Enhanced tuberculosis detection using Vision Transformers and explainable AI with a Grad-CAM approach on chest X-rays by K. Vanitha, T. R. Mahesh, V. Vinoth Kumar, Suresh Guluwadi

“…The model contains a Conv2D stem for initial feature extraction, followed by many transformer encoder blocks, thereby significantly boosting its ability to learn discriminative features without any pre-processing. …”
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YOLOv-MA: A High-Precision Foreign Object Detection Algorithm for Rice by Jiahui Wang, Mengdie Jiang, Tauseef Abbas, Hao Chen, Yuying Jiang

“…Rice plays a crucial role in global agricultural production, but various foreign objects often mix in during its processing. To efficiently and accurately detect small foreign objects in the rice processing pipeline, ensuring food quality and consumer safety, this study innovatively proposes a YOLOv-MA-based foreign object detection algorithm for rice, leveraging deep learning techniques. …”
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Cloud-Driven Data Analytics for Growing Plants Indoor by Nezha Kharraz, István Szabó

“…Built with Apache NiFi (Niagara Files), the pipeline facilitates real-time ingestion, processing, and storage of IoT sensor data measuring light, moisture, and nutrient levels. …”
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Impact of stocking density on oxidative stress, digestive enzyme activity, ATPase function, and transcriptomic changes in juvenile Crimson snapper (Lutjanus erythropterus) during l... by Jiaqi Su, Yu Guo, Jiayang Li, Karsoon Tan, Chuanxin Qin

“…At low to moderate stocking densities (20–60 g/L), L. erythropterus adapted environmental stress by boosting total antioxidant capacity, α-amylase activity, and ATPases activities. …”
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Uncertainty-Aware Deep Learning for Robust and Interpretable MI EEG Using Channel Dropout and LayerCAM Integration by Óscar Wladimir Gómez-Morales, Sofia Escalante-Escobar, Diego Fabian Collazos-Huertas, Andrés Marino Álvarez-Meza, German Castellanos-Dominguez

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Big Data Analytics Framework for Decision-Making in Sports Performance Optimization by Dan Cristian Mănescu

“…Analytical methods, including gradient boosting classifiers, logistic regression, and multilayer perceptron models, were employed to predict injury risk, optimize in-game tactical decisions, and personalize sprint mechanics training. …”
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Multifunction Transceiver for Data Communication, Radar Sensing and Power Transfer by Thomas Micallef, Intikhab Hussain, Ke Wu

“…The integration of multiple wireless functionalities into a unified system presents a critical challenge due to conflicting requirements in transceiver architecture and signal processing. Recent investigations are directing attention towards the development of systems that serve dual functions, like simultaneous wireless information and power transfer and radar-communication, aimed at boosting operational efficiency and ensuring seamless communication among different wireless capabilities. …”
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Performance Evaluation of Hybrid Machine Learning Algorithms for Online Lending Credit Risk Prediction by Tesfahun Berhane, Tamiru Melese, Abdu Mohammed Seid

“…Peer-to-Peer systems are still in the early stages of development when it comes to the processing of credit and the appraisal of the risk associated with it. …”
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Applying machine learning to classify table olives using bacterial metataxonomic data by Elio López-García, Antonio Benítez-Cabello, Francisco Noé Arroyo-López

“…Our findings show that ML techniques can effectively classify bacterial profiles based on olive processing type, cultivar, country of origin, and isolation matrix. …”
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Automated Classification Model for Elementary Mathematics Diagnostic Assessment Data Based on TF-IDF and XGBoost by Seonghyun Park, Seungmin Oh, Woncheol Park

“…Furthermore, the system demonstrated an average real-time processing speed of 1.3 s, ensuring instant feedback in educational settings. …”
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Non-destructive detection of pre-incubated chicken egg fertility using hyperspectral imaging and machine learning by Md Wadud Ahmed, Asher Sprigler, Jason Lee Emmert, Ryan N Dilger, Girish Chowdhary, Mohammed Kamruzzaman

“…The Extreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), Random Forest (RF), and Support Vector Machine (SVM) calibration models were developed at full wavelengths (374–1015 nm), and the performance of the models was evaluated by 10-fold cross-validation and independent validation. …”
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Recent overview of kaffir lime (Citrus hystrix DC) dual functionality in food and nutraceuticals by Rahmat Budiarto, Nasrul Wathoni, Syariful Mubarok, Jajang Sauman Hamdani, Tri Ujilestari, Cici Darsih, Reka Mustika Sari, Rizal Maarif Rukmana, Mohammad Miftakhus Sholikin

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In Situ Converting Conformal Sacrificial Layer Into Robust Interphase Stabilizes Fluorinated Polyanionic Cathodes for Aqueous Sodium‐Ion Storage by Peng Gong, Shibo Chai, Xingjie Li, Yibo Dong, Shengjun Zhai, Xihao Chen, Ning Wang, Yuanyuan Li, Jinping Liu

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Ensemble Machine Learning Models Utilizing a Hybrid Recursive Feature Elimination (RFE) Technique for Detecting GPS Spoofing Attacks Against Unmanned Aerial Vehicles by Raghad Al-Syouf, Omar Y. Aljarrah, Raed Bani-Hani, Abdallah Alma’aitah

“…This technique is built on ensemble learning approaches, namely, bagging, boosting, stacking, and voting classifiers, to efficiently detect GPS spoofing attacks. …”
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Integrated GBR–NSGA-II Optimization Framework for Sustainable Utilization of Steel Slag in Road Base Layers by Merve Akbas

“…Four advanced tree-based ensemble regression algorithms—Random Forest Regressor (RFR), Extremely Randomized Trees (ERTs), Gradient Boosted Regressor (GBR), and Extreme Gradient Boosting Regressor (XGBR)—were rigorously evaluated. …”
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Advancements in the application of artificial intelligence in the field of colorectal cancer by Mengying Zhu, Mengying Zhu, Zhenzhu Zhai, Yue Wang, Fang Chen, Ruibin Liu, Ruibin Liu, Xiaoquan Yang, Guohua Zhao

“…DL, a more advanced form of ML, simulates the brain’s processing power, enhancing the accuracy of tumor detection, differentiation, and prognosis predictions. …”
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Hierarchical Feature Fusion and Enhanced Attention Mechanism for Robust GAN-Generated Image Detection by Weinan Zhang, Sanshuai Cui, Qi Zhang, Biwei Chen, Hui Zeng, Qi Zhong

“…Meanwhile, the AEM enhances the network’s ability to capture subtle forgery traces by incorporating attention mechanisms and filtering techniques, significantly boosting the model’s efficiency in processing complex information. …”
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Highly efficient stacking ensemble learning model for automated keratoconus screening by Zahra J. Muhsin, Rami Qahwaji, Ibrahim Ghafir, Mo’ath AlShawabkeh, Muawyah Al Bdour, Saif Aldeen AlRyalat, Majid Al-Taee

“…Following extensive pre-processing, key corneal features that are strongly correlated with the target diagnosis are identified. …”
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An improved performance model for artificial intelligence-based diabetes prediction by Ugwu Hillary Okwudili, Oparaku Ogbonna Ukachukwu, V. C. Chijindu, Michael Okechukwu Ezea, Buhari Ishaq

“…XB demonstrates remarkable predictive performance, bolstered by its built-in cross-validation and parallel processing; nevertheless, it remains sensitive to outliers, highlighting the importance of thorough data processing. …”
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Highly Selective Electroreduction of CO2 to CH4 on Cu–Pd Alloy Catalyst: the Role of Palladium‐Adsorbed Hydrogen Species and Blocking Effect by Jinyan Huang, Ye Yang, Xuexue Liang, Bing Chen, Yue Shen, Yan Chen, Jielian Yang, Yinglin Yu, Fang Huang, Huibing He, Peican Chen, Liya Zhou, Anxiang Guan

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