An Efficient Method for Mining Erasable Itemsets Using Multicore Processor Platform by Bao Huynh, Bay Vo

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Network-, Cost-, and Renewable-Aware Ant Colony Optimization for Energy-Efficient Virtual Machine Placement in Cloud Datacenters by Ali Mohammad Baydoun, Ahmed Sherif Zekri

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TEORÍA DE INVENTARIOS APLICACIÓN DE LA TEORIA DE INVENTARIOS EN LA EMPRESA KJANTU COLLECTION S.A.C. by Jean Paul Santiago Tumialán

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Establishment and performance analysis of RIS-assisted coded relay cooperation system based on LDPC product codes by Shunwai ZHANG, Jin WANG

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Unmanned Aerial Vehicle Surveying and Mapping Trajectory Scheduling and Autonomous Control for Landslide Monitoring by Shifang Liao, Manzhu Ye, Rongcai Yuan, Wanzhi Ma

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Information-extremе machine learning for object identification on the terrain by V. V. Moskalenko, A. H. Korobov

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Optimized Trust Prediction and Multi-Criteria Framework for Task and Data Collector Selection Using Deep Learning in Ubiquitous Environments by Ahmed A. A. Gad-Elrab

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Adaptive Cooperative Quality Weight Spectrum Sensing for Mitigating Byzantine Attacks in Cognitive Radio by Kanabadee Srisomboon, Luepol Pipanmekaporn, Akara Prayote, Wilaiporn Lee

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A novel method to predict white blood cells after kidney transplantation based on machine learning by Songping He, Xiangxi Li, Zunyuan Zhao, Bin Li, Xin Tan, Hui Guo, Yanyan Chen, Xia Lu

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A prospective cluster randomized trial of an interventions bundle to reduce inappropriate antibiotic use for upper respiratory tract infections in the outpatient setting by Adeel A. Butt, Sherin Shams, Atika Jabeen, Asma Ali Al-Nuaimi, Jeyaram Illiayaraja Krishnan, Aimon B. Malik, Samah Saleem, Maryam Hassan Abdulaziz, Naheel Ismail Seyam, Kamran Aziz, Dalia Kandil, Anil G. Thomas, Hanaa Nafady-Hego, Muzna I. Lone, Jameela Al Ajmi, Zain A. Bhutta, Noora AlSulaiti, Wael E. Said Hussein, Sandy Semaan, Samya Ahmad Al-Abdulla, Mohamed Ghaith Al-Kuwari, Abdul-Badi Abou-Samra

“…Intervention Bundled 4-component intervention including extensive provider education, a decision support algorithm, option for deferred antibiotics prescription, and monthly feedback on prescription patterns, vs. a single randomly assigned intervention (decision support algorithm). …”
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EUS-based intratumoral and peritumoral machine learning radiomics analysis for distinguishing pancreatic neuroendocrine tumors from pancreatic cancer by Shuangyang Mo, Shuangyang Mo, Nan Yi, Fengyan Qin, Huaying Zhao, Huaying Zhao, Yingwei Wang, Haiyan Qin, Haixiao Wei, Haixing Jiang, Shanyu Qin

“…Following this, the radiomic features underwent dimensionality reduction through the utilization of the least absolute shrinkage and selection operator (LASSO) algorithm. Six machine learning algorithms were utilized to train prediction models employing features with nonzero coefficients. …”
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Crack Tracking in Small-Diameter Metal Pipe Using Controlled Motor Vibrations and Flexible Sensor by Md Rabiul Awal, Nurul Atiqah Tajulmar, Muhammad Syarifuddin Yahya, Nurafnida Afrizal, Wan Hafiza Wan Hassan, Nurul Adilah Abdul Latiff, Shakir Saat

“…However, it is very tricky in the case of a bent pipe, as the pressure differences are less than 300 a.u. for three conditions and above for only one. Hence, it might provoke an incorrect decision when detecting a bent pipe. …”
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Machine learning based screening of biomarkers associated with cell death and immunosuppression of multiple life stages sepsis populations by Jie Yang, Fanyan Ou, Binbin Li, Lixiong Zeng, Qiuli Chen, Houyu Gan, Jianing Yu, Qian Guo, Jihua Feng, Jianfeng Zhang

“…Nine machine learning algorithms (Logistic Regression LR, Decision Tree DT, Gradient Boosting Machine GBM, K-Nearest Neighbors KNN, LASSO, Principal Component Analysis PCA, Random Forest RF, Support Vector Machine SVM, and XGBoost) were applied to training and testing datasets with 10-fold cross-validation to select three optimized algorithm models. …”
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Sleep Stage Classification using Laplacian Score Feature Selection Method by Single Channel EEG by Mahtab Vaezi, Mehdi Nasri

“…Simulation results confirms the superiority of the proposed method based on the classification results. With the proposed algorithm, 2, 3, 4, 5 and 6 stages of sleep were classified by SVM and decision tree with 98.0%, 98.0%, 97.3%, 96.6%, and 95.0% accuracy, which are more superior to previous methodâs results.…”
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Development of a machine learning-derived model to predict unplanned ICU admissions after major non-cardiac surgery by Catherine Chiu, Matthias R. Braehler, Anne L. Donovan, Atul J. Butte, Romain Pirracchio, Andrew M. Bishara

“…We developed our prediction model with a gradient-boosting decision tree algorithm (XGBoost). The model incorporated sixteen generalizable predictor variables that were derived from the demographics and surgical booking details. …”
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Distinguishing novel coronavirus influenza A virus pneumonia with CT radiomics and clinical features by Lianyu Sui, Huan Meng, Jianing Wang, Wei Yang, Lulu Yang, Xudan Chen, Liyong Zhuo, Lihong Xing, Yu Zhang, Jingjing Cui, Xiaoping Yin

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Difference Equation Model-Based PM2.5 Prediction considering the Spatiotemporal Propagation: A Case Study of Bohai Rim Region, China by Ceyu Lei, Xiaoling Han, Chenghua Gao

“…The mean absolute error (MAE) of the forecast data for each urban agglomeration is within 7 units μg/m3. The experimental results show that the difference equation model can effectively reduce the prediction time, improve the prediction accuracy, and provide decision support for local air pollution early warning and urban comprehensive management.…”
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Agile DQN: adaptive deep recurrent attention reinforcement learning for autonomous UAV obstacle avoidance by Fadi AlMahamid, Katarina Grolinger

“…Abstract Unmanned Aerial Vehicle (UAV) obstacle avoidance in 3D environments demands sophisticated handling of high-dimensional inputs and effective state representations. …”
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Dynamic weighted ensemble model for predictive optimization in green sand casting: Advancing industry 4.0 manufacturing by Rajesh V․ Rajkolhe, Dr. Sanjay S․ Bhagwat, Dr. Priyanka V․ Deshmukh

“…The model dynamically allocates weights to top-performing algorithms based on their 10-fold cross-validated RMSE, ensuring robust and adaptive prediction performance.Five models—Linear Regression, Ridge Regression, Decision Tree, Random Forest, and Gradient Boosting—were evaluated over ten folds. …”
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Using machine learning to identify key predictors of maternal success in sheep for improved lamb survival by Ebru Emsen, Bahadir Baran Odevci, Muzeyyen Kutluca Korkmaz

“…Several machine learning algorithms, including Random Forest, Decision Trees, Logistic Regression, and Support Vector Machines (SVM), were evaluated for predictive accuracy. …”
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