorithms for Prediction of Survival Curves in Breast Cancer Patients by Roqia Saleem Awad Maabreh, Malik Bader Alazzam, Ahmed S. AlGhamdi

“…Nonlinear relationships between variables and the impact they have on the variable to be predicted are very easy to evaluate using statistical methods. …”
Get full text

Device-Driven Service Allocation in Mobile Edge Computing with Location Prediction by Qian Zeng, Xiaobo Li, Yixuan Chen, Minghao Yang, Xingbang Liu, Yuetian Liu, Shiwei Xiu

“…To validate the effectiveness of the proposed methods, we conduct multiple controlled experiments focusing on both location prediction models and service allocation algorithms. …”
Get full text

Quality Prediction Model Based on Novel Elman Neural Network Ensemble by Lan Xu, Yuting Zhang

“…Simulations were conducted to compare the proposed method with other NN methods and evaluate its performance. …”
Get full text

Evaluating the diagnostic efficiency of ultrasound and serum autoantibodies in Hashimoto’s thyroiditis: a cross-sectional study by Hai-Long Tan, Huan Ge, Zi-En Qin, Ya-Ling Jiang, Shi Chang, Neng Tang

Get full text

Transformer network for time series prediction via wavelet packet decomposition by Zhichao Wu, Aiye Shi, Yan Ping Tao

“…Although, conventional time series processing methods—such as multi-scale feature extraction or Transformer-based algorithms—produce superior prediction results, when dealing with data that contain morenoise and outliers, the prediction ability of such methods can suffer. …”
Get full text

Fair and Transparent Student Admission Prediction Using Machine Learning Models by George Raftopoulos, Gregory Davrazos, Sotiris Kotsiantis

“…This paper explores the development and evaluation of machine learning models designed to predict student admissions while prioritizing fairness and interpretability. …”
Get full text

Near-infrared spectroscopy analysis to predict urinary allantoin in dairy cows by Leonardo A.C. Ribeiro, Guilherme L. Menezes, Tiago Bresolin, Sebastian I. Arriola Apelo, Joao R.R. Dórea

“…The raw spectra were preprocessed using scatter correlation methods and spectral derivatives. The partial least squares regression model achieved an R2 of 0.55, a concordance correlation coefficient of 0.73, and a root mean squared error of prediction (RMSEP) of 3.63 mmol/L to predict allantoin concentration from the spectra data set without preprocessing. …”
Get full text

Prediction of mortality with unmeasured anions in critically ill patients on mechanical ventilation by Novović Miloš N., Jevđić Jasna

“…AG represented a model with imprecise calibration, i.e. a model with little predictive power. APACHE II had p-value more than 0.05 if it was near it, and therefore it could be considered potentially unreliable for outcome prediction. …”
Get full text

Predicted oxaloacetate activity, gene expression and viability of human dermal fibroblasts by Nataliya A. Kolotyeva, Larisa V. Limareva, Frida N. Gilmiyarova, Violetta V. Boltovskaya, Pavel V. Ilyasov, Oksana A. Gusyakova, Vasily V. Remizov

“…Material and Methods — We predicted biological activity of oxaloacetate using in silico methods. …”
Get full text

MHC2-SCALE enhances identification of immunogenic neoantigens by Joshua G. Gober, Aude-Hélène Capietto, Reyhane Hoshyar, Martine Darwish, Richard Vandlen, Jonathan L. Linehan, Lélia Delamarre, Adel M. ElSohly

Get full text

Personality traits prediction based on eye movements while reading manga by Yuichi Wada

“…BackgroundPrevious studies utilizing machine learning methods have demonstrated that personal traits can be predicted from eye movement data recorded in real-world situations, such as navigating a university campus or browsing one’s Facebook news feed. …”
Get full text

Deep learning approaches for time series prediction in climate resilience applications by Cai Chen, Jin Dong

“…ED-CAS complements this by embedding equity considerations into resource allocation, ensuring that resilience-building efforts prioritize vulnerable populations and regions.ResultsExperimental evaluations on climate datasets demonstrate that our approach significantly improves forecasting accuracy, resilience indices, and equitable resource distribution compared to traditional models.DiscussionBy integrating predictive analytics with optimization and equity-driven strategies, this framework provides actionable insights for climate adaptation, advancing the development of scalable and socially just resilience solutions.…”
Get full text