Performance Estimation of Low Power and Area-Efficient Parallel Pipelined FFT by Surya P, Arunachalaperumal C, Dhilipkumar S

“…The proposed FFT processor utilizes only 8 % of the available look-up tables (LUTs) with a 1:3 ratio in resource utilization and a 56 % reduction in delays compared to previous research. …”
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Enhancing Unmanned Aerial Vehicle Object Detection via Tensor Decompositions and Positive–Negative Momentum Optimizers by Ruslan Abdulkadirov, Pavel Lyakhov, Denis Butusov, Nikolay Nagornov, Dmitry Reznikov, Anatoly Bobrov, Diana Kalita

“…Our positive–negative momentum approaches enabled a reduction in the loss in precision and recall assessments for the proposed neural network. …”
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Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…This fusion of deep learning innovation with the principles of randomization-based algorithms opens new avenues for developing accessible, accurate diagnostic tools, potentially alleviating the global impact of diabetic vision loss.…”
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YOLORM: An Advanced Key Point Detection Method for Accurate and Efficient Rotameter Reading in Low Flow Environments by Huang Yong, Xia Xing, Xiao Shengwang

“…Compared to the baseline YOLOv8n model, YOLORM achieved a 7.43% increase in detection accuracy and a 15.21% reduction in computational complexity. Moreover, YOLORM exhibited significant reductions in parameter count and computational cost while maintaining or enhancing detection performance relative to state-of-the-art algorithms. …”
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Introducing a novel 3D Chen-Rössler map for NTRU-based image encryption with OFDM transmission over a noisy channel by Alain F. Djomo, Lee Mariel H. Yepdia, Yannick P. K. Nkandeu, Yannick A. Abanda, Alain Tiedeu

“…Traditional encryption algorithms, such as AES and RSA, show limitations in the face of modern threats, not least because of their vulnerability to quantum computers. …”
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Contributon-Informed Approach to RPV Irradiation Study Using Hybrid Shielding Methodology by Mario Matijević, Krešimir Trontl, Dubravko Pevec

“…The complex design of a typical PWR is posing a deep penetration shielding problem for which an elaborate simulation model is needed, not only in geometrical aspects but also in efficient computational algorithms for solving particle transport. This paper presents such a hybrid shielding approach of FW-CADIS for characterization of the reactor pressure vessel (RPV) irradiation using SCALE6.2.4 code package. …”
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Enhanced Plant Leaf Classification over a Large Number of Classes Using Machine Learning by Ersin Elbasi, Ahmet E. Topcu, Elda Cina, Aymen I. Zreikat, Ahmed Shdefat, Chamseddine Zaki, Wiem Abdelbaki

“…The results indicate that the Multilayer Perception algorithm gives 89.48%, the Naïve Bayes Classifier gives 89.63%, Convolutional Neural Networks has 88.72%, and the Hoeffding Tree algorithm gives 89.92% accuracy for the classification of 99 label plant leaf classification problems.…”
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Application of Artificial Intelligence in Prosthodontics in the 21st century by Lavanya V, Keerthivasan MS, Venkatakrishnan CJ, Tamizhesai BV, Anandh V

“…With responsible implementation AI can augment dental education and practice particularly in prosthodontics and oral implantology paving the way for a new era of precision and patient-centered care.…”
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IMMUNOPATHOGENESIS OF MYASTHENIA GRAVIS (REVIEW) by E. D. Gasymly

“…High clinical heterogeneity of autoimmune myasthenia, initiating the flow, increases the urgency of studying its pathogenesis, searching for specific methods of marker diagnostics, developing algorithms for predicting the features of the development of the disease. …”
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Transcriptome signature for multiple biotic and abiotic stress in barley (Hordeum vulgare L.) identifies using machine learning approach by Bahman Panahi

“…Machine learning models, specifically Random Forest and C4.5, were optimized and evaluated using a 10-fold cross-validation approach. The C4.5 algorithm demonstrated superior accuracy in predicting stress-responsive signatures. …”
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Examining the Impact of Topography and Vegetation on Existing Forest Canopy Height Products from ICESat-2 ATLAS/GEDI Data by Yisa Li, Dengsheng Lu, Yagang Lu, Guiying Li

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Functional Connectivity Metrics in Temporal Lobe Epilepsy: A Machine Learning Perspective With MEG by M. V. Suhas, N. Mariyappa, A. Karunakar Kotegar, M. Ravindranadh Chowdary, K. Raghavendra, Ajay Asranna, L. G. Viswanathan, H. Anitha, Sanjib Sinha

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Electrical discharge machining: Recent advances and future trends in modeling, optimization, and sustainability by Muhamad Taufik Ulhakim, Sukarman, Khoirudin, Dodi Mulyadi, Hendri Susilo, Rohman, Muji Setiyo

“…Advanced modeling techniques, such as finite element analysis (FEA) and artificial intelligence (AI)-driven simulations, have improved the accuracy of process predictions, enabling real-time adjustments and precise control of machining parameters. …”
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Deep Learning-Based Adaptive Downsampling of Hyperspectral Bands for Soil Organic Carbon Estimation by Mohammad Rahman, Shyh Wei Teng, Manzur Murshed, Manoranjan Paul, David Brennan

“…However, hyperspectral data suffer from redundancy and noise, which can degrade predictive accuracy if not properly addressed. Existing dimensionality reduction techniques, such as fixed-interval downsampling and autoencoders, either risk discarding informative bands or disrupt spectral continuity, limiting their effectiveness for models like one-dimensional convolutional neural networks (1D-CNNs) that rely on local spectral patterns. …”
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Faster R-CNN model for target recognition and diagnosis of scapular fractures by Qiong Fang, Anhong Jiang, Meimei Liu, Sen Zhao

“…The accuracy of the CNN algorithm model combined with orthopedist interpretation was 97.78 %, significantly higher than orthopedist-independent interpretation (82.95 %) and CNN algorithm-independent prediction (92.05 %) (P < 0.05). …”
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Advancing Marine Surveillance: A Hybrid Approach of Physics Infused Neural Network for Enhanced Vessel Tracking Using Automatic Identification System Data by Tasmiah Haque, Md Asif Bin Syed, Srinjoy Das, Imtiaz Ahmed

“…Recognizing the strengths and limitations of the LSTM model, we propose a hybrid machine-learning algorithm that integrates LSTM with a physics-based model. …”
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Importance Analysis of Vegetation Change Factors in East Africa Based on Machine Learning by Zhang Xiumei, Ma Bo, Zhang Yijie

“…Six machine learning algorithms were used to establish NDVI prediction models: random forest (RF), BP neural networks (BP), support vector machines (SVM), genetic algorithm (GA), radial basis function (RBF), and convolutional neural networks (CNN). …”
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Integrative analysis of bulk and single-cell transcriptomic data reveals novel insights into lipid metabolism and prognostic factors in hepatocellular carcinoma by Feiyu Qi, Guiming Zha, Yanfang Zhang, Sihua Liu, Yuhang Yang, Wanliang Sun, Dongdong Wang, Zhong Liu, Zheng Lu, Dengyong Zhang

“…Immune-related analysis was conducted based on seven algorithms for immune cell infiltration prediction. …”
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Halftone images compression of bitplane using run length encoding with confirmation of repeateation by H. K. Al-Bahadily, V. Yu. Tsviatkou, V. K. Kanapelka

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THE ESTIMATION TECHNIQUE OF THE ASSOCIATION INFORMATION EFFICIENCY ABOUT AIR OBJECTS ACCORDING TO SEVERAL SOURCES by A. A. Belous, A. V. Khizhniak, D. S. Sharak, A. S. Bely

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