AIoT Monitoring for Early Identification of Diseases in Grapevines: Complete Study by Mihaela Hnatiuc, Domnica Alpetri, Sorin-Robertino Sintea, Bogdan Hnatiuc, Gabriel Margarit Raicu, Mirel Paun, Ionica Dina

“…Deployed at the Murfatlar vineyard in Romania, which grows Cabernet Sauvignon and Sauvignon Blanc, the system allows for proactive disease management, thus improving grapevine health and reducing crop losses. …”
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A Subspace-Based Compensation Method for the Mutual Coupling in Concentric Circular Ring Arrays for Near-Field Source Localisation by Mohammed Jainul Abedin, Ananda Sanagavarapu Mohan

“…The mutual coupling among antenna elements of the array would affect the orthogonality of subspaces when MUSIC or ESPRIT algorithms are used for parameter estimation. The proposed method obtains a compensation matrix that restores the orthogonality between the subspaces there by improving the accuracy of estimation. …”
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Enhanced Homomorphic Encryption for Cloud Security Through Individual Optimization by Radha Marepalli, Sunitha Vanamala, Manoj Kumar Konda, Venkata Rama Lakshmi Gundala, Prasanthi B.

“…These algorithms are also often referred to as PSO strategies. …”
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ILSTMA: Enhancing Accuracy and Speed of Long-Term and Short-Term Memory Architecture by Zongyu Ming, Zimu Wu, Genlang Chen

“…Furthermore, our proposed most relevant dialogue retrieval process substantially enhances the answer accuracy of LLMs while examining the potential of the two most commonly used memory retrieval algorithms. Experimental results demonstrate that our acceleration method improves the execution efficiency of the original architecture by 21.45%, and our most relevant dialogue retrieval process raises the answer accuracy to 88.4%, surpassing several benchmarks. …”
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The Role of Artificial Intelligence (AI) in the Future of Forestry Sector Logistics by Leonel J. R. Nunes

“…Results: The results demonstrated that optimization algorithms reduced transportation costs and carbon emissions. …”
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Conformal prediction for uncertainty quantification in dynamic biological systems. by Alberto Portela, Julio R Banga, Marcos Matabuena

“…These approaches can provide non-asymptotic guarantees, improving robustness and scalability across various applications, even when the predictive models are misspecified. …”
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Unmasking social bots: how confident are we? by James Giroux, Gangani Ariyarathne, Alexander C. Nwala, Cristiano Fanelli

“…Despite the progress made in developing multiple sophisticated social bot detection algorithms and tools, bot detection remains a challenging, unsolved problem that is fraught with uncertainty due to the heterogeneity of bot behaviors, training data, and detection algorithms. …”
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Early Heart Attack Detection Using Hybrid Deep Learning Techniques by Niga Amanj Hussain, Aree Ali Mohammed

“…These algorithms can process large datasets, extracting valuable insights that help mitigate the risk of fatal outcomes. …”
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CLIPPERS. Three clinical cases and review by L. N. Prakhova, A. S. Parfyonova, Zh. I. Savintseva, A. G. Ilves, E. V. Bubnova, V. S. Krasnov, A. M. Tarasova, N. A. Totolyan

“…Furthermore, the necessity of further research is shown for improving the accuracy and specificity of the diagnostic criteria, as well as for defining biomarkers and developing algorithms of effective therapy.…”
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A new machine learning method for rainfall classification: temporal random tree by Kokten Ulas Birant, Bita Ghasemkhani, Özlem Varlıklar, Derya Birant

“…Traditional classification algorithms usually assume that all samples in a dataset contribute equally to the training of a machine learning model, which is not always the case. …”
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Optimizing Gammatone Cepstral Coefficients for Gear Fault Detection by Zrar Kh Abdul, Abdulbasit K. Al-Talabani, Wisam Hazim Gwad, Entisar Alkayal, Halgurd S. Maghdid, Safar Maghdid Asaad

“…Experimental results demonstrate that optimizing GTCC parameters with GWO improves fault detection performance using an SVM classifier, achieving over 1% and 3% accuracy improvements on the PHM09 and DDS datasets, respectively.…”
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Thermal performance analysis of gas turbine power plant using soft computing techniques: a review by Ravindra S. Surase, Ramakrishna Konijeti, Ramchandra P. Chopade

“…Optimizing their thermal efficiency is essential for improving energy output and sustainability. Soft computing methods such as neural networks, genetic algorithms, and fuzzy logic offer potent tools for this optimization due to their ability to handle the turbines' nonlinear and dynamic characteristics. …”
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Exploring the Use of Virtual Reality and AI to Create Immersive, Interactive Music Experiences for Performance, Education, and Therapy by Jing Zhao, Kun Cheng

“…Key findings include significant improvements in user engagement, learning outcomes, and audience satisfaction in educational and performance contexts. …”
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CALCULATION MODEL OF SOLID PARTICLES MOTION IN NATURAL TURBULENT FLOWS by M. R. Magomedova

“…Objectives Improving the model of movement of solid particles in natural turbulent flows.Method The improvement of knowledge about the structure of water flows and the nature of channel processes has led to the development of views on sediment movement as a stochastic process due to the random nature of the factors causing it: natural-climatic and hydrological conditions, variability of the physical and mechanical properties of soils, and turbulence of water streams. …”
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Neutrosophic Fuzzy Power Management (NFPM): Tackling Uncertainty in Energy Harvesting for Sensor Networks by Musallam M. AlZubi, Mohamed A. Mohamed, Hanan M. Amer, A. A. Salama

“…The results are validated through numerical examples and extensive simulations, demonstrating NFPM's superiority over traditional fuzzy logic, with significant improvements such as a 25% reduction in power failures, 95% enhanced network connectivity, a 15% increase in data transmission success rates, and overall improvements in energy efficiency and robustness to fluctuations and noise. …”
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TOMOGRAPHIC MAMMOGRAPHY AND TOMOSYNTHESIS USING OPENGL by S. A. Zolotarev, M. A. Mirzavand

“…We believe that these methods are particularly useful for improving the quality of breast reconstructed image. …”
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ANN-Based Maximum Power Tracking for a Grid-Synchronized Wind Turbine-Driven Doubly Fed Induction Generator Fed by Matrix Converter by Mohamed A. Alarabi, Sedat Sünter

“…Simulation outcomes confirm that the ANN-based MPPT enhances the power extraction efficiency and improves the system performance. This study shows how wind energy systems can be optimized for smart grids by integrating advanced control techniques like FOC and simplified Venturini modulation with intelligent algorithms like ANN.…”
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Biomarker discovery by sparse canonical correlation analysis of complex clinical phenotypes of tuberculosis and malaria. by Juho Rousu, Daniel D Agranoff, Olugbemiro Sodeinde, John Shawe-Taylor, Delmiro Fernandez-Reyes

“…We show that using clinical view projections we obtain remarkable improvements in diagnostic class prediction, up to 11% in tuberculosis and up to 5% in malaria. …”
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Making JavaScript Render Decisions to Optimize Security-Oriented Crawler Process by Onur Aktas, Ahmet Burak Can

“…This approach seeks to reduce computational requirements and quicken the security evaluation process through the use of machine learning algorithms. By utilizing a dataset containing the source code from the main pages of 17,160 websites, our experimental results demonstrate a 20% reduction in execution time compared to full JavaScript rendering, indicating an improvement in resource usage without any significant reduction in coverage. …”
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YOLOv8-POS: a lightweight model for coal-rock image recognition by Yanqin Zhao, Wenyu Wang

“…Empirical results demonstrate that YOLOv8-POS markedly improves performance on coal-rock image datasets, achieving an AP50 of 77.1% and an AP50:95 of 63.6%, while concurrently reducing the model’s parameters to 2.60 M and the floating point operations (FLOPS) to 6.4 G. …”
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