Mitigating malicious denial of wallet attack using attribute reduction with deep learning approach for serverless computing on next generation applications by Amal K. Alkhalifa, Mohammed Aljebreen, Rakan Alanazi, Nazir Ahmad, Sultan Alahmari, Othman Alrusaini, Ali Alqazzaz, Hassan Alkhiri

“…This study proposes a Mitigating Malicious Denial of Wallet Attack using Attribute Reduction with Deep Learning (MMDoWA-ARDL) approach for serverless computing on next-generation applications. …”
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A Nomogram for Predicting Survival in Patients with SARS-CoV-2 Omicron Variant Pneumonia Based on Admission Data by Yang Y, Li D, Nie J, Wang J, Huang H, Hang X

“…Risk analysis was performed using clinical symptoms, laboratory findings, and chest CT imaging features. A predictive algorithm was developed using Cox multivariate analysis.Results: The high-risk group had a shorter survival duration than the low-risk group. …”
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Computational study on a puzzle in the biosynthetic pathway of anthocyanin: Why is an enzymatic oxidation/ reduction process required for a simple tautomerization? by Hajime Sato, Chao Wang, Mami Yamazaki, Kazuki Saito, Masanobu Uchiyama

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Evaluating the generalisability of region-naïve machine learning algorithms for the identification of epilepsy in low-resource settings. by Ioana Duta, Symon M Kariuki, Anthony K Ngugi, Angelina Kakooza Mwesige, Honorati Masanja, Daniel M Mwanga, Seth Owusu-Agyei, Ryan Wagner, J Helen Cross, Josemir W Sander, Charles R Newton, Arjune Sen, Gabriel Davis Jones

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CMIP6 multi-model ensemble projection of reference evapotranspiration using machine learning algorithms by Milad Nouri, Shadman Veysi

“…The X-means clustering algorithm was also exploited to classify ETo based on various characteristics, including minimum, maximum, average, skewness, and standard deviation, as well as ETo ranges of 0–5, 5–10, and greater than 10 mm d⁻¹. …”
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Advanced Mathematical Modeling of Hydrogen and Methane Production in a Two-Stage Anaerobic Co-Digestion System by Olympia Roeva, Elena Chorukova, Lyudmila Kabaivanova

“…Parameter identification was achieved through dynamic experimentation, utilizing three distinct optimization algorithms: the deterministic active-set method (A-S) and the metaheuristics–genetic algorithm (GA), coyote optimization algorithm (COA), and marine predator algorithm (MPA). …”
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Comparison and modeling of hybrid green energy systems tied to unhealthy grid utilizing different algorithms by Emad M. Sayed, Khaled H. Ibrahiem, Mohamed Mahmoud Samy, Ahmed Farhan

“…CGO emerges as the most effective algorithm, suggesting an HRES with an LCOE of $0.0347 per kilowatt-hour, and a net present cost (NPC) of $3.75 million. …”
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Examining the empathy levels of medical students using CHAID analysis by Nesrin Hark Söylemez

“…CHAID analysis was employed to identify the key predictors influencing empathy levels, whereas machine learning algorithms were utilized to classify and predict individuals' empathy levels. …”
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Innovative approaches to beam forming antenna array systems with adaptive Partial Update NLMS algorithms by Zahraa A. Shubber, Thamer M. Jamel, Ali.K. Nahar

“…For the most part, we will be discussing PU Normalized Least Mean Square (PU NLMS) algorithms like M-max NLMS, Periodic-NLMS, and Stochastic-NLMS. …”
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Two New Weak Convergence Algorithms for Solving Bilevel Pseudomonotone Equilibrium Problem in Hilbert Space by Gaobo Li

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Ultrasonic radiomics in predicting pathologic type for thyroid cancer: a preliminary study using radiomics features for predicting medullary thyroid carcinoma by Dai Zhang, Dai Zhang, Dai Zhang, Dai Zhang, Fan Yang, Fan Yang, Fan Yang, Fan Yang, Wenjing Hou, Wenjing Hou, Wenjing Hou, Wenjing Hou, Ying Wang, Ying Wang, Ying Wang, Ying Wang, Jiali Mu, Jiali Mu, Jiali Mu, Jiali Mu, Hailing Wang, Hailing Wang, Hailing Wang, Hailing Wang, Xi Wei, Xi Wei, Xi Wei, Xi Wei

“…We constructed clinical model, radiomics model and comprehensive model by executing machine learning algorithms based on baseline clinical, pathological characteristics and ultrasound image data, respectively.ResultsThe study showed that the comprehensive model observed the highest diagnostic efficacy in differentiating MTC from PTC with AUC, sensitivity, specificity, positive predictive value, negative predictive value and accuracy of 0.93, 0.88, 0.82, 0.77, 0.91, 85.8%. …”
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Versatile machine learning algorithms for FTIR spectroscopy: differentiating crosslinked and non-crosslinked gelatin samples by Juliana Rincón-López, Eliana Álvarez-Valdés, Daniela Velez-Arango, Estefanía Rojas Zuleta, Leidy Yuliana Vargas Soto, Liliana Lellesch, Victor Alonso García Londoño, Milton Rosero-Moreano, Gonzalo Taborda-Ocampo

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Improvement of point cloud feature extraction and alignment algorithms and lidar slam in coal mine underground by Guanghui XUE, Zhenghao ZHANG, Guiyi ZHANG, Ruixue LI

“…Compared to the traditional LIO-SAM algorithm, the improved algorithm showcases higher accuracy in pose estimation and point cloud registration, with a 6.52% improvement in average relative position error and an 18.84% reduction in maximum absolute position error. …”
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Relaxed Iterative Algorithms for Generalized Mixed Equilibrium Problems with Constraints of Variational Inequalities and Variational Inclusions by Lu-Chuan Ceng, Chi-Ming Chen, Ching-Feng Wen, Chin-Tzong Pang

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Resource allocation strategies and task scheduling algorithms for cloud computing: A systematic literature review by Kareem Awad Waleed, Zainol Ariffin Khairul Akram, Nazri Mohd Zakree Ahmad, Yassen Esam Taha

“…It evaluates popular algorithms designed to optimize key metrics such as energy consumption, resource utilization, cost reduction, makespan minimization, and performance satisfaction. …”
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Significance of Machine Learning-Driven Algorithms for Effective Discrimination of DDoS Traffic Within IoT Systems by Mohammed N. Alenezi

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Development and Comparison of Interrupt-Based and Analog-to-Digital Converter Algorithms for Seed Counting in Precision Planters by A. Ghaffarnezhad, H. Navid, H. Karimi

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A comparative study of the performance of ten metaheuristic algorithms for parameter estimation of solar photovoltaic models by Adel Zga, Farouq Zitouni, Saad Harous, Karam Sallam, Abdulaziz S. Almazyad, Guojiang Xiong, Ali Wagdy Mohamed

“…This estimation is challenging due to computational complexity and the risk of optimization errors, which can hinder reliable performance predictions. The algorithms evaluated include the Crayfish Optimization Algorithm, the Golf Optimization Algorithm, the Coati Optimization Algorithm, the Crested Porcupine Optimizer, the Growth Optimizer, the Artificial Protozoa Optimizer, the Secretary Bird Optimization Algorithm, the Mother Optimization Algorithm, the Election Optimizer Algorithm, and the Technical and Vocational Education and Training-Based Optimizer. …”
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Algorithm of athletes’ fitness structure individual features’ determination with the help of multidimensional analysis (on example of basketball) by Zh.L. Kozina, M. Cieslicka, K. Prusik, R. Muszkieta, I.N. Sobko, O.A. Ryepko, T.A. Bazilyuk, S.B. Polishchuk, A.V. Osiptsov, S.A. Korol

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Prediction Approaches for Smart Cultivation: A Comparative Study by Amitabha Chakrabarty, Nafees Mansoor, Muhammad Irfan Uddin, Mosleh Hmoud Al-adaileh, Nizar Alsharif, Fawaz Waselallah Alsaade

“…Other contemporary machine learning algorithms, namely, support vector machine, random forest, and logistic regression, have average prediction accuracy of around 68.9%, 91.2%, and 62.39%, respectively.…”
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