Applying Machine Learning for Sustainable Farm Management: Integrating Crop Recommendations and Disease Identification by P. Ankit Krishna, Neelamadhab Padhy, Archana Patnaik

“…To suggest appropriate crops and detect pertinent plant diseases, cutting-edge machine learning and deep learning algorithms were used. Real-time data from Internet of Things sensors and high-resolution camera photos were used to identify diseases. …”
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The effects of limb position and grasped load on hand gesture classification using electromyography, force myography, and their combination. by Peyton R Young, Kihun Hong, Eden J Winslow, Giancarlo K Sagastume, Marcus A Battraw, Richard S Whittle, Jonathon S Schofield

“…A prominent control technique employs surface electromyography (EMG) and pattern recognition algorithms to identify specific patterns in muscle electrical activity and translate these to device commands. …”
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An Optimised CNN Hardware Accelerator Applicable to IoT End Nodes for Disruptive Healthcare by Arfan Ghani, Akinyemi Aina, Chan Hwang See

“…In the evolving landscape of computer vision, the integration of machine learning algorithms with cutting-edge hardware platforms is increasingly pivotal, especially in the context of disruptive healthcare systems. …”
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Method for Two-Stage Radar Measurement of the Blade Repetition Rate of a Propeller-Driven Aircraft by S. R. Heister, V. V. Kirichenko

“…Such images can be obtained using algorithms based on an inverse antenna aperture synthesis. …”
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Single-cell and multi-omics analysis reveals the role of stem cells in prognosis and immunotherapy of lung adenocarcinoma patients by Jianan Zheng, Haoran Lin, Wei Ye, Mingjun Du, Chenjun Huang, Jun Fan

“…Multiple machine learning algorithms were systematically compared in order to develop an optimal prognostic model. …”
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Methodical approaches to the economic assessment of costs in the operation of cars with axial load of 27 tons at the section Kachkanar—Smychka by G. A. Granovskaya, A. I. Safonova, O. A. Suslov, N. S. Okhotnikov

“…The article describes method of calculating the coefficient reflecting the change in the impact of cars with an axial load of 27 tons on the roadbed during transportation in estimated cars compared to transportation in equivalent cars. Algorithms for calculating changes in the cost of fuel and energy costs for train traction and maintenance of the track infrastructure on the site during the operation of trains formed from cars with an axial load of 27 tons are given, as well as methods for determining the initial data for the calculation.Authors provide values of the coefficient reflecting the change in the impact of vertical and horizontal forces on the railway line when passing freight cars with an axial load of 27 tons compared to analogue cars, and the coefficient of change of the main specific resistance to motion separately for loaded and empty cars.Developed calculation algorithms and methods for obtaining baseline data allow an economic assessment of changes in infrastructure maintenance costs and fuel and energy resources for the operation of trains formed from cars with an axial load of 27 tons compared to those formed from cars with a load of 23.5 tons at the experimental section Kachkanar—Smychka.The cost change assessment carried out in 2017 shows a generally definite economic effect, while there is a reduction in costs associated with the consumption of electricity for train traction as a result of the operation of the estimated cars in the experimental section and an increase in the cost of maintaining the track superstructure and the roadbed, which is quite expected for the conditions of the organization of traffic with increased axial loads.…”
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Comment on “Odontogenic Tumors: A Challenge for Clinical Diagnosis and an Opportunity for AI Innovation” by Hinpetch Daungsupawong, Viroj Wiwanitkit

“…By incorporating advanced imaging techniques and machine learning algorithms, researchers can improve the accuracy and efficiency of diagnostic processes. …”
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Acoustic-Based Machine Main State Monitoring for High-Speed CNC Drilling by Pimolkan Piankitrungreang, Kantawatchr Chaiprabha, Worathris Chungsangsatiporn, Chanat Ratanasumawong, Peemdej Chancharoen, Ratchatin Chancharoen

“…Advanced signal processing techniques, including spectrogram analysis and Fast Fourier Transform, extract dominant frequencies and acoustic patterns, while machine learning algorithms like DBSCAN clustering classify operational states such as cutting, breakthrough, and returning. …”
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Advancing soil mapping and management using geostatistics and integrated machine learning and remote sensing techniques: a synoptic review by Sunshine A. De Caires, Chaney St Martin, Melissa A. Atwell, Fuat Kaya, Glorious A. Wuddivira, Mark N. Wuddivira

“…Hybrid approaches combining geostatistics with ML algorithms (e.g., RF, Boost, SVM, ANN) demonstrate promise in addressing spatial uncertainty, while RS data enhances covariate enrichment and near-real-time applications. …”
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Flexible Configurable Modular Neural Network-Based OFDM Receiver by A. B. Sergienko, P. V. Apalina, A. D. Lebedinskaya

“…The proposed OFDM receiver for all considered modulation types provided error rates comparable to those of the baseline algorithms under favorable channel conditions (moderate delay spread with low Doppler spread) and outperformed baseline algorithms in severe conditions (channel with a large delay spread and high Doppler spread). …”
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Personalizing the Marketing with Artificial Intelligence (AI) by Rozhko Viktor I., Pletnova Yelyzaveta S.

“…Another major challenge is the technical limitations of AI. While AI algorithms are capable of analyzing vast amounts of data, they cannot always properly adapt to a changing market environment or predict consumer behavior in non-standard situations. …”
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Enhancing Security and Authenticity in Immersive Environments by Rebecca Acheampong, Dorin-Mircea Popovici, Titus Balan, Alexandre Rekeraho, Manuel Soto Ramos

“…Simulations of tampering and forgery attacks further validated the system’s capability to detect unauthorized modifications, with a 100% detection rate observed across multiple trials. While the system currently employs RSA, which may be vulnerable to quantum computing in the future, its modular design ensures crypto-agility, allowing for the integration of quantum-resistant algorithms as needed. …”
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Opportunities, challenges, and interventions for agriculture 4.0 adoption by Shanmugam Vijayakumar, Varunseelan Murugaiyan, S. Ilakkiya, Virender Kumar, Raman Meenakshi Sundaram, Rapolu Mahender Kumar

“…This includes developing cost-effective sensors, user-friendly algorithms, and versatile machinery tailored for small-scale farms. …”
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Clustering and classification of early knee osteoarthritis using machine-learning analysis of step-up and down test kinematics in recreational table tennis players by Ui-jae Hwang, Kyu Sung Chung, Sung-min Ha

“…Supervised learning models achieved high performance in classifying EOA status, with Random Forest, gradient boosting, and decision tree algorithms achieving 100% classification accuracy (AUC = 1.000) on the test dataset. …”
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The Author's Reply by Mohamad Reza Golzar Feshalami, Mehraban Shahi, Nasrin Davari Dolatabadi

“…The commenter rightly points out the need for a more detailed exploration of specific types of odontogenic tumors that present significant diagnostic challenges. While our article aimed to provide a broad overview of the diagnostic complexities across various tumor types, we acknowledge that a deeper dive into individual tumor characteristics and diagnostic hurdles would have enriched the discussion.Moving forward, we recognize the importance of focusing research efforts on developing AI algorithms that can effectively differentiate between different types of odontogenic tumors based on their unique clinical and radiographic features. …”
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Breast cancer diagnosis with MFF-HistoNet: a multi-modal feature fusion network integrating CNNs and quantum tensor networks by Tariq Mahmood, Tanzila Saba, Amjad Rehman

“…Leveraging the BreaKHis dataset, MFF-HistoNet differentiates between eight breast cancer subtypes and reduces model complexity while preserving the ability to capture vital spatial relationships, thus enhancing computational efficiency. …”
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The Nexus between spatiotemporal land use/land cover dynamics and ecosystem service values in the wabe river catchment, Omo Gibe River Basin, Ethiopia by Yonas Mathewos, Brook Abate, Mulugeta Dadi, Markos Mathewos

“…Historical Landsat imagery was classified under supervised techniques employing maximum likelihood algorithms in ERDAS Imagine; future changes were forecasted using multilayer perceptron neural network and cellular automata-Markov chain algorithms, and the value transfer valuation technique in conjunction with ArcGIS 10.8 was utilized to quantify the nexus between LULC changes and resulting ESVs. …”
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UOrtos: Methodology for Co-Registration and Subpixel Georeferencing of Satellite Imagery for Coastal Monitoring by Gonzalo Simarro, Daniel Calvete, Francesca Ribas, Yeray Castillo, Càrol Puig-Polo

“…The approach utilizes feature-based methods, cross-correlation, and RANSAC (RANdom SAmple Consensus) algorithms to accurately align images while avoiding outliers. …”
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The use of artificial intelligence in the HR processes of logistics companies by Adam Panek

“…Personalization of AI-based training improves employee engagement and productivity, while optimization of work schedules and accurate forecasting of staffing needs allow for better human resource management. …”
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Ensemble deep learning-enabled single-shot composite structured illumination microscopy (eDL-cSIM) by Jiaming Qian, Chunyao Wang, Hongjun Wu, Qian Chen, Chao Zuo

“…Experimental results demonstrate that eDL-cSIM integrates the advantages of various state-of-the-art neural networks, enabling robust super-resolution image predictions across different specimen types or structures of interest, and outperforms classical physics-driven methods in terms of imaging speed, reconstruction quality and environmental robustness, while avoiding intricate and specialized algorithmic procedures. …”
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