Study on Electric Power Fittings Identification Method for Snake Inspection Robot Based on Non-Contact Inductive Coils by Zhiyong Yang, Jianguo Liu, Shengze Yang, Changjin Zhang

“…Then, the concept of condition number and singular value decomposition (SVD) are introduced to analyse the impact of detection position on classification accuracy, with optimal detection positions found using the particle swarm optimization algorithm. …”
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Air pressure forecasting for the Mutriku oscillating‐water‐column wave power plant: Review and case study by Jorge Marques Silva, Susana M. Vieira, Duarte Valério, João C. C. Henriques, Paul D. Sclavounos

“…Abstract The high variability and unpredictability of renewable energy resources require optimization of the energy extraction, by operating at the best efficiency point, which can be achieved through optimal control strategies. …”
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Enhancing Crop Yield Prediction Using IoT-Based Soil Moisture and Nutrient Sensors by Alsalami Zaid, Mohammed G., Srinivas Tummala

“…Crop yield prediction is crucial for ensuring food security by enabling farmers to optimize resource use, manage risks, and plan for market demands, ultimately leading to increased agricultural productivity and sustainability..The IoT-based crop yield prediction system integrates advanced sensing technologies, communication protocols, machine learning algorithms, and real-time monitoring to optimize crop production. …”
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Effects of normal stress on shear properties and acoustic emission characteristics of bonded rock-concrete interfaces by Yan Chen, Jiangfan Yang, Jintao Wang, Shuai Heng, Zhiqiang Hou

“…Additionally, the proportion of shear damage signals in specimens, as determined by the joint Gaussian Mixture Model (GMM) and Support Vector Machine (SVM), was found to exceed 75% and to rise with higher normal stress levels. …”
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Enhancing security in electromagnetic radiation therapy using fuzzy graph theory by Radhey Lal, Rajiv Kumar Singh, Dinesh Kumar Nishad, Saifullah Khalid

“…The study also identifies key directions for future research, including machine learning integration, blockchain implementation, and scalability optimization.…”
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Research on the impact of green finance on regional carbon emission reduction and its role mechanisms by Huiyun Li, Zongbao Yu, Gang Chen, Yingjun Nie

“…Therefore, taking the green financial reform and innovation pilot zone as a quasi-natural experiment, we select 270 cities from 2010 to 2021 as research samples and empirically assess the effects of the green finance policy on reducing regional carbon emissions through the double debiased machine learning (DDML) model. This study demonstrates that (1) green finance policy plays a significant role in promoting regional carbon emission reduction, and this conclusion remains valid after a variety of robustness tests; (2) the mechanism of action indicates that green finance policy contributes to regional carbon emission reduction by supporting green technological innovation and promoting the optimization of the industrial structure; (3) the analysis of heterogeneity reveals that green finance policy has a more pronounced effect on carbon emission reduction in the eastern region and in non-resource-based cities than in the central and western regions and in resource-dependent cities; and (4) the pilot policy of “Broadband China”, the pilot policy of information consumption, and the comprehensive experimental zone of big data has a synergistic effect on carbon reduction and emission reduction with green finance policy. …”
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Mechanical Impedance Control in the Human Arm While Manually Transporting an Open-Top Fluid Filled Dish by Navit Roth, Rami Seliktar, Joseph Mizrahi

“…These results can help in the optimization of manual materials handeling tasks in industrial settings as well as future design of prosthetic arms, robotic appliances and man machine interfacing devices.…”
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THE PROBLEM OF ENERGY EFFICIENCY OF SYSTEMS BASED ON ARTIFICIAL INTELLIGENCE OF THE INTERNET OF THINGS (AIOT) by С. В. Войтко

“…AIoT energy efficiency can be ensured on the basis of the following: selection of machine learning methods, hardware improvement, software optimization, network planning, effective model design, and energy consumption testing with subsequent conclusions for comprehensive improvement. …”
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A control strategy for shipboard stabilization platforms based on a fuzzy adaptive proportional–integral–derivative (PID) control architecture by H. Liu, Z. Zeng, X. Yang, Y. Zou, X. Liu

“…The research advances marine stabilization technology through mechanical optimization via virtual-work modeling and control enhancement via fuzzy–PID synthesis. …”
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Waveshift Augmentation: A Physics-Driven Strategy in Fine-Grained Plant Disease Classification by Gent Imeraj, Hitoshi Iyatomi

“…Recent advancements in computer vision and machine learning enable automatic and precise plant disease diagnosis. …”
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Smart extrusion via data-driven prediction of grain size and peripheral coarse grain defect formation by Marco Negozio, Lorenzo Donati, Adrian H. A. Lutey

“…Over 22,000 data points were collected from two distinct AA6082 aluminum alloy profiles with different geometries, extruded over a range of different process conditions. Hyperparameter optimization of artificial neural networks (ANNs) for regression and prediction was performed, with ANN outcomes benchmarked against existing analytical models. …”
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Dual level dengue diagnosis using lightweight multilayer perceptron with XAI in fog computing environment and rule based inference by Deepika R., Pradeep Kumar T.S.

“…A variety of metrics have been computed to assess the effectiveness of the model. Since the suggested model is a “black box,” explainable artificial intelligence (XAI) tools such as SHAP and LIME have been used to help explain its predictions. …”
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Construction and Application of Intelligent O&M System for Urban Rail Transit Signaling Systems by YU Meng, LU Huaike, LIANG Zhe, FAN Zichao, GAO Ning

“…[Result & Conclusion] In the engineering application of Nanning Rail Transit Line 4, this intelligent system promotes three major transformations in the O&M model: from passive response to proactive prevention, from experience-driven to data-driven, and from fragmented management to coordinated optimization. …”
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Integrated neural network and evolutionary algorithm approach for liver fibrosis staging: Can artificial intelligence reduce patient costs? by Ali Nazarizadeh, Touraj Banirostam, Taraneh Biglari, Mohammadreza Kalantarhormozi, Fatemeh Chichagi, Amir H Behnoush, Mohammad A Habibi, Ramin Shahidi

“…Besides, the diagnostic accuracy of all methods, except the model designed with the Bayesian network, increases when the SMOTE balancer is applied. …”
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A Novel Approach to Pine Nut Classification: Combining Near-Infrared Spectroscopy and Image Shape Features with Soft Voting-Based Ensemble Learning by Yueyun Yu, Xin Huang, Danjv Lv, Benjamin K. Ng, Chan-Tong Lam

“…Pine nuts hold significant economic value due to their rich plant protein and healthy fats, yet precise variety classification has long been hindered by limitations of traditional techniques such as chemical analysis and machine vision. This study proposes a novel near-infrared (NIR) spectral feature selection algorithm, termed the improved binary equilibrium optimizer with selection probability (IBiEO-SP), which incorporates a dynamic probability adjustment mechanism to achieve efficient feature dimensionality reduction. …”
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Enhancing stroke risk prediction through class balancing and data augmentation with CBDA-ResNet50 by Muhammad Asim Saleem, Ashir Javeed, Wasan Akarathanawat, Aurauma Chutinet, Nijasri Charnnarong Suwanwela, Pasu Kaewplung, Surachai Chaitusaney, Watit Benjapolakul

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Analisis Sentimen Berbahasa Inggris Dengan Metode Lstm Studi Kasus Berita Online Pariwisata Bali by Ngakan Made Krisna Sedana, I Nyoman Saputra Wahyu Wijaya, I Ketut Resika Arthana

“…Analisis sentimen dilakukan menggunakan model machine learning LSTM (Long-Term Memory), dengan data berita yang telah diberi label sentimen oleh pakar sesuai dengan isi berita. …”
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Material informatics-driven insights into brain cancer nanocarriers: A bibliometric comparison of PLGA vs. liposomes by Brilly Andro Makalew, Syauqi Abdurrahman Abrori

“…These improvements are crucial for effective delivery across the blood-brain barrier, a major challenge in brain cancer treatment.The integration of computational modelling, machine learning, and high-throughput screening enabled by material informatics is shown to be a key factor in advancing the design and optimization of these nanocarriers. …”
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Reconstruction of beam parameters and betatron radiation spectra measured with a Compton spectrometer by M. Yadav, M. H. Oruganti, B. Naranjo, S. Zhang, G. Andonian, Y. Zhuang, Ö. Apsimon, C. P. Welsch, J. B. Rosenzweig

“…This capacity is critical to understanding intense beam propagation and its optimization in plasma.…”
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Robust biochar yield and composition prediction via uncertainty-aware ResNet-based autoencoder by Yali Zhang, Bowen Lei, Amirhossein Mahdaviarab, Xiao Wang, Zong Liu

“…Additionally, robust sensitivity analyses of the input covariates revealed the impact of data uncertainty on the performance of the model, emphasizing the robustness of the model. In advancing the application of machine learning in biochar research, this study provides a reliable method to determine optimal production conditions. …”
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