Privacy-Preserving Machine Learning for IoT-Integrated Smart Grids: Recent Advances, Opportunities, and Challenges by Mazhar Ali, Moharana Suchismita, Syed Saqib Ali, Bong Jun Choi

“…Recent studies have provided valuable insights into the potential of machine learning algorithms in SGs, covering areas such as generation, distribution, microgrids, consumer energy market, and cyber security. …”
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SYSTEM OF STABILIZATION OF REACTIVE MAGNETRON SPUTTERING PROCESS by A. P. Burmakou, V. N. Kuleshov, A. V. Stoliarov

“…The sensors of the system may be vacuum gauges or pressure sensors, discharge current and voltage sensors of sprays, optical sensors for recording spectral element processes, absorption of a plasma of a magnetron discharge. …”
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Comparison of Deep Learning Techniques in Detection of Sickle Cell Disease. by Mabirizi, Vicent, Kawuma, Simon, Kyarisiima, Addah, Bamutura, David, Atwiine, Barnabas, Nanjebe, Deborah, Oyesigye, Adolf Mukama

“…This is evidenced by some models and algorithms with ≥90% prediction accuracy. From the literature, most of the proposed methods are trained and tested on pre-trained deep learning models like VGG16, VGG19, ResNet, Inception_V3, and ReNet. …”
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An ultrasonography of thyroid nodules dataset with pathological diagnosis annotation for deep learning by Xiaowen Hou, Menglei Hua, Wei Zhang, Jianxin Ji, Xuan Zhang, Huiru Jiang, Mengyun Li, Xiaoxiao Wu, Wenwen Zhao, Shuxin Sun, Lei Cao, Liuying Wang

“…Abstract Ultrasonography (US) of thyroid nodules is often time consuming and may be inconsistent between observers, with a low positivity rate for malignancy in biopsies. …”
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Urban Greening Analysis: A Multimodal Large Language Model for Pinpointing Vegetation Areas in Adverse Weather Conditions by Hanzhang Liu, Shijie Yang, Chengwu Long, Jiateng Yuan, Qirui Yang, Jiahua Fan, Bingnan Meng, Zhibo Chen, Fu Xu, Chao Mou

“…Additionally, these algorithms also have performance limitations such as inaccurate boundary area positioning. …”
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Western disturbances and climate variability: a review of recent developments by K. M. R. Hunt, K. M. R. Hunt, J.-P. Baudouin, A. G. Turner, A. G. Turner, A. P. Dimri, A. P. Dimri, G. Jeelani, Pooja, R. Chattopadhyay, R. Chattopadhyay, F. Cannon, T. Arulalan, T. Arulalan, M. S. Shekhar, T. P. Sabin, E. Palazzi

“…Use of new modelling frameworks and tracking algorithms has significantly improved knowledge of WD structure and variability, and a more frequentist approach can now be taken. …”
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Hyperspectral and Multispectral Remote Sensing Image Fusion Based on a Retractable Spatial–Spectral Transformer Network by Yilin He, Heng Li, Miaosen Zhang, Shuangqi Liu, Chunyu Zhu, Bingxia Xin, Jun Wang, Qiong Wu

“…Fusion that aims to emphasize spatial–spectral heterogeneous characteristics may significantly enhance the robustness of joint representation for multi-source data. …”
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Practicality of training a quantum-classical machine in the noisy intermediate-scale quantum era by Tarun Dutta, Alex Jin, Clarence Liu Huihong, José Ignacio Latorre, Manas Mukherjee

“…It addresses the challenges of coupling ion-trap systems with classical processors and highlights the effectiveness of genetic algorithms for NISQ devices and complex binary classification tasks with many local minima. …”
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Remote Sensing Time Series Analysis: A Review of Data and Applications by Yingchun Fu, Zhe Zhu, Liangyun Liu, Wenfeng Zhan, Tao He, Huanfeng Shen, Jun Zhao, Yongxue Liu, Hongsheng Zhang, Zihan Liu, Yufei Xue, Zurui Ao

“…., a constellation strategy, increasing computing power and advancing deep learning algorithms, are driving a paradigm shift from traditional point-in-time mapping to near-real-time monitoring tasks, and even to modeling integration of parameter inversion and prediction in land, water, and air science. …”
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Land Surface Temperature Super-Resolution With a Scale-Invariance-Free Neural Approach: Application to MODIS by Romuald Ait-Bachir, Carlos Granero-Belinchon, Aurelie Michel, Julien Michel, Xavier Briottet, Lucas Drumetz

“…Most of them are trained at low resolution but applied at fine resolution, and so they require a scale-invariance hypothesis that is not always adapted. The main contribution of this work is the introduction of a Scale-Invariance-Free approach for training neural network (NN) models, and the implementation of two NN models, called Scale-Invariance-Free Convolutional Neural Network for Super-Resolution (SIF-CNN-SR) for the super-resolution of MODIS LST products. …”
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Listener Acoustic Personalization Challenge - LAP24: Head-Related Transfer Function Upsampling by Aidan O. T. Hogg, Roberto Barumerli, Rapolas Daugintis, Katarina C. Poole, Fabian Brinkmann, Lorenzo Picinali, Michele Geronazzo

“…The submissions to Task 2 employed both algorithmic and machine learning-based approaches, which were evaluated on three key spatial audio objective metrics, including the log-spectral distortion (LSD), interaural time difference (ITD), and the interaural level difference (ILD). …”
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Autonomous novel class discovery for vision-based recognition in non-interactive environments by Xuelin Zhang, Feng Liu, Xuelian Cheng, Siyuan Yan, Zhibin Liao, Zongyuan Ge

“…Visual recognition with deep learning has recently been shown to be effective in robotic vision. However, these algorithms tend to be build under fixed and structured environment, which is rarely the case in real life. …”
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WEST GCN-LSTM: Weighted stacked spatio-temporal graph neural networks for regional traffic forecasting by Theodoros Theodoropoulos, Angelos-Christos Maroudis, Uwe Zdun, Antonios Makris, Konstantinos Tserpes

“…Furthermore, the aforementioned information is included via two novel dedicated algorithms, the Shared Borders Policy and the Adjustable Hops Policy. …”
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Neural network-based method for measuring the impacts of epileptic brain activities on cardiac cycles by Cândida H. L. Alves, Gilberto S. Alves, Gilberto S. Alves, Rômulo Kunrath, Mariélia Barbosa L. de Freitas, João Pedro G. Castor, Allan Kardec Barros, Diego Dutra Sampaio, Jonathan Araújo Queiroz

“…Although electroencephalogram (EEG) is widely used to monitor brain activity in epilepsy, limitations related to the accessibility and reproducibility of measurements may restrict its everyday use. Conversely, wearable methods, easily accessible, such as electrocardiogram (ECG), represent an alternative for indirectly monitoring brain activity through cardiac cycles. …”
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Continuous Speech-Based Fatigue Detection and Transition State Prediction for Air Traffic Controllers by Susmitha Vekkot, Surya Teja Chavali, Charan Tej Kandavalli, Rama Sai Abhishek Podila, Deepa Gupta, Mohammed Zakariah, Yousef Ajami Alotaibi

“…The ensemble algorithms demonstrated the best performance, achieving a maximum accuracy of 100% on the XGBoost test set. …”
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Efficacy of drugs most commonly prescribed at functional gastrointestinal diseases (functional dyspepsia syndrome and irritable bowel syndrome) observational study results by V. T. Ivashkin, Ye. A. Poluektova, D. V. Reykhart, O. S. Shifrin, A. G. Beniashvili, O. S. Lyashenko, A. V. Belostotsky

“…It is established that presence of probiotic in the treatment mode leads to significant reduction in main symptoms severity typical both for FD and IBS according to the «7×7» questionnaire.…”
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A database of upper limb surface electromyogram signals from demographically diverse individuals by Harshavardhana T. Gowda, Neha Kaul, Carlos Carrasco, Marcus Battraw, Safa Amer, Saniya Kotwal, Selena Lam, Zachary McNaughton, Ferdous Rahimi, Sana Shehabi, Jonathon Schofield, Lee M. Miller

“…The dataset also includes measures such as skin hydration and elasticity, which may affect EMG signals. This dataset provides a basis to study demographic confounds in EMG signals and serves as a benchmark to test the development of fair and unbiased algorithms that enable accurate hand gesture decoding across demographically diverse subjects. …”
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Characteristic expression profile of small nucleolar RNAs and their association with tumor immune microenvironment in papillary thyroid carcinoma by Qi-Lan Jiang, Fu-Yi Wang, Yuan Men, Yi-Huan Wu, Qin Xu, Yang Zeng, Jun Jiang

“…Abstract Certain cancers exhibit unique expression profiles of small nucleolar RNAs (snoRNAs), and the aberrant expression of snoRNAs may play significant roles in tumor biology. As the most common endocrine malignancy, the expression pattern and clinical relevance of snoRNAs in papillary thyroid carcinoma (PTC) remain largely unexplored. …”
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LED array-based multi-angle light scattering for aspirating smoke detection and classification by Soocheol Kim, Hoesung Yang, Kwangsoo Cho, Kyuwon Han, Yusun Ahn, Jin Hwa Ryu, Kangbok Lee

“…In particular, most smoke detection systems based on Mie scattering, which rely on single-scattering measurements, may not perform effectively in real-world environments where multiple scattering occurs. …”
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Texture Analysis in Volumetric Imaging for Dentomaxillofacial Radiology: Transforming Diagnostic Approaches and Future Directions by Elaine Dinardi Barioni, Sérgio Lúcio Pereira de Castro Lopes, Pedro Ribeiro Silvestre, Clarissa Lin Yasuda, Andre Luiz Ferreira Costa

“…The traditional imaging techniques rely primarily on visual assessment, which may overlook subtle variations in tissue structure. …”
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