A multi-scale multi-channel CNN introducing a channel-spatial attention mechanism hyperspectral remote sensing image classification method by Ru Zhao, Chaozhu Zhang, Dan Xue

“…First, the data set is divided into two kinds of pixel module, and then different channels are used for feature extraction. …”
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Speech emotion recognition using long-term average spectrum by Huerta-Hernández Luis David, Meléndez-Acosta Nayeli Joaquinita, Troncoso-Romero David Ernesto, Ramírez-Pacheco Julio César, León-Borges Jose Antonio

“…In this work, a new framework for emotion recognition is proposed based on the long-term average spectrum (LTAS). Our framework is evaluated through a comparative study, where classifiers such as artificial neural network, K-nearest neighbours, logistic regression, Bayesian algorithms, tree-based logistics, and support vector machine were used. …”
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Profiling triple-negative breast cancer-specific super-enhancers identifies high-risk mesenchymal development subtype and BETi-Targetable vulnerabilities by Qing-shan Chen, Rui-zhao Cai, Yan Wang, Ge-hao Liang, Kai-ming Zhang, Xiao-Yu Yang, Dong Yang, De-Chang Zhao, Xiao-Feng Zhu, Rong Deng, Jun Tang

“…The biological significance of CRCs in these different TNBC subtypes and their influence on BETi sensitivity were evaluated using in vitro and in vivo models. …”
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Development of IIOT-Based Pd-Maas Using RNN-LSTM Model with Jelly Fish Optimization in the Indian Ship Building Industry by PNV Srinivasa Rao, PVY Jayasree

“…The validation of the proposed predictive maintenance model optimization with different types of deep learning algorithms shows that our proposed methodology gives an improved accuracy of 98.9336% which is higher than any other models.   …”
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Development of machine learning models to predict clinical outcome and recovery time in dogs with parvovirus enteritis by Negin Sanaei, Mohamad Zamani-Ahmadmahmudi, Seyed Mahdi Nassiri

“…With the advent of machine learning methods/algorithms, various models can be developed using a combination of clinical and non-clinical variables to predict clinical outcome in different diseases with higher efficiency compared to traditional biomarkers. …”
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Prediction of persistent type II endoleak after endovascular aortic repair using machine learning based on preoperative clinical data and radiomic by Jinqing Mo, Qi Liu, Kangjie Wang, Lin Huang, Chen Yao

“…Six common machine learning algorithms were used to predict persistent T2ELs based on preoperative features. …”
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Efficient Real-Time Object Detection and Classification Using mmWave Radar and Jetson Xavier NX by Mohamed Lamane, Abdessamad Klilou, Mohamed Tabaa

“…Recently, mmWave radars have been used in several automotive and industrial applications to provide the position and speed of detected objects using FMCW algorithms. However, this radar is not able to recognize or classify the detected objects. …”
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Transforming Wind Data into Insights: A Comparative Study of Stochastic and Machine Learning Models in Wind Speed Forecasting by Türker Tuğrul, Sertaç Oruç, Mehmet Ali Hınıs

“…In these analyses, five different models were created with the assistance of cross-correlation. …”
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A Hybrid Proactive Caching System in Vehicular Networks Based on Contextual Multi-Armed Bandit Learning by Qiao Wang, David Grace

“…The two parallel prediction algorithms are based on Contextual Multi-armed bandit (cMAB) learning, called Dual-context cMAB and Single-context cMAB. …”
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A Multilevel and Hierarchical Approach for Multilabel Classification Model in SDGs Research by Berliana Sugiarti Putri, Lya Hulliyyatus Suadaa, Efri Diah Utami

“…This study aimed to implement and evaluate problem transformation methods and machine learning classification algorithms with a multilevel and hierarchical approach to categorize research publications into SDG levels. …”
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Identification of osteoarthritis-associated chondrocyte subpopulations and key gene-regulating drugs based on multi-omics analysis by Ting Hao, Zhiwei Pei, Sile Hu, Zhenqun Zhao, Wanxiong He, Jing Wang, Liuchang Jiang, jirigala Ariben, Lina Wu, Xiaolong Yang, Leipeng Wang, Yonggang Wu, Xiaofeng Chen, Qiang Li, Haobo Yang, Siqin Li, Xing Wang, Mingqi Sun, Baoxin Zhang

“…Additionally, the immune and pathway scores of the training dataset samples were evaluated using the ESTIMATE, MCP-counter, and ssGSEA algorithms to establish the relationship between the hub genes and immune and pathways. …”
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Machine Learning-Based Methodologies for Cyber-Attacks and Network Traffic Monitoring: A Review and Insights by Filippo Genuario, Giuseppe Santoro, Michele Giliberti, Stefania Bello, Elvira Zazzera, Donato Impedovo

“…Also, the ensembles are tested. The algorithms are evaluated on the KDD-99, NSL-KDD, UNSW-NB15, IoT-23, and UNB-CIC IoT 2023 datasets. …”
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Prognostic analysis of sepsis-induced myocardial injury patients using propensity score matching and doubly robust analysis with machine learning-based risk prediction model develo... by Pan Guo, Pan Guo, Li Xue, Fang Tao, Kuan Yang, YuXia Gao, Chongzhe Pei

“…This study aimed to evaluate the prognostic impact of SIMI and develop validated predictive models using advanced machine learning (ML) algorithms for identifying SIMI in critically ill sepsis patients.MethodsData were sourced from the Medical Information Mart for Intensive Care IV (MIMIC-IV, v3.0) database. …”
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Prediction and Stage Classification of Pressure Ulcers in Intensive Care Patients by Machine Learning by Mürsel Kahveci, Levent Uğur

“…Using demographic, clinical and laboratory data of the patients, six different machine learning algorithms (SVM, KNN, ANN, Decision Tree, Naive Bayes and Discriminant Analysis) were used for classification. …”
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PV Module Soiling Detection Using Visible Spectrum Imaging and Machine Learning by Boris I. Evstatiev, Dimitar T. Trifonov, Katerina G. Gabrovska-Evstatieva, Nikolay P. Valov, Nicola P. Mihailov

“…One of these factors is the soiling of the PV surface, which could be observed in different forms, such as dust and bird droppings. In this study, visible spectrum data and machine learning algorithms were used for the identification of soiling. …”
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A Framework for Assessment of Perception Systems in Autonomous Vehicles by Hussein Hennaoui, Daniel Paluszczyszyn, Lipika Deka, Serhan Cosar

“…The results demonstrate that the sensors with the respective algorithms in the simulation are adapted to different lighting conditions, ensuring consistent sensory performance. …”
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Seal Pipeline: Enhancing Dynamic Object Detection and Tracking for Autonomous Unmanned Surface Vehicles in Maritime Environments by Mohamed Ahmed, Bader Rasheed, Hadi Salloum, Mostafa Hegazy, Mohammad Reza Bahrami, Mikhail Chuchkalov

“…The preprocessing effectiveness was assessed using the Root Mean Square Error (RMSE) and tracking accuracy was evaluated through detection rate metrics. The results demonstrate a 25% to 30% improvement in detection accuracy and show that the pipeline can aid industry even with sparse object representation across different frames. …”
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Building trust for traffic flow forecasting components in intelligent transportation systems via interpretable ensemble learning by Jishun Ou, Jingyuan Li, Chen Wang, Yun Wang, Qinghui Nie

“…To evaluate the effectiveness of the framework, the developed tree-ensemble models and another three typical categories of baseline models, including statistical time series, shallow learning, and deep learning, were compared on three datasets collected from different types of roads (i.e., arterial, expressway, and freeway). …”
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Ensemble machine learning prediction accuracy: local vs. global precision and recall for multiclass grade performance of engineering students by Yagyanath Rimal, Yagyanath Rimal, Navneet Sharma

“…The results highlight a significant comparative analysis of prediction accuracy across different algorithms, emphasizing the importance of employing multiple receiver operating characteristic curves, areas under the curves, and a one-vs-rest classification approach when target features are represented as letter grades. …”
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Single target tracking in high-resolution satellite videos: a comprehensive review by Xin Huang, Ding Wang, Qiqi Zhu, Ying Zheng, Qingfeng Guan

“…To identify emerging research trends and opportunities, we classify established and emerging algorithms into three main categories and evaluate their performance on typical satellite videos. …”
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