Research on an Apple Recognition and Yield Estimation Model Based on the Fusion of Improved YOLOv11 and DeepSORT by Zhanglei Yan, Yuwei Wu, Wenbo Zhao, Shao Zhang, Xu Li

Get full text

A Novel Fault Diagnosis Method for Rolling Bearing Based on Improved Sparse Regularization via Convex Optimization by Dongjie Zhong, Cancan Yi, Han Xiao, Houzhuang Zhang, Anding Wu

Get full text

Clinical effectiveness of routine first‐trimester combined screening for pre‐eclampsia in Spain with the addition of placental growth factor by Pablo Garcia‐Manau, Erika Bonacina, Berta Serrano, Sara Caamiña, Marta Ricart, Eva Lopez‐Quesada, Àngels Vives, Monica Lopez, Elena Pintado, Anna Maroto, Sara Catalan, Marta Dalmau, Ester Del Barco, Alina Hernandez, Marta Miserachs, Marta San Jose, Mireia Armengol‐Alsina, Elena Carreras, Manel Mendoza

“…A greater treatment adherence resulted in a significant reduction in adverse outcomes. Conclusions Routine first‐trimester screening for pre‐eclampsia with placental growth factor leads to a reduction in preterm pre‐eclampsia and other pregnancy complications. …”
Get full text

A rolling bearing fault diagnosis method based on GADF-CWT-GCNN by ZHANG Xiaoli, LUO Xin, LI Min, LIANG Wang, WANG Fangzhen

Get full text

Daily runoff forecasting using novel optimized machine learning methods by Peiman Parisouj, Changhyun Jun, Sayed M. Bateni, Essam Heggy, Shahab S. Band

“…In the Carson River, the GB model achieves the highest forecasting accuracy, which is significantly improved by ARO, resulting in a 24.8 % reduction in root mean square error (RMSE). The MLP model also benefits notably from ARO, with RMSE improvements of 4.8 % and a substantial 48.9 % reduction in mean absolute error (MAE). …”
Get full text

Fine-scale carbon stocks mapping in the mangrove forests of Tumaco, Colombia using machine learning and remote sensing approaches by Laura Lozano-Arias, Bryan Ernesto Gallego-Pérez, John Josephraj Selvaraj

“…Additionally, spectral indices significantly enhanced the model’s ability to predict aboveground biomass.…”
Get full text

Crowd anomaly estimation and detection: A review by A. Hussein, M.W. Raed, A. Al-Shaikhi, M. Mohandes, B. Liu

“…We present a comprehensive literature review on crowd anomaly detection using disruptive technologies such as radio frequency identification, wireless sensor networks, Wi-Fi, and Bluetooth low energy, employing device-free noninvasive algorithms based on received signal strength indicator variations to detect the speed and direction of a moving crowd to predict the onset of a stampede. …”
Get full text

Deep-Learning and Dynamic Time Warping-Based Approaches for the Diagnosis of Reactor Systems by Hoejun Jeong, Jihyun Kim, Doyun Jung, Jangwoo Kwon

“…The experiment results demonstrate that the size and position of clamping force degradation can be accurately predicted. It is expected that this research will contribute to enhancing the precision and efficiency of internal structure monitoring in nuclear power plants.…”
Get full text

Early Detection of Parkinson’s Disease Using AI Techniques and Image Analysis by Marilena Ianculescu, Corina Petean, Virginia Sandulescu, Adriana Alexandru, Ana-Mihaela Vasilevschi

“…Methods: The best approach is selected to be integrated in a neurodegenerative disease management platform called NeuroPredict. The most innovative aspects of the presented approaches are related to the employed feature extraction techniques that convert hand-drawn spirals into a frequency spectra, so that frequency features may be extracted and utilized as inputs for various classification algorithms. …”
Get full text

Artificial intelligence in soil science: Where do we go now? by Jose Pablo Castro, Caley K. Gasch, Paulo Flores

“…Core Ideas Artificial intelligence (AI) is changing soil science with advanced analytic and predictive modeling tools. Ethical AI in soil science should focus on data integrity, privacy, and transparent research. …”
Get full text

Optimizing Energy Supply for Full Electric Vehicles in Smart Cities: A Comprehensive Mobility Network Model by Victor Fernandez, Virgilio Pérez, Rosa Roig

“…This study presents a comprehensive mobility network model designed to predict and optimize the energy supply for FEVs within smart cities. …”
Get full text

METHODOLOGY OF PRACTICE-ORIENTED RESEARCH ACTIVITIES OF STUDENTS DURING PEDAGOGICAL INTERNSHIP: BUILDING NATIONAL IDENTITY IN MULTICULTURAL ENVIRONMENT by Tatyana L. Oskolova

“…Proposed investigation is based on formal requirements of national education including analysis of specific educational activities in ethnically and culturally diverse society.Methods. …”
Get full text

Restoring Force Model of an Energy-Dissipation Joint in Hybrid Frames: Simplified Skeleton Curve and Hysteretic Rules by Yanhua Wang, Yan Feng, Dongsheng Huang, Zirui Huang, Zhongfan Chen

Get full text

Apple Variety Identification Using Near-Infrared Spectroscopy by Caihong Li, Lingling Li, Yuan Wu, Min Lu, Yi Yang, Lian Li

“…Especially, the SPA-ELM model could reach 98.33% identification accuracy on the calibration set and 96.67% on the prediction set. This study suggests that it is feasible to identify apple variety and cultivation region by using NIR spectroscopy.…”
Get full text

Robust time series analysis for forecasting photovoltaic energy yield by Sapundzhi Fatima, Chikalov Aleksandar, Georgiev Slavi, Georgiev Ivan, Todorov Venelin

“…This study introduces an approach to forecasting the power output of a photovoltaic (PV) system by employing an ARIMA-based algorithm. Two distinct ARIMA models were designed – one generated via SPSS and one selected by the researchers. …”
Get full text

Clinicopathological study of adrenal pheochromocytoma and extra-adrenal paragangliomas with reference to GAPP and PASS scoring systems by Akash Mondal, Moumita Sengupta, Soumya Dey, Anish Kar, Krishnendu Maiti, Debansu Sarkar, Uttara Chatterjee

“…Pheochtomocytoma of adrenal gland scaled score (PASS) and the grading of adrenal pheochromocytoma and paraganglioma (GAPP) score are two histological algorithms used to predict metastatic potential, but neither has been regarded as ‘gold-standard’. …”
Get full text

Hexapod robot motion planning investigation under the influence of multi-dimensional terrain features by Chen Chen, Chen Chen, Junbo Lin, Junbo Lin, Bo You, Bo You, Jiayu Li, Jiayu Li, Biao Gao, Biao Gao

Get full text

Field calibration of fine particulate matter low-cost sensors in a highly industrialized semi-arid conurbation by Mariana Villarreal-Marines, Michael Pérez-Rodríguez, Yasmany Mancilla, Gabriela Ortiz, Alberto Mendoza

“…We also tested the Extreme Gradient Boosting (XGBoost) algorithm for classification and field calibration of the PM2.5 data derived from the LCS. …”
Get full text

An Innovative Proposal for Developing a Dynamic Urban Growth Model Through Adaptive Vector Cellular Automata by Ahmet Emir Yakup, Ismail Ercument Ayazli

“…For the simulation phase, an adaptive VCA-based urban growth model was developed to predict LULC changes through to 2040. The results demonstrate that the proposed algorithm can achieve a satisfactory level of accuracy in modeling urban growth.…”
Get full text

From word models to executable models of signaling networks using automated assembly by Benjamin M Gyori, John A Bachman, Kartik Subramanian, Jeremy L Muhlich, Lucian Galescu, Peter K Sorger

“…Abstract Word models (natural language descriptions of molecular mechanisms) are a common currency in spoken and written communication in biomedicine but are of limited use in predicting the behavior of complex biological networks. …”
Get full text