Predicting Index Trend Using Hybrid Neural Networks with a Focus on Multi-Scale Temporal Feature Extraction in the Tehran Stock Exchange by Mohammad Osoolian, Ali Nikmaram, Mahdi Karimi

“…A wide array of predictive modeling techniques have been meticulously investigated, spanning from conventional statistical methodologies to more sophisticated machine learning algorithms. The primary focus of this research endeavor revolves around the predictive analysis of the Tehran Stock Exchange (TSE) Composite Index, wherein a novel hybrid neural network framework is employed. …”
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Enhancing Transpiration Estimates: A Novel Approach Using SIF Partitioning and the TL-LUE Model by Tewekel Melese Gemechu, Baozhang Chen, Huifang Zhang, Junjun Fang, Adil Dilawar

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Machine learning and response surface methodology forecasting comparison for improved spray dry scrubber performance with brine sludge-derived sorbent by B.J. Chepkonga, L. Koech, R.S. Makomere, H.L. Rutto

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Deep learning-based sow posture classifier using colour and depth images by Verônica Madeira Pacheco, Tami M. Brown-Brandl, Rafael Vieira de Sousa, Gary A. Rohrer, Sudhendu Raj Sharma, Luciane Silva Martello

“…This study aimed to develop and compare different deep learning-based sow posture classifiers using different architectures and image types. …”
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TomaFDNet: A multiscale focused diffusion-based model for tomato disease detection by Rijun Wang, Rijun Wang, Yesheng Chen, Fulong Liang, Xiangwei Mou, Xiangwei Mou, Guanghao Zhang, Hao Jin

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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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A XGBoost-Based Prediction Method for Meat Sheep Transport Stress Using Wearable Photoelectric Sensors and Infrared Thermometry by Ruiqin Ma, Runqing Chen, Buwen Liang, Xinxing Li

“…Their classification results were compared. The results show that SVC and GBDT algorithms are more effective and the overall model classification accuracy reached 86.44% and 91.53%. …”
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Probing the Pitfalls: Understanding SVD’s Shortcomings in Language Model Compression by Сергей Александрович Плетенев

“…Our research can inform the development of future compression techniques that adapt factorization strategies to the inherent structure of models and their tasks. …”
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Elastic net with Bayesian Density Estimation model for feature selection for photovoltaic energy prediction by Venkatachalam Mohanasundaram, Balamurugan Rangaswamy

“…Considering comprehensive data preliminary processing, FS, and validation, ELNET-BDE outperforms existing methods. Research investigations demonstrate that the ELNET-BDE model attains significantly lower Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) than contesting Machine Learning (ML) algorithms like Artificial Neural Network (ANN), Support Vector Machine (SVM), Random Forest (RF), and Gradient Boosting Machines (GBM). …”
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Predictive analysis of heart disease using quantum-assisted machine learning by Mehroush Banday, Sherin Zafar, Parul Agarwal, M. Afshar Alam, Siddhartha Sankar Biswas, Imran Hussain, K. M. Abubeker

“…In this research, a hybrid approach utilises techniques with quantum computing capabilities to tackle complex problems that are not amenable to conventional ML algorithms and to minimise computational expenses. …”
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In Vivo Insights: Near-Infrared Photon Sampling of Reflectance Spectra from Cranial and Extracranial Sites in Healthy Individuals and Patients with Essential Tremor by Antonio Currà, Riccardo Gasbarrone, Davide Gattabria, Giuseppe Bonifazi, Silvia Serranti, Daniela Greco, Paolo Missori, Francesco Fattapposta, Alessandra Picciano, Andrea Maffucci, Carlo Trompetto

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Exploring PID and FOPID Control Methods for Thrust Vectoring in Aerospace Systems-A Beginner’s Guide by Menhal Abdulmohsen Alkodur, Ali Hussain Almusharraf, Ghulam E. Mustafa Abro, Eman Mahmoud, Ayman M. Abdallah

“…The study instructs readers on constructing a physical prototype with SolidWorks software and experimentally evaluating the control algorithms. This text offers a fundamental comprehension of robust control approaches, enabling students and researchers with practical abilities to tackle high precision thrust vectoring issues in aerospace systems and space missions.…”
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Aerosol layer height (ALH) retrievals from oxygen absorption bands: intercomparison and validation among different satellite platforms, GEMS, EPIC, and TROPOMI by H. Kim, H. Kim, X. Chen, X. Chen, J. Wang, J. Wang, J. Wang, J. Wang, Z. Lu, Z. Lu, Z. Lu, M. Zhou, G. R. Carmichael, G. R. Carmichael, S. S. Park, J. Kim

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Highly Versatile FPGA-Implemented Cyber Coherent Ising Machine by Toru Aonishi, Tatsuya Nagasawa, Toshiyuki Koizumi, Mastiyage Don Sudeera Hasaranga Gunathilaka, Kazushi Mimura, Masato Okada, Satoshi Kako, Yoshihisa Yamamoto

“…By modifying the sequence control code for the calculation control module, other algorithms such as Simulated Bifurcation (SB) can also be implemented. …”
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Next Generation Power System Planning and Operation With Quantum Computation by Priyanka Arkalgud Ganeshamurthy, Kumar Ghosh, Corey O'Meara, Giorgio Cortiana, Jan Schiefelbein-Lach, Antonello Monti

“…Additionally, we provide an overview of quantum solutions for various power system related applications available in current literature and suggest future topics for research. We further highlight challenges with existing quantum solutions for exploiting full quantum capabilities. …”
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Early Warning of Axillary Lymph Node Metastasis in Breast Cancer Patients Using Multi-Omics Signature: A Machine Learning-Based Retrospective Study by Ke Z, Shen L, Shao J

“…The AUC of GLRM was 0.818 (95% CI: 0.757~0.879), significantly lower than that of RFM’s AUC 0.893 (95% CI: 0.836~0.950).Conclusion: The prediction models based on machine learning (ML) algorithms and multiomics have shown good performance in predicting ALN metastasis, and RFM shows greater advantages compared to traditional GLRM. …”
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Optimized Identification of Sentence-Level Multiclass Events on Urdu-Language-Text Using Machine Learning Techniques by Somia Ali, Uzma Jamil, Muhammad Younas, Bushra Zafar, Muhammad Kashif Hanif

“…The novelty of this research lies in the inclusion of 16 event categories to broaden coverage and the implementation of the SMFCNN and transformer-based algorithms. …”
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Date delivery scheme of delay-tolerant mobile sensor networks for high-voltage power transmission line inspection robot by FAN Fei, WU Gong-ping, WANG Man, XU Qing-shan, CAO Qi, YANG Song

“…Multiple simulation scenarios were performed, and the influences of different parameters with four routing algorithms were discussed. The results indicate that compared with the commonly used DTMSN data transmission methods, the proposed method can provide a higher delivery ratio and lower transport delay under appropriate transmission energy consumption.…”
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Using fishery-related data, scientific expertise, and machine learning to improve marine habitat mapping in northeastern Mediterranean waters by Loukas Katikas, Sofia Reizopoulou, Paraskevi Drakopoulou, Vassiliki Vassilopoulou

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HoRNS-CNN model: an energy-efficient fully homomorphic residue number system convolutional neural network model for privacy-preserving classification of dyslexia neural-biomarkers by Opeyemi Lateef Usman, Ravie Chandren Muniyandi, Khairuddin Omar, Mazlyfarina Mohamad, Ayoade Akeem Owoade, Morufat Adebola Kareem

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