High-Precision Phenotyping in Soybeans: Applying Multispectral Variables Acquired at Different Phenological Stages by Celí Santana Silva, Dthenifer Cordeiro Santana, Fábio Henrique Rojo Baio, Ana Carina da Silva Cândido Seron, Rita de Cássia Félix Alvarez, Larissa Pereira Ribeiro Teodoro, Carlos Antônio da Silva Junior, Paulo Eduardo Teodoro

“…This reinforces that the use of different specific spectra for each model can enhance accuracy, optimizing the choice of model according to the phenological stage of the plants.…”
Get full text

Dynamic Modeling and Nonlinear Vibration Research of the Rotary Cutting Mechanism Based on Bond Graphs by Zhao Jiayi, Gao Yiyang, Zhao Changzhen, Rao Xiaobo, Ding Shunliang, Gao Jianshe

“…The results provide reference for the subsequent dynamic performance optimization and vibration suppression of the mechanism.…”
Get full text

A Neural Network Constitutive Model and Automatic Stiffness Evaluation for Multiscale Finite Elements by Aliki D. Mouratidou, Georgios E. Stavroulakis

Get full text

Semi-supervised Fault Diagnosis of Refrigeration System Based on Tri-Training by Ren Zhengxiong, Han Hua, Cui Xiaoyu, Lu Hailong, Zhang Yunqian

Get full text

Mid-infrared spectra of dried and roasted cocoa (Theobroma cacao L.): A dataset for machine learning-based classification of cocoa varieties and prediction of theobromine and caffe... by Gentil A. Collazos-Escobar, Andrés F. Bahamón-Monje, Nelson Gutiérrez-Guzmán

“…This dataset provides a basis for further research, enabling the integration of mid-infrared spectral data with HPLC (as a standard) to fine-tune machine learning and deep learning models that could be used to simultaneously predict the theobromine and caffeine content, as well as cocoa variety in both dried and roasted cocoa samples using a non-destructive approach based on spectral data. …”
Get full text

Comparative analysis of supervised learning models for effluent quality prediction in wastewater treatment plants. by Liu Bo-Qi, Zhou Ding-Jie, Zhao Yang, Shi Long-Yu

“…Nevertheless, the findings provide valuable insights into selecting effective machine learning models for effluent quality prediction, supporting data-driven decision-making in wastewater management and advancing intelligent process optimization in WWTP.…”
Get full text

Driving enhanced exciton transfer by automatic differentiation by E Ballarin, D A Chisholm, A Smirne, M Paternostro, F Anselmi, S Donadi

Get full text

A novel stochastic approach for reliable design of advanced frugal products by Balkrishna C. Rao

“…This approach can be applied to any part/product in any sector and is suitable for use with machine learning.…”
Get full text

Prediction and optimization of Rhodamine B removal from water using metal-organic frameworks: RSM-CCD, ANN, non-linear kinetics, and isotherm studies by Simon Bbumba, John Ssekatawa, Ibrahim Karume, Emmanuel Tebandeke, Moses Kigozi, Solomon Yiga, Robert Setekera, Joseph Ssebuliba, Steven Sekitto, Ruth Mbabazi, Ivan Kiganda, Maximillian Kato, Patrick Taremwa, Moses Murungi, Chinaecherem Tochukwu Arum, Collins Yiiki Letibo, Geofrey Kaddu, Margret Namugwanya, John Kusasira, Peace Mwesigwa, Muhammad Ntale

“…Artificial intelligence models such as Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) were used to predict and optimize the adsorptive removal of Rhodamine B (RhB) from water. …”
Get full text

Utilising AI technique to identify depression risk among doctoral students by Changhong Teng, Chunmei Yang, Qiushi Liu

Get full text

Bathymetry Inversion Using a Deep‐Learning‐Based Surrogate for Shallow Water Equations Solvers by Xiaofeng Liu, Yalan Song, Chaopeng Shen

Get full text

Investigation of Freeway Incident Duration Using Classification and Regression Trees Based on Multisource Data by Xun Xie, Gen Li, Lan Wu, Shuxin Du

Get full text

Enhancing Sustainable Manufacturing in Industry 4.0: A Zero-Defect Approach Leveraging Effective Dynamic Quality Factors by Rouhollah Khakpour, Ahmad Ebrahimi, Seyed Mohammad Seyed Hosseini

“…<a href="#_ENREF_16">Mourtzis et al. (2021)</a> focus on ZDM by equipment design optimization and propose an approach relying on the integration of DT for simulation of new design based on historical data gathered from already installed similar machines and production environment.…”
Get full text

Anomaly Detection for Aviation Cyber-Physical System: Opportunities and Challenges by Qurrat Ul Ain, Atif Aftab Ahmed Jilani, Nigar Azhar Butt, Shafiq Ur Rehman, Hisham Abdulrahman Alhulayyil

“…The findings suggest several directions for future research, including developing standardized datasets, optimizing hybrid models, and integrating explainable AI (XAI) to enhance model interpretability. …”
Get full text

Assessing the Impact of Climate Change on Winter Wheat Production in the North China Plain from 1980 to 2020 by Jinhui Zheng, Shuai Zhang

Get full text

Multi-Feature Facial Complexion Classification Algorithms Based on CNN by Xiyuan Cao, Delong Zhang, Chunyang Jin, Zhidong Zhang, Chenyang Xue

“…The comprehensive evaluation reveals that multi-feature fusion and splicing classification algorithms achieve accuracies of 95.98% and 93.76%, respectively. The optimal approach combining multi-feature CNN with machine learning algorithms attains a remarkable accuracy of 97.78%. …”
Get full text

Inversion model of stress state reconstruction for geological hazard pipelines based on digital twin by Xue Luning, Tian Mingliang, Zhao Juncheng

“…The mechanical state of the physical pipeline is mapped in real time by the digital twin, the numerical simulation and multi-source monitoring data are integrated, and the parameters of the twin model are dynamically optimized by combining the optimization algorithms of Particle Swarm Optimization (PSO) and Support Vector Machine (SVM), so as to realize the real-time prediction of the pipeline stress state and the dynamic updating of the disaster scenario. …”
Get full text

Near Miss Detection Using Distancing Monitoring and Distance-Based Proximal Indicators by Lek Ming Lim, Lu Yang, Wen Zhu, Ahmad Sufril Azlan Mohamed, Majid Khan Majahar Ali

Get full text

Intelligent Reflecting Surface-Assisted Wireless Communication Using RNNs: Comprehensive Insights by Rana Tabassum, Mohammad Abrar Shakil Sejan, Md Habibur Rahman, Md Abdul Aziz, Hyoung-Kyu Song

“…In IRS-assisted communication systems, accurate channel estimation is crucial for optimizing signal transmission and achieving high spectral efficiency. …”
Get full text

Integrating genomics & AI for precision crop monitoring and adaptive stress management by Rajesh Polegopu, Satya Sumanth Vanapalli, Sashi Vardhan Vanapalli, Naga Prudvi Diyya, Mounika Vandila, Divya Valluri, Anjali Peddinti, Sowjanya Saladi, Meghana Pyla, Padmini Gelli

“…Machine learning models continuously adapt by learning from historical and real-time data, making recommendations more precise over time. …”
Get full text