Productive automation of calibration processes for crystal plasticity model parameters via reinforcement learning by Jonghwan Lee, Burcu Tasdemir, Suchandrima Das, Michael Martin, David Knowles, Mahmoud Mostafavi

Get full text

Prediction of Key Quality Parameters in Hot Air-Dried Jujubes Based on Hyperspectral Imaging by Quancheng Liu, Chunzhan Yu, Yuxuan Ma, Hongwei Zhang, Lei Yan, Shuxiang Fan

Subjects: Get full text

Multimodal Computational Approach for Forecasting Cardiovascular Aging Based on Immune and Clinical–Biochemical Parameters by Madina Suleimenova, Kuat Abzaliyev, Ainur Manapova, Madina Mansurova, Symbat Abzaliyeva, Saule Doskozhayeva, Akbota Bugibayeva, Almagul Kurmanova, Diana Sundetova, Merey Abdykassymova, Ulzhas Sagalbayeva

Get full text

Rapid Detection of Key Phenotypic Parameters in Wheat Grains Using Linear Array Camera by Wenjing Zhu, Kaiwen Duan, Xiao Li, Kai Yu, Changfeng Shao

Subjects: Get full text

Fast determination of nutritional parameters in soil based on spectroscopic techniques by JIANG Lu-lu, ZHANG Yu, WANG Yan-yan, TAN Li-hong, HE Yong

“…It supplies a new way for the fast and accurate detection of nutritional parameters in soil.…”
Get full text

Principles of research of soil ped deformation at interaction with machine working element by V. I. Kravchuk, V. P. Davydyuk

Subjects: Get full text

A data-driven machine learning approach toward an improved maize crop production by Tosin Comfort Olayinka, Adebayo Olusola Adetunmbi, Olayinka Olumide Obe, Emmanuel Onwuka Ibam, Akinola Samson Olayinka

Subjects: Get full text

Seasonal Analysis and Machine Learning-Based Prediction of Air Pollutants in Relation to Meteorological Parameters: A Case Study from Sakarya, Türkiye by Beytullah Eren, Samiullah Serat, Yasemin Damar Arifoglu, Serkan Ozdemir

Get full text

Assessing Groundwater Level Change and Aquifer Parameters Across Los Angeles and Orange County Using InSAR Measurements and Machine Learning by Shuaiying Wu, Guoxiang Liu, Xiaowen Wang, Hongguo Jia, Yihang Ding, Bo Zhang, Wenfei Mao

Subjects: “…Aquifer parameters…”
Get full text

Experimental investigation and laser control in Ti10Mo6Cu powder bed fusion: optimizing process parameters with machine learning by Ouf A. Shams, Hanan B. Matar Al-Baity, Luttfi A. Al-Haddad

“…Abstract Laser Powder Bed Fusion (LPBF) is a key additive manufacturing technique, yet achieving optimal track formation remains a challenge due to the complex interplay of laser parameters. This study presents a hybrid experimental and machine learning (ML) approach to enhance laser control in the LPBF process for Ti10Mo6Cu alloys. …”
Get full text

Machine learning for predicting physical parameters of atom-vacancy defects from low-frequency noise in few-atom layer MoS2 by Y. Nonaka, K. Takaki, Y. Kobayashi, J. Haruyama

Get full text

Optimizing chickpea yield prediction under wilt disease through synergistic integration of biophysical and image parameters using machine learning models by RN Singh, P. Krishnan, C. Bharadwaj, Sonam Sah, B. Das

“…The objective of this study was, therefore, to assess the impact of different levels of wilt disease on the biophysical parameters of chickpea and developing machine learning (ML) models for early yield prediction. …”
Get full text

Leveraging Subjective Parameters and Biomarkers in Machine Learning Models: The Feasibility of <i>lnc-IL7R</i> for Managing Emphysema Progression by Tzu-Tao Chen, Tzu-Yu Cheng, I-Jung Liu, Shu-Chuan Ho, Kang-Yun Lee, Huei-Tyng Huang, Po-Hao Feng, Kuan-Yuan Chen, Ching-Shan Luo, Chien-Hua Tseng, Yueh-His Chen, Arnab Majumdar, Cheng-Yu Tsai, Sheng-Ming Wu

Get full text

Machine learning based prediction of geotechnical parameters affecting slope stability in open-pit iron ore mines in high precipitation zone by John Gladious, Partha Sarathi Paul, Manas Mukhopadhyay

“…Utilizing a comprehensive dataset collected before and after the monsoon, the system targets the prediction of es- sential properties including unit weight, cohesion, and friction angle—parameters significantly influenced by monsoon rains. …”
Get full text

Multi-objective optimization of laser machining parameters for carbon-glass reinforced hybrid composites: Integrating gray relational analysis, regression, and ANN by Ashish A Desai, S.N. Khan, Pooja Bagane, Sagar Dnyandev Patil

“…This research intends to optimize laser machining parameters to enhance surface quality and machining efficiency for these composites by a thorough parametric analysis. …”
Get full text

Development and validation of a machine learning model for online predicting the risk of in heart failure: based on the routine blood test and their derived parameters by Jianchen Pu, Yimin Yao, Xiaochun Wang

Get full text

NSA-CHG: An Intelligent Prediction Framework for Real-Time TBM Parameter Optimization in Complex Geological Conditions by Youliang Chen, Wencan Guan, Rafig Azzam, Siyu Chen

“…This study proposes an intelligent prediction framework integrating native sparse attention (NSA) with the Chen-Guan (CHG) algorithm to optimize tunnel boring machine (TBM) operations in heterogeneous geological environments. …”
Get full text

CINNAMON: A hybrid approach to change point detection and parameter estimation in single-particle tracking data by Jakub Malinowski, Marcin Kostrzewa, Michał Balcerek, Weronika Tomczuk, Janusz Szwabiński

“…In this paper, we propose Change poInt detectioN aNd pArameter estiMation fOr aNomalous diffusion, a hybrid approach to classifying SPT trajectories, detecting change points within them, and estimating diffusion parameters in the segments between the change points. …”
Get full text

Formation of the pediatric electroretinogram database parameters for the development of doctor’s decisionmaking algorithm by A. E. Zhdanov, A. Yu. Dolganov, V. N. Kazaykin, V. I. Borisov, V. O. Ponomarev, L. G. Dorosinsky, A. V. Lizunov, E. Luchian, X. Bao

“…The signal parameters were obtained by extracting the parameters from the wavelet scalogram of the electroretinogram signal using digital image processing and machine learning methods.…”
Get full text

Prediction of digestible energy requirement in growing finishing stage of pigs using machine learning models by Nibas Chandra Deb, Jayanta Kumar Basak, Sijan Karki, Elanchezhian Arulmozhi, Dae Yeong Kang, Niraj Tamrakar, Eun Wan Seo, Junghoo Kook, Myeong Yong Kang, Hyeon Tae Kim

Subjects: Get full text