Application of Machine Learning for Target Selection and Acid Treatment Design by I. I. Mannanov, M. A. Varfolomeev, G. R. Ganieva, A. R. Gimaeva, R. R. Giniyatullin

“…These algorithms significantly simplify the tasks of acid treatment design.…”
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Mechanisms of Disinformation Amplification in Hybrid Warfare: The Case of the Conflict in Ukraine by Rafał ROMAŃSKI

“…The article contributes a novel theoretical framework in the form of a “hybrid tripartite model” (communication–perception–algorithms), which may serve as a useful analytical tool in future studies of disinformation in conflict situations. …”
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Short-Term Electrical Load Forecasting in Power Systems Using Deep Learning Techniques by Nihat Pamuk

“…Using a real dataset for one-step forecasting, this article compares three deep learning algorithms for short-term power load forecasting: LSTM, GRUs, and CNN. …”
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The Enterprise School Readiness Prediction System (ESRPS) Uses Machine Learning to Assess Children's Readiness for Entering Elementary School by Muhammad Choerul Umam, Cicilia Dyah Sulistyaningrum I., Dydik Kurniawan, Priyono Tri Febrianto

“…The system implements four algorithms: Decision Tree, Random Forest, Naive Bayes, and SVM. …”
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A Comprehensive Approach to Rustc Optimization Vulnerability Detection in Industrial Control Systems by Kaifeng Xie, Jinjing Wan, Lifeng Chen, Yi Wang

“…However, the Rustc optimization process may introduce vulnerabilities due to algorithmic flaws or issues arising from component interactions. …”
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Biomarker and clinical data–based predictor tool (MAUXI) for ultrafiltration failure and cardiovascular outcome in peritoneal dialysis patients: a retrospective and longitudinal st... by Eva María Arriero-País, María Auxiliadora Bajo-Rubio, Roberto Arrojo-García, Pilar Sandoval, Guadalupe Tirma González-Mateo, Patricia Albar-Vizcaíno, Gloria del Peso-Gilsanz, Marta Ossorio-González, Pedro Majano, Manuel López-Cabrera, Gloria del Peso-Gilsanz

“…Biomarkers displayed proper mutual information and SHapley values, indicating that MMT processes may have a causal relationship in the development of UFF and CVD.Conclusions MMT biomarkers and clinical data may be associated in a causal manner with ultrafiltration failure (local effect) and cardiovascular events (systemic effect) in PD. …”
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The State of Artificial Intelligence and its Prospects in Pakistan's Medical Sector by Rohail Akhtar Habib, Yumna Sattar Khan

“…Predictive analytics using machine learning algorithms has become more popular in Pakistani healthcare. …”
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Clinical Approach to Evaluation of Underlying Cardiac Device Infection in Patients Hospitalized with Bacteremia by Dierdre B. Axell-House, Sarwat Khalil, M. Rizwan Sohail

“…While CIED pocket infection can be diagnosed based on clinical exam findings, positive blood culture may be the only manifestation of CIED lead infection. …”
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Machine learning provides reconnaissance-type estimates of carbon dioxide storage resources in oil and gas reservoirs by Emil Attanasi, Philip Freeman, Timothy Coburn

“…Further, ML algorithms can capture highly complex, particularly nonlinear, relationships among predictor variables. …”
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Validating machine learning models for the prediction of labour induction intervention using routine data: a registry-based retrospective cohort study at a tertiary hospital in nor... by Jian Wu, Soumitra S Bhuyan, Xiaoli Fu, Quanman Li, Clifford Silver Tarimo, Michael Johnson J Mahande

“…Further optimisation of these classifiers through hyperparameter tuning may result in an improved performance. Extensive research into the performance of other classifier algorithms is warranted.…”
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IEWNet: Multi-Scale Robust Watermarking Network Against Infrared Image Enhancement Attacks by Yu Bai, Li Li, Shanqing Zhang, Jianfeng Lu, Ting Luo

“…The robustness of the algorithms is also better than the existing state-of-the-art image watermarking algorithms used in the performance evaluation comparison.…”
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Application of Classical and Genomic Cryptography on Textual Dataset by İbrahim Türkoğlu, Alev Kaya

“…These variables determine the effectiveness of cryptographic algorithms. In fact, existing cryptographic algorithms may be inadequate or ineffective in the face of new requirements. …”
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Identification and mechanism analysis of biomarkers related to butyrate metabolism in COVID-19 patients by Wenchao Zhou, Hui Li, Juan Zhang, Changsheng Liu, Dan Liu, Xupeng Chen, Jing Ouyang, Tian Zeng, Shuang Peng, Fan Ouyang, Yunzhu Long, Yukun Li

“…Background Butyrate may inhibit SARS-CoV-2 replication and affect the development of COVID-19. …”
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MACHINE LEARNING AND DEEP LEARNING: A COMPARATIVE ANALYSIS FOR APPLE LEAF DISEASE DETECTION by Anupam Bonkra, Sunil Pathak, Amandeep Kaur

“…This work employs five classification algorithms Inception V3, Decision Tree, Support Vector Machine (SVM), and Random Forest to create a model for detecting diseases on apple leaves. …”
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Dual-modal edible oil impurity dataset for weak feature detection by Huiyu Wang, Qianghua Chen, Jianding Zhao, Liwen Xu, Ming Li, Ying Zhao, Qinpei Zhao, Qin Lu

“…Abstract Edible oil may be mixed with tiny solid impurities like raw material fragments, hair, metal fragments and etc. during the production and manufacturing process. …”
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Analyzing Data Incompleteness for MRI Data for Quality Enhancement by Sanjay Shanbhag, Supreetha Raju, Varadraj P. Gurupur, S. Sowmya Kamath, Rajesh N. V. P. S. Kandala, Elizabeth A. Trader, Shyam Lal

“…In this paper, we present algorithms specifically designed to address the challenges of undersampling and motion artifacts in MR images. …”
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Deep Learning-Based Efficient Model Development for Phishing Detection Using Random Forest and BLSTM Classifiers by Shan Wang, Sulaiman Khan, Chuyi Xu, Shah Nazir, Abdul Hafeez

“…Such communication needs a secure medium through which users can communicate in a secure and reliable way so that their information may not be lost. The proposed study is an endeavor toward the detection of phishing by using random forest and BLSTM classifiers. …”
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Optimization of DC Energy Storage in Tokamak Poloidal Coils by Alessandro Lampasi, Riccardo Testa, Bhavana Gudala, Cristina Terlizzi, Sabino Pipolo, Sandro Tenconi

“…This flow can be managed by introducing a DC energy storage based on supercapacitors. Because such storage may be the most expensive and largest part of the poloidal power supply system, an excessive size would cancel its potential advantages. …”
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Resolving multi-image spatial lipidomic responses to inhaled toxicants by machine learning by Nathanial C. Stevens, Tong Shen, Joshua Martinez, Veneese J. B. Evans, Morgan C. Domanico, Elizabeth K. Neumann, Laura S. Van Winkle, Oliver Fiehn

“…We evaluate the effect of combined allergen sensitization and ozone exposure on eliciting spatial differences in lipid distribution in the mouse lung that may contribute to ozone-induced exacerbations in asthma. …”
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Performance-Enhancing Market Risk Calculation Through Gaussian Process Regression and Multi-Fidelity Modeling by N. Lehdili, P. Oswald, H. D. Nguyen

“…The market risk measurement of a trading portfolio in banks, specifically the practical implementation of the value-at-risk (VaR) and expected shortfall (ES) models, involves intensive recalls of the pricing engine. Machine learning algorithms may offer a solution to this challenge. In this study, we investigate the application of the Gaussian process (GP) regression and multi-fidelity modeling technique as approximation for the pricing engine. …”
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