Navigating Ethical Dilemmas Of Generative AI In Medical Writing by Qurrat Ulain Hamdan, Waleed Umar, Mahnoor Hasan

“…Privacy and Security Concerns The innate programming of generative AI chatbots to store the information that is provided to them also raises concerns regarding their safety and security. …”
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A Survey on Investigating the Need for Intelligent Power-Aware Load Balanced Routing Protocols for Handling Critical Links in MANETs by B. Sivakumar, N. Bhalaji, D. Sivakumar

“…This paper also suggests a machine learning based hybrid power-aware approach for handling critical nodes via load balancing.…”
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Bilateral acute angle closure due to choroidal effusion: a case report by I. I. Shteyner, E. Yu. Zubkova, A. V. Zolotarev

“…The diagnostic and treatment algorithms are described. Advanced diagnostic technologies and a systematic approach to the analysis of atypical angle closure allowed not only to identify the cause of clinical presentations — choroidal effusion and anterior displacement of the lens–iris complex, but also to reveal the underlying systemic disease. …”
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Distributed Prescribed Finite Time Consensus Scheme for Economic Dispatch of Smart Grids with the Valve Point Effect by Yingjiang Zhou, Shigao Zhu, Qian Chen

“…Third, with considering the constraints of generation units, the prescribed finite time result is also achieved. Finally, from the simulations, the efficiency of the proposed algorithms is validated.…”
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Mathematical analysis of COVID-19 dynamics in Iraq utilising empirical data by Wasan I. Khalil, Ayad R. Khudair

“…Utilising the validated model, we establish an optimal control problem aimed at minimising daily infections via vaccination, employing a cost function. We also present algorithms utilising Pontryagin’s minimum principle, with time-delay modifications, to identify the optimal vaccination strategy.…”
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Bias and Variance Analysis of Contemporary Symbolic Regression Methods by Lukas Kammerer, Gabriel Kronberger, Stephan Winkler

“…On the contrary, larger models effectively prevent systematic errors. We also show how other algorithms like ITEA or AIFeynman with the declared goal of producing consistent results meet up to their expectation of small and similar models.…”
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Quantum Technologies for Beyond 5G and 6G Networks: Applications, Opportunities, and Challenges by Engin Zeydan, Chamitha De Alwis, Rabia Khan, Yekta Turk, Abdullah Aydeger, Thippa Reddy Gadekallu, Madhusanka Liyanage

“…A particular focus is on the role of quantum technologies in enhancing 6G Radio Access Networks (RAN), 6G core and edge network optimization, and 6G security. The survey paper also explores the application of quantum cryptography with a focus on Quantum Key Distribution (QKD), Quantum Secure Direct Communication (QSDC) and quantum-resistant cryptographic algorithms and assesses their implementation challenges and potential impact on 6G networks. …”
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Assessing Huanglongbing Severity and Canopy Parameters of the Huanglongbing-Affected Citrus in Texas Using Unmanned Aerial System-Based Remote Sensing and Machine Learning by Ittipon Khuimphukhieo, Jose Carlos Chavez, Chuanyu Yang, Lakshmi Akhijith Pasupuleti, Ismail Olaniyi, Veronica Ancona, Kranthi K. Mandadi, Jinha Jung, Juan Enciso

“…Huanglongbing (HLB), also known as citrus greening disease, is a devastating disease of citrus. …”
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An Innovative Smart Irrigation Using Embedded and Regression-Based Machine Learning Technologies for Improving Water Security and Sustainability by Abdennabi Morchid, Abdennacer Elbasri, Zahra Oughannou, Hassan Qjidaa, Rachid El Alami, Badre Bossoufi, Saleh Mobayen, Pawel Skruch

“…Discussions reveal that the integration of embedded systems with machine learning algorithms can not only improve irrigation efficiency but also contribute to the sustainability of agriculture by enabling more accurate and adaptive management of water resources. …”
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Investigating Bias of DCFT, DPT and Promoted DPT Methods in terms of Phase Parameters Estimation of Chirp Signal by Nooshin Rabiee, Hamid Aazad, Naser Parhizgar

“…The results of investigating the bias of estimators indicated the improved accuracy of the DPT and promoted DPT algorithms in estimation using the RBF method instead of NLS and also than DCFT method.…”
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Machine Learning Techniques for Classification of Stress Levels in Traffic by Amanda Trojan Fenerich, Egídio José Romanelli, Rodrigo Eduardo Catai, Maria Teresinha Arns Steiner

“… The aim of this study is to apply Machine Learning techniques for predicting and classifying the stress level of people commuting from home to work and also to evaluate the performance of prediction models using feature selection. …”
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Monoclonal anti-CD20 antibodies in lymphomas therapy during the COVID-19 pandemic: pro and contra by K. A. Sychevskaya, S. K. Kravchenko

“…The current trends in the modification of the accepted algorithms of lymphoproliferative diseases therapy with the inclusion of monoclonal anti-CD20 antibodies are summarized, and the possibilities of specific prevention by vaccination against COVID-19 are also considered.…”
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Multi-level high utility-itemset hiding. by Loan T T Nguyen, Hoa Duong, An Mai, Bay Vo

“…To address this issue, this work suggests two PPUM algorithms, namely MLHProtector and FMLHProtector, to operate at all abstraction levels in a transaction database to protect them from data mining algorithms. …”
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Machine Learning Models for the Classification of Histopathological Images of Colorectal Cancer by Nektarios Georgiou, Pavlos Kolias, Ioanna Chouvarda

“…The findings of this research suggested that XGboost provides the highest accuracy (89.79%) and could contribute to the growing body of knowledge in computational pathology. Other algorithms, such as the random forest, SVM, and CNN, also provided satisfactory results, offering insights into the effectiveness of image classification algorithms in distinguishing between different categories of cancerous cells. …”
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A survey of sand-dust image visual enhancement techniques by SI Yazhong, ZHANG Xulong, YANG Fan, WANG Jianzong, CHENG Ning, XIAO Jing

“…To better understand the current research progress in the field of sandstorm image processing, this paper elaborates in detail on sandstorm image enhancement algorithms based on traditional technology, sandstorm image restoration algorithms based on atmospheric scattering models, and summarizes data-driven sandstorm image reconstruction algorithms. …”
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Optimization Techniques for Physician Scheduling Problem: A Systematic Review of Recent Advancements and Future Directions by Norizal Abdullah, Masri Ayob, Meng Chun Lam, Nasser R. Sabar, Graham Kendall, Mohamad Khairulamirin Md Razali

“…Future research directions are outlined, emphasizing the need for more scalable algorithms, real-time scheduling capabilities, improved user interfaces, and comprehensive validation studies. …”
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Time series forecasting of Valley fever infection in Maricopa County, AZ using LSTMResearch in context by Xueting Jin, Fangwu Wei, Srinivasa Srivatsav Kandala, Tejas Umesh, Kayleigh Steele, John N. Galgiani, Manfred D. Laubichler

“…Summary: Background: Coccidioidomycosis (CM), also known as Valley fever, is a respiratory infection. …”
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Future of Alzheimer's detection: Advancing diagnostic accuracy through the integration of qEEG and artificial intelligence by Sahar Rezaei, Farzan Asadirad, Alireza Motamedi, Mohammadsadegh Kamran, Farzaneh Parsa, Haniyeh Samimi, Parna Ghannadikhosh, Mahdi Zahmatyar, Seyed Ali Hosseinzadeh, Hossein Arabi

“…Through systematic analysis of 11 key studies across multiple international databases, we evaluated various AI architectures, including machine learning algorithms and deep learning networks, applied to qEEG data for AD detection. …”
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A comprehensive review of data analytics and storage methods in geothermal energy operations by Ali Basem, Ahmed Kateb Jumaah Al-Nussairi, Dana Mohammad Khidhir, Narinderjit Singh Sawaran Singh, Mohammadreza Baghoolizadeh, Mohammad Ali Fazilati, Soheil Salahshour, S. Mohammad Sajadi, Ali Mohammadi Hasanabad

“…The study also delves into the potential of machine learning to optimize geothermal design, monitor performance, improve performance, find errors, and more. …”
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The Weight Distributions of a Class of Cyclic Codes with Three Nonzeros over 𝔽3 by Xiaogang Liu, Yuan Luo

“…Cyclic codes have efficient encoding and decoding algorithms. The decoding error probability and the undetected error probability are usually bounded by or given from the weight distributions of the codes. …”
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