A Novel Methodology to Correct Chlorophyll-a Concentrations from Satellite Data and Assess Credible Phenological Patterns by Irene Biliani, Ekaterini Skamnia, Polychronis Economou, Ierotheos Zacharias

“…This study highlights the value of integrating statistical methods with remote sensing data for accurate, long-term monitoring of water quality in aquatic ecosystems.…”
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Leveraging explainable artificial intelligence for early detection and mitigation of cyber threat in large-scale network environments by G. Nalinipriya, S. Rama Sree, K. Radhika, E. Laxmi Lydia, Faten Khalid Karim, Mohamad Khairi Ishak, Samih M. Mostafa

“…Additionally, the Hiking Optimization Algorithm (HOA) is employed to fine-tune the hyperparameters of the SDAE model. …”
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Enhancing safety in surface mine blasting operations with IoT based ground vibration monitoring and prediction system integrated with machine learning by Mangalpady Aruna, Harsha Vardhan, Abhishek Kumar Tripathi, Satyajeet Parida, N. V. Raja Sekhar Reddy, Krishna Moorthy Sivalingam, Li Yingqiu, P. V. Elumalai

“…The study also employed Support Vector Regression (SVR), Gradient Boosting Regression (GBR), and Random Forest (RF) algorithms to predict Peak Particle Velocity (PPV) values. …”
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Shared diagnostic genes and potential mechanism between PCOS and recurrent implantation failure revealed by integrated transcriptomic analysis and machine learning by Wenhui Chen, Wenhui Chen, Wenhui Chen, Qingling Yang, Qingling Yang, Qingling Yang, Linli Hu, Linli Hu, Linli Hu, Mengchen Wang, Mengchen Wang, Mengchen Wang, Ziyao Yang, Ziyao Yang, Ziyao Yang, Xinxin Zeng, Xinxin Zeng, Xinxin Zeng, Yingpu Sun, Yingpu Sun, Yingpu Sun

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A Verifiable and Secure Industrial IoT Data Deduplication Scheme With Real-Time Data Integrity Checking in Fog-Assisted Cloud Environments by Jakkarin Lapmoon, Somchart Fugkeaw

“…For real-time data integrity, we propose an integrity verification algorithm that cross-references hash values stored in the cloud and blockchain, enabling fast and lightweight integrity checks. …”
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Adaptive estimation: Fuzzy data-driven gamma distribution via Bayesian and maximum likelihood approaches by Abbarapu Ashok, Nadiminti Nagamani

“…Integrating fuzzy concepts into statistical estimation offers considerable advantages by enhancing both the accuracy and reliability of parameter estimations, irrespective of the sample size and technique used. …”
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Petrophysics Parameter Inversion and Its Application Based on the Transient Electromagnetic Method by Xiaozhen Teng, Jianhua Yue, Kailiang Lu, Danyang Xi, Herui Zhang, Kua Wang

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Design, synthesis and simulation of fractional-order element using MOS transistors as distributed resistive capacitive devices by David Kubanek, Aleksandr Shadrin, Pavel Seda, Jan Dvorak, Jan Jerabek, Vilem Kledrowetz, Cole Christie, Todd J. Freeborn, Pyotr A. Ushakov

“…The synthesis approach adopts a genetic algorithm to generate the MOS structures interconnections and dimensions to realize an FOE with user-defined constant input admittance phase, allowed ripple deviations, and target frequency range. …”
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Symmetric Cryptography With Shift 2^n-1, Hash Transformation, Optimization-Based Controller for Medical Image Infosecurity: Case Study in Mammographic Image by Pi-Yun Chen, Jian-Xing Wu, Chien-Ming Li, Chao-Lin Kuo, Neng-Sheng Pai, Chia-Hung Lin

“…This study proposes right / left shift 2^n−1 pixel values, hash transformation with multi-secret gold keys, and an optimization-based controller to integrate two symmetric cryptography processes for medical image encryption and decryption with the same secret gold keys. …”
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Trade-off between cost and performance of earth observation data in olive trees health assessment: Digital crop mapping approach using machine learning algorithms by Yassine Bouslihim, Abdelkrim Bouasria, Aicha Rochdi, El Bachir El Haissen, Dénes Loczy, Zoltan Orban, Ali Salem

“…Furthermore, three machine learning algorithms, Random Forest (RF), Cubist, and Extreme Gradient Boosting (XGBoost), were employed to predict chlorophyll content. …”
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Optimizing drying and storage for edible mushrooms: Study on gamma irradiation levels, drying temperatures, and packaging materials with SVM-based predictions by Ehsan Fartash Naeimi, Mohammad Hadi Khoshtaghaza, Kemal Çağatay Selvi, Mariana Ionescu, Soleiman Abbasi

“…Nanocomposite packaging preserved the appearance characteristics of the dried mushrooms, and the SVM algorithm demonstrated strong potential for predicting quality changes prior to processing.…”
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Integrated multiomics analysis and machine learning refine neutrophil extracellular trap-related molecular subtypes and prognostic models for acute myeloid leukemia by Fangmin Zhong, Fangyi Yao, Zihao Wang, Jing Liu, Bo Huang, Xiaozhong Wang

“…Receiver operating characteristic (ROC) curve and Cox regression analyses further validated the strong independent prognostic value of the risk score model. The nomogram, which was constructed by integrating the risk score model and clinicopathological factors, demonstrated high accuracy in predicting the overall survival of AML patients. …”
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Integrating Machine Learning and Deep Learning for Predicting Non-Surgical Root Canal Treatment Outcomes Using Two-Dimensional Periapical Radiographs by Catalina Bennasar, Antonio Nadal-Martínez, Sebastiana Arroyo, Yolanda Gonzalez-Cid, Ángel Arturo López-González, Pedro Juan Tárraga

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Integrative analysis of epigenetic subtypes in acute myeloid Leukemia: A multi-center study combining machine learning for prognostic and therapeutic insights. by Jincan Li, Shengyue Wang

“…This study aimed to develop an integrated epigenetic-based classification system and evaluate its prognostic value.…”
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Estimating and Downscaling ESA-CCI Soil Moisture Using Multi-Source Remote Sensing Images and Stacking-Based Ensemble Learning Algorithms in the Shandian River Basin, China by Liguo Wang, Ya Gao

“…Furthermore, it is observed that the stacking algorithm, which integrates multiple models, outperforms the single-model CatBoost algorithm in terms of accuracy. …”
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Integrative radiomics of intra- and peri-tumoral features for enhanced risk prediction in thymic tumors: a multimodal analysis of tumor microenvironment contributions by Liang zhu, Jiamin Li, Xuefeng Wang, Yan He, Siyuan Li, Shuyan He, Biao Deng

“…Subsequently, hierarchical clustering and the LASSO algorithm were applied to identify the most predictive features. …”
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IMSBA: A Novel Integrated Sensing and Communication Beam Allocation Based on Multi-Agent Reinforcement Learning for mmWave Internet of Vehicles by Jinxiang Lai, Deqing Wang, Yifeng Zhao

“…To address these challenges, this paper proposes an integrated sensing and communication (ISAC) beam allocation algorithm, termed IMSBA, which jointly optimizes beam direction, transmission power, and spectrum resource allocation to effectively mitigate the interference between I2V and V2V while maximizing the overall network performance. …”
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Post-deployment performance of a deep learning algorithm for normal and abnormal chest X-ray classification: A study at visa screening centers in the United Arab Emirates by Amina Abdelqadir Mohamed AlJasmi, Hatem Ghonim, Mohyi Eldin Fahmy, Aswathy Nair, Shamie Kumar, Dennis Robert, Afrah Abdikarim Mohamed, Hany Abdou, Anumeha Srivastava, Bhargava Reddy

“…At such high-volume settings, manual CXR reporting is challenging and integrating artificial intelligence (AI) algorithms into the workflow help to rule out normal findings in minutes, allowing radiologists to focus on abnormal cases. …”
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Improving appendix cancer prediction with SHAP-based feature engineering for machine learning models: a prediction study by Ji Yoon Kim

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Identification of Maize Kernel Varieties Using LF-NMR Combined with Image Data: An Explainable Approach Based on Machine Learning by Chunguang Bi, Xinhua Bi, Jinjing Liu, He Chen, Mohan Wang, Helong Yu, Shaozhong Song

“…Subsequently, LF-NMR features and image morphological data were integrated to construct a classification model and the SVM hyperparameters were optimized using an improved differential evolution algorithm, achieving a final classification accuracy of 96.36%, which demonstrated strong robustness and precision. …”
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