Improving fluoroprobe sensor performance through machine learning by D. Lafer, A. Sukenik, T. Zohary, O. Tal

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Implementation of laser-light backscattering imaging for authentication of the geographic origin of Indonesia region citrus by Muhammad Achirul Nanda, S. Rosalinda, Rahmat Budiarto, Inna Novianty, Taufik Ibnu Salim, Pradeka Brilyan Purwandoko, Dimas Firmanda Al Riza

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CNN-LSTM-Attention with PSO optimization for temperature and fault prediction in meat grinder motors by Yao Zhang, Pengfei Zhang, Wenchao Zhang, Mingwei Wang

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Well logging super-resolution based on fractal interpolation enhanced by BiLSTM-AMPSO by Jian Han, Yu Deng, Bing Zheng, Zhimin Cao

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Automatic Detection of Interplanetary Coronal Mass Ejections in Solar Wind In Situ Data by H. T. Rüdisser, A. Windisch, U. V. Amerstorfer, C. Möstl, T. Amerstorfer, R. L. Bailey, M. A. Reiss

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Time Series Forecasting for Air Quality with Structured and Unstructured Data Using Artificial Neural Networks by Kenneth Chan, Paul Matthews, Kamran Munir

“…CORD has a similar result to GRU and slightly smaller mean absolute and root mean square errors than LSTM. Compared with an ANN algorithm, CORD has better accuracy.…”
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Integrating explainable artificial intelligence and light gradient boosting machine for glioma grading by Teuku Rizky Noviandy, Ghalieb Mutig Idroes, Irsan Hardi

“…Methods: This study employs the Light Gradient Boosting Machine (LightGBM), an advanced ML algorithm, in combination with Explainable Artificial Intelligence (XAI) methodology to grade gliomas more effectively. …”
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A Novel Phase Error Estimation Method for TomoSAR Imaging Based on Adaptive Momentum Optimizer and Joint Criterion by Muhan Wang, Silin Gao, Xiaolan Qiu, Zhe Zhang

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Strategies to alleviate flickering: Bayesian and smoothing methods for deep learning classification in video by Noah Miller, Glen Ryan Drumm, Lance Champagne, Bruce Cox, Trevor Bihl

“…Bayesian neural networks are a potential remedy to this issue using Bayesian priors. This research compares a traditional video classification neural network to its Bayesian equivalent based on performance and capabilities. …”
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Machine learning analysis of molecular dynamics properties influencing drug solubility by Zeinab Sodaei, Saeid Ekrami, Seyed Majid Hashemianzadeh

“…The Gradient Boosting algorithm achieved the best performance with a predictive R2 of 0.87 and an RMSE of 0.537 in test set. …”
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Deep Temporal Joint Clustering for Satellite Image Time-Series Analysis by Wenqi Guo, Zheng Zhang, Yu Meng, Weixiong Zhang, Shichen Gao, Ping Tang

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GDnet-IP: Grouped Dropout-Based Convolutional Neural Network for Insect Pest Recognition by Dongcheng Li, Yongqi Xu, Zheming Yuan, Zhijun Dai

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Elicitation of Norwegian EQ-5D-5L values for hypothetical and experience-based health states based on the EuroQol Valuation Technology (EQ-VT) protocol by Knut Stavem, Tonya Moen Hansen, Ylva Helland, Liv Ariane Augestad, Kim Rand, Andrew Garratt

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Near-Infrared Hyperspectral Target Tracking Based on Background Information and Spectral Position Prediction by Li Wu, Mengyuan Wang, Weixiang Zhong, Kunpeng Huang, Wenhao Jiang, Jia Li, Dong Zhao

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Evaluating Deep Learning Architectures for Breast Tumor Classification and Ultrasound Image Detection Using Transfer Learning by Christopher Kormpos, Fotios Zantalis, Stylianos Katsoulis, Grigorios Koulouras

“…These insights are further anticipated to advance future algorithm development and broaden the potential of the research applicability across diverse fields.…”
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A Decade in Software-Based Side and Covert Channel Attacks and Countermeasures: A Survey by Teodora Vasilas, Remus Brad

“…In addition, we conduct a comparative analysis of the attacks, considering key aspects such as attack methodology, targeted algorithms, victim system environment, reliability, performance impact, and mitigation strategies. …”
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A Comprehensive Vector Dataset of Bus Networks Across China for the Year 2024 by Shiguang Wang, Jinyu He, Rui Ma, Zeyang Cheng, Heng Ding

“…We designed a set of high-precision algorithms for generating bus network vector data based on electronic map APIs, which include steps such as coordinate transformation, network simplification, station projection, and topology generation. …”
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Optimizing Photovoltaic Power Prediction Using Computational Methods and Artificial Neural Networks by Cempaka Amalin Mahadzir, Ahmad Fateh Mohamad Nor, Siti Amely Jumaat, Noor Syahirah Ahmad Safawi

“…Since solar power output is fluctuating and depends on climatic, geographical and temporal factors, precise prediction requires the implementation of computational approaches. The aim of this research is to develop ANN algorithms that anticipate solar power output and enhance the structure of them by incorporating the derating factor due to dirt (kdirt) into account. …”
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Automated Tomato Leaf Disease Detection Using Image Processing: An SVM-Based Approach with GLCM and SIFT Features by Rashid Khan, Nasir Ud Din, Asim Zaman, Bingding Huang

“…Our findings suggest that this framework can significantly benefit tomato cultivation by enabling timely and precise disease management. Future research can explore integrating advanced deep learning algorithms to enhance the system’s accuracy in this multiclass classification challenge.…”
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Impact of massive open online courses in higher education using machine learning and decision based fuzzy frank power aggregation operators models by Feng Ye

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