High performance data integration for large-scale analyses of incomplete Omic profiles using Batch-Effect Reduction Trees (BERT) by Yannis Schumann, Simon Schlumbohm, Julia E. Neumann, Philipp Neumann

“…This work introduces batch-effect reduction trees (BERT), a high-performance method for data integration of incomplete omic profiles. …”
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A Particle Swarm Optimization Approach to Solve the Vehicle Routing Problem with Cross-Docking and Carbon Emissions Reduction in Logistics Management by Shih-Che Lo

“…<i>Methods</i>: A heuristic approach based on Particle Swarm Optimization, called ePSO, was proposed and implemented in this paper to solve the vehicle routing problems with cross-docking and carbon emissions reduction at the same time. <i>Results</i>: Performance comparisons were made with the Genetic Algorithm (GA) through the experiments of several vehicle routing problems with pickup and delivery benchmark problems to validate the performance of the ePSO procedure. …”
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Enhanced anomaly network intrusion detection using an improved snow ablation optimizer with dimensionality reduction and hybrid deep learning model by Fatimah Alhayan, Asma Alshuhail, Ahmed Omer Ahmed Ismail, Othman Alrusaini, Sultan Alahmari, Abdulsamad Ebrahim Yahya, Sami Saad Albouq, Mutasim Al Sadig

“…This manuscript proposes an Enhanced Anomaly Intrusion Detection using an Optimization Algorithm with Dimensionality Reduction and Hybrid Model (EAID-OADRHM) technique. …”
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Development of a Forecasting Framework Based on Advanced Machine Learning Algorithms for Greenhouse Gas Emissions by Seval Ene Yalçın

“…The reduction of greenhouse gas emissions, in order to effectively address the issue of climate change, has critical importance worldwide. …”
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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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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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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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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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Bio inspired feature selection and graph learning for sepsis risk stratification by D. Siri, Raviteja Kocherla, Sudharshan Tumkunta, Pamula Udayaraju, Krishna Chaitanya Gogineni, Gowtham Mamidisetti, Nanditha Boddu

Subjects: “…Wolverine optimization algorithm…”
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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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Intelligent irrigation strategy model for farmland using dung beetle optimization-random forest algorithms by Wenwen Hu, Yong Liu, Jun An, Shipu Xu, Zhiwen Zhou, Mingming An, Xiaokun Guo, Xiang Ma, Wenfei Jiang, Yunsheng Wang

“…This study proposes an optimized machine learning prediction model using the Dung Beetle Optimization-Random Forest (DBO-RF) algorithm, thus improving irrigation predictability. …”
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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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