MTAD: A Multitarget Heuristic Algorithm for Virtual Machine Placement by Lei Chen, Jing Zhang, Lijun Cai, Rui Li, Tingqin He, Tao Meng

“…Firstly, we propose a physical machine (PM) classification algorithm by analyzing pseudotime complexity and find out an important factor (the number of physical hosts) that affects the efficiency, which improves running efficiency through reduction number of physical hosts; secondly, we present a VM placement optimization model using multitarget heuristic algorithm and figure out the positive and negative vectors of three goals using matrix transformation so as to provide the mapping of VMs to hosts by comparing distance with positive and negative vectors such that the energy consumption is saved, resources wastage of occupied PM is lowered, multidimension resource utilization is optimized, and the running time is shortened. …”
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Advancing Sub-Seasonal to Seasonal Streamflow Forecasting in Canada: A Review of Conventional and Emerging Approaches for Operational Applications by Duc Hai Nguyen, Amin Elshorbagy, Muhammad Naveed Khaliq, Chaopeng Shen, Mohammad Khaled Akhtar, Mohamed Moghairib, Fisaha Unduche, Saman Razavi, Philippe Lamontagne

“…This paper reviews state-of-the-art in S2S streamflow forecasting, considering conventional process-based and statistical modeling approaches, emerging machine learning (ML) techniques, and hybrid options. …”
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Implementation of Machine Vision Methods for Cattle Detection and Activity Monitoring by Roman Bumbálek, Tomáš Zoubek, Jean de Dieu Marcel Ufitikirezi, Sandra Nicole Umurungi, Radim Stehlík, Zbyněk Havelka, Radim Kuneš, Petr Bartoš

“…However, the accuracy of the trained model was 6 per cent higher (0.8969) when using the SGD optimizer.…”
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Design and Experiment of the Belt-Tooth Residual Film Recovery Machine by Zebin Gao, Xinlei Zhang, Jiaxi Zhang, Yichao Wang, Jinming Li, Shilong Shen, Wenhao Dong, Xiaoxuan Wang

“…To address poor film pickup, incomplete soil–film separation, and high soil content in conventional residual film recovery machines, this study designed a belt-tooth type residual film recovery machine. …”
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Machine Learning System for Predicting Cardiovascular Disorders in Diabetic Patients by A. Mayya, H. Solieman

“…Feature selection methods were used to derive the most significant indicators for predicting CVD risk in diabetic patients. Performance optimization of the developed classification and prediction models was carried out based on different evaluation metrics.Results. …”
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Machine learning frameworks to accurately predict coke reactivity index by Ayat Hussein Adhab, Morug Salih Mahdi, Krunal Vaghela, Anupam Yadav, Jayaprakash B, Mayank Kundlas, Ankur Srivastava, Jayant Jagtap, Aseel Salah Mansoor, Usama Kadem Radi, Nasr Saadoun Abd, Samim Sherzod

“…In this research, several machine learning predictive models based on extra trees, decision tree, support vector machine, random forest, multilayer perceptron artificial neural network, K-nearest neighbors, convolutional neural network, ensemble learning, and adaptive boosting using a dataset gathered from a coke plant are developed to predict CRI. …”
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Dynamic Positioning and Optimization of Magnetic Target Based on Binocular Vision by Jing Li, Yang Wang, Ligang Qu, Guangming Lv, Zhenyu Cao

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Efficiency Analysis and Optimization of Two-Speed-Region Operation of Permanent Magnet Synchronous Motor Taking into Account Iron Loss Based on Linear Non-Equilibrium Thermodynamic... by Ihor Shchur, Yurii Biletskyi, Bohdan Kopchak

“…For IPMSM, taking into account iron loss, a mathematical model of the corresponding PC has been built, and an algorithm and research program have been developed, which is valid in a wide range of machine speed regulations. …”
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Research on Forced Cooling of Machine Tools and its Operational Effects by Jerzy JEDRZEJEWSKI, Zdzislaw WINIARSKI, Wojciech KWASNY

“…The essence and methods of forced cooling parameters improvement through holistic modelling, numerical simulations and optimization are presented. …”
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Optimizing Open Radio Access Network Systems with LLAMA V2 for Enhanced Mobile Broadband, Ultra-Reliable Low-Latency Communications, and Massive Machine-Type Communications: A Fram... by H. Ahmed Tahir, Walaa Alayed, Waqar ul Hassan, Thuan Dinh Do

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Leveraging machine learning in nursing: innovations, challenges, and ethical insights by Sophie So Wan Yip, Sheng Ning, Niki Yan Ki Wong, Jeffrey Chan, Kei Shing Ng, Bernadette Oi Ting Kwok, Robert L. Anders, Simon Ching Lam

“…Aim/objectiveThis review aims to provide a comprehensive analysis of the integration of machine learning (ML) (1) in nursing by exploring its implications on patient care, nursing practices, and healthcare delivery. …”
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Machine-learning driven strategies for adapting immunotherapy in metastatic NSCLC by Maliazurina B. Saad, Qasem Al-Tashi, Lingzhi Hong, Vivek Verma, Wentao Li, Daniel Boiarsky, Shenduo Li, Milena Petranovic, Carol C. Wu, Brett W. Carter, Girish S. Shroff, Tina Cascone, Xiuning Le, Yasir Y. Elamin, Mehmet Altan, Simon Heeke, Ajay Sheshadri, Joe Y. Chang, Percy P. Lee, Zhongxing Liao, Don L. Gibbons, Ara A. Vaporciyan, J. Jack Lee, Ignacio I. Wistuba, Cara Haymaker, Seyedali Mirjalili, David Jaffray, Justin F. Gainor, Yanyan Lou, Alessandro Di Federico, Federica Pecci, Mark Awad, Biagio Ricciuti, John V. Heymach, Natalie I. Vokes, Jianjun Zhang, Jia Wu

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A review on machine learning applications in hydrogen energy systems by Zaid Allal, Hassan N. Noura, Ola Salman, Flavien Vernier, Khaled Chahine

“…We also present the advantages and limitations of applying ML models in this field, offering recommendations for their optimal use. …”
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Machine Learning Algorithms in Predicting Prices in Volatile Cryptocurrency Markets by Miguel Jiménez-Carrión, Gustavo A. Flores-Fernandez

“…The model's performance was optimized through hyperparameter tuning, and its stability was validated using an analysis of variance (ANOVA). …”
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Application of Machine Learning to Statistical Evaluation of Artificial Rainfall Enhancement by Li Dan, Lin Wen, Liu Qun, Feng Hongfang, Hu Shuping, Wang Zhihai

“…The performance of the model established by CNN method is relatively optimal, with determination coefficient R2 up to 0.658 and RMSE only 0.2 mm1/2, followed by SVM statistical model based on sixth-order root square transform data, with R2 being 0.41 and RMSE being 0.203 mm1/2. …”
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Machine Learning-Based Highway Pavement Performance Prediction in Xinjiang by Qi Yang, Wei Tian, Xiaomin Dai

“…We integrate various factors (design, materials, environment, traffic, and maintenance) into regression models, creating a region-specific pavement performance decay model. …”
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A scalable machine learning strategy for resource allocation in database by Fady Nashat Manhary, Marghny H. Mohamed, Mamdouh Farouk

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The analysis of fraud detection in financial market under machine learning by Jing Jin, Yongqing Zhang

“…Therefore, this paper proposes a financial fraud detection model based on Stacking ensemble learning algorithm, which integrates many basic learners such as logical regression (LR), decision tree (DT), random forest (RF), Gradient Boosting Tree (GBT), support vector machine (SVM) and neural network (NN), and introduces feature importance weighting and dynamic weight adjustment mechanism to improve the model performance. …”
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Early-Stage State-of-Health Prediction of Lithium Batteries for Wireless Sensor Networks Using LSTM and a Single Exponential Degradation Model by Lorenzo Ciani, Cristian Garzon-Alfonso, Francesco Grasso, Gabriele Patrizi

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A Novel Support Vector Machine with Globality-Locality Preserving by Cheng-Long Ma, Yu-Bo Yuan

“…However, the solution of the primal optimal model of SVM is susceptible for class distribution and may result in a nonrobust solution. …”
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