Generalized perception of tree-row with distribution-peak feature in 3D point cloud for various orchards navigation by Yingxing Jiang, Wuhao Li, Jizhan Liu, Muhammad Mahmood ur Rehman, Binbin Xie, Jie Wang

Get full text

Ensemble Learning-Driven and UAV Multispectral Analysis for Estimating the Leaf Nitrogen Content in Winter Wheat by Yu Han, Jiaxue Zhang, Yan Bai, Zihao Liang, Xinhui Guo, Yu Zhao, Meichen Feng, Lujie Xiao, Xiaoyan Song, Meijun Zhang, Wude Yang, Guangxin Li, Sha Yang, Xingxing Qiao, Chao Wang

Get full text

Automated and Enhanced Classification of Persea Americana Using Optimized Deep Convolutional Neural Networks With Improved Training Strategies for Agro-Industrial Settings by Oscar Vera, Jose Cruz, Severo Huaquipaco, Wilson Mamani, Victor Yana-Mamani, Saul Huaquipaco

“…These promising results open new possibilities for the implementation of machine learning in the agri-food industry. For future research, the possibility of expanding the data set and extending the application of this model to other varieties of fruits is proposed.…”
Get full text

AI-Driven Mapping System for Smart Parking Management Applications Using an INS-GNSS-Solid-State LiDAR-Monocular Camera Fusion Engine Empowered by HD Maps by Kai-Wei Chiang, Syun Tsai, Jou-An Chen, Surachet Srinara, Meng-Lun Tsai, Chih-Yun Hsieh, Jyun-Yang Hung, Chalermchon Satirapod, Naser El-Sheimy

Get full text

Automatic Evaluation of Bone Age Using Hand Radiographs and Pancorporal Radiographs in Adolescent Idiopathic Scoliosis by Ifrah Andleeb, Bilal Zahid Hussain, Julie Joncas, Soraya Barchi, Marjolaine Roy-Beaudry, Stefan Parent, Guy Grimard, Hubert Labelle, Luc Duong

“…<b>Results:</b> The model achieves an average mean absolute error (MAE) of 4.87 months on more than 250 clinical testing AIS patient dataset. …”
Get full text

Deep Learning-Based Cascaded Light Source Detection for Link Alignment in Underwater Wireless Optical Communication by Bowen Jia, Wenmin Ge, Jingxuan Cheng, Zihao Du, Renming Wang, Guangbin Song, Yufan Zhang, Chengye Cai, Sitong Qin, Jing Xu

“…On the ULDB test set, the proposed detection method achieves an average precision (AP) of 99.1&#x0025; and an average positioning error of 4.66 pixels, while the traditional method may frequently extract false light spots. …”
Get full text

A Composite Barrier Function Sliding Mode Control Method Based on an Extended State Observer for the Path Tracking of Unmanned Articulated Vehicles by Kanghua Zhang, Xiaochao Gu, Nan Wang, Jialu Cao, Jixin Wang, Shaokai Zhang, Xiang Li

“…Afterward, based on the error compensation theory, a composite barrier function sliding mode controller suitable for articulated vehicle path tracking is derived. …”
Get full text

Deep learning-based thermal modeling of slipping velocity in oblique magnetohydrodynamic non-Newtonian nanofluid flows by Nek Muhammad Katbar, Hina Zahir, Kamel Guedri, Basim M. Makhdoum, Siti Suzilliana Putri Mohamed Isa, Syed M. Hussain, Abbas Khan

Get full text

Accuracy of Measurement Tools for Ocular-Origin Anomalous Head Posture and the Cervical Range of Motion Kinematics in Children with an Anomalous Head Position by Serena Cerfoglio, Francesco Bonsignore, Giuseppina Bernardelli, Lucia Donno, Fabiana Aili, Manuela Galli, Francesca Nucci, Edoardo Villani, Paolo Nucci, Veronica Cimolin

“…Pearson’s correlation coefficient (PCC), root mean square error (RMSE), and Bland–Altman plots assessed inter-system agreement, while MoCap analyzed cervical ROM. …”
Get full text

A comparative artificial neural networks for Schwarzschild black hole (SBH) radius by Khalil Ur Rehman, Wasfi Shatanawi, Weam G. Alharbi

“…It is consensus among researchers that the data for the black holes is complicated and extremely non-linear in nature. …”
Get full text

A guidebook for DISCO tissue clearing by Muge Molbay, Zeynep Ilgin Kolabas, Mihail Ivilinov Todorov, Tzu‐Lun Ohn, Ali Ertürk

“…Abstract Histological analysis of biological tissues by mechanical sectioning is significantly time‐consuming and error‐prone due to loss of important information during sample slicing. …”
Get full text

T-S Fuzzy System Controller for Stabilizing the Double Inverted Pendulum by Boutaina Elkinany, Mohammed Alfidi, Redouane Chaibi, Zakaria Chalh

“…This article provides a representation of the double inverted pendulum system that is shaped and regulated in response to torque application at the top rather than the bottom of the pendulum, given that most researchers have controlled the double inverted pendulum based on the lower part or the base. …”
Get full text

Deviations of Boundary Layer Height and Meteorological Parameters Between Ground-Based Remote Sensing and ERA5 over the Complex Terrain of the Mongolian Plateau by Yiming Wei, Yankun Sun, Yongjing Ma, Yulong Tan, Xinbing Ren, Kecheng Peng, Simin Yang, Zhong Lin, Xingjun Zhou, Yuanzhe Ren, Masroor Ahmed, Yongli Tian, Jinyuan Xin

“…Results indicate that ERA5 exhibits significant biases in horizontal wind speed, with deviations ranging from −5 to 8 m/s at 50 m, primarily driven by sandstorms in winter and convective weather in summer. The most pronounced errors occur below 500 m. Vertical wind speeds are consistently underestimated in both seasons, with biases reaching up to 1 m/s, particularly during active summer convection. …”
Get full text

Feature Selection Using a Genetic Algorithms and Fuzzy logic in Anti-Human Immunodeficiency Virus Prediction for Drug Discovery by Houda Labjar, Mohammad Al-Sarem, Mohamed Kissi

Get full text

Effects of a GenAI-based debugging approach integrating the reflective strategy on senior high school students’ learning performance and computational thinking by Jian-Wen Fang, Jing Chen, Qiu-Lin Weng, Yun-Fang Tu, Gwo-Jen Hwang and Yi-Chen Xia

“…However, debugging tools embedded in integrated development environments (IDEs) often provide limited error diagnosis, which may reduce students’ engagement with coding and inhibit their learning performances. …”
Get full text

Mathematical Modelling of a Friction Stir Welding Process to Predict the Joint Strength of Two Dissimilar Aluminium Alloys Using Experimental Data and Genetic Programming by Mohammed Yunus, Mohammad S. Alsoufi

“…The obtained results from the GP models showed good agreement with experimental and target data at an average prediction error of 0.72%.…”
Get full text

Computer vision systems and deep learning for the recognition of athlete's movement: A review article by Ahmed S. Abdullah, Khalil Ibrahim Alsaif

“…Reviewing the articles demonstrates that relying on computer vision systems is more effective than relying on human rulers, as humans are more prone to error. As for relying on the deep learning techniques for detecting the object, the results are very positive, due to the correct detection of the object. …”
Get full text

Engineering method of calculation temperature fields and thermal stresses in the initial stage of radiation convection heating (cooling) body with variable heat transfer coefficien... by Gorbunov A.D., Uklеina S.V.

“…It is shown that the error in determining the surface temperature does not exceed 6%, and that the developed method can be used up to Fourier numbers Fo<0.4…”
Get full text

Measuring the Effective Factors in the Non-Development of the Sustainable Smart City of Tabriz by Ali Zeynali Azim, Mehri Fadaei Haghi, Amin Alizadeh, Mohammad Jodeiri Abbasi, Reza Fathipour, Mohammadali Sharifi

“…The value of the root mean square error of estimation (RMSEA) was 0.057, which is acceptable considering that it is smaller than 0.08, and it indicates the confirmation of the research model. …”
Get full text

Modeling the compressive strength behavior of concrete reinforced with basalt fiber by Kennedy C. Onyelowe, Ahmed M. Ebid, Shadi Hanandeh, Viroon Kamchoom, Paul Awoyera, Siva Avudaiappan

“…Taylor chart for measured compressive strength of basalt fiber reinforced concrete predicted with ANN, KNN, SVM, Tree and RF is presented for comparing the performance of predictive models by illustrating three key statistical measures simultaneously: the correlation coefficient (R), the normalized standard deviation (σ), and the root-mean-square error (RMSE). Finally, it can be deduced that after considering the performance indices of the selected ensemble and classification models utilized in this present research paper, all the developed modes have almost the same excellent level of accuracy 95%, but ANN, KNN, and SVR produced R2 of 0.98 each with KNN producing MAE of 1.4 MPa, and MSE of 2.5 MPa to outperform ANN and SVR which produced MAE of 1.55 MPa/MSE of 4.1 MPa and MAE of 1.6 MPa/MSE of 3.85 MPa, respectively. …”
Get full text