Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis by Ali Nabavi, Mohammad Kashkooli, Sara Sadat Nabavizadeh, Farimah Safari

“…Multiple machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, Logistic Regression, CatBoost, and MLP, were optimized and evaluated. …”
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Energy-Efficient UAV Relaying Robust Resource Allocation in Uncertain Adversarial Networks by Shakil Ahmed, Mostafa Zaman Chowdhury, Saifur Rahman Sabuj, Md Imtiajul Alam, Yeong Min Jang

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Implementasi Algoritma AES 256 CBC, BASE 64, Dan SHA 256 dalam Pengamanan dan Validasi Data Ujian Online by Ferzha Putra Utama, Gusman Wijaya, Ruvita Faurina, Arie Vatresia

“…Abstract There are various ways to organize exams at the higher education level. During the Covid-19 pandemic, the online examination method has become widely used. …”
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Rapid and accurate multi-phenotype imputation for millions of individuals by Lin-Lin Gu, Hong-Shan Wu, Tian-Yi Liu, Yong-Jie Zhang, Jing-Cheng He, Xiao-Lei Liu, Zhi-Yong Wang, Guo-Bo Chen, Dan Jiang, Ming Fang

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Post-Quantum Cryptographic Frameworks for Internet of Things (IoT) and Internet of Medical Things (IoMT) Authentication Systems by Thomas L Barna, Samson Isaac, Christopher Habu, Saratu Habu, Abimbola A Joseph

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La Teoría del andamiaje como herramienta de construcción del pensamiento matemático by Cesar Orlando Vargas Mantilla, Sonia Maritza Mendoza Lizcano, Wlamyr Palacios Alvarado

“…This manifest weakness is observed with concern at different educational stages, but the research focused on the teachers who teach knowledge to first-semester engineering students at Francisco de Paula Santander University, more specifically those taking Calculus I or Integral Calculus. …”
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An Approach for Multi-Source Land Use and Land Cover Data Fusion Considering Spatial Correlations by Jing Yang, Yiheng Jiang, Qirui Song, Zheng Wang, Yang Hu, Kaiqiang Li, Yizhong Sun

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Multi Objective Prioritized Workflow Scheduling Using Deep Reinforcement Based Learning in Cloud Computing by Sudheer Mangalampalli, Syed Shakeel Hashmi, Amit Gupta, Ganesh Reddy Karri, K. Varada Rajkumar, Tulika Chakrabarti, Prasun Chakrabarti, Martin Margala

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Diagnosis and detection of bone fracture in radiographic images using deep learning approaches by Theyazn Aldhyani, Zeyad A. T. Ahmed, Bayan M. Alsharbi, Sultan Ahmad, Sultan Ahmad, Mosleh Hmoud Al-Adhaileh, Ahmed Hassan Kamal, Mohammed Almaiah, Jabeen Nazeer

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The design of copper flotation process based on multi-label classification and regression by Haipei Dong, Fuli Wang, Dakuo He, Yan Liu

“…Moreover, further improves the prediction effect through the following methods: (1) Referencing adaboost algorithm, the training set samples with large prediction error in the previous iteration are set with higher weight; (2) To enhance robustness, the label uncertainty coefficient is introduced; (3) To alleviate the over fitting of small sample machine learning, bootstrap aggregating is introduced for each sub label. …”
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Field Test and Numerical Research of Blast-Induced Liquefaction in Calcareous Sand by Changchun Li, Yumin Chen, Yingkang Yao, Yonggang Gou, Qiongting Wang, Junwei Guo, Xiao Xie

“…The research results can provide a theoretical reference for the prediction of blast-induced liquefaction in saturated calcareous sand foundations.…”
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Risk assessment of tunnel water inrush based on Delphi method and machine learning by Leizhi Dong, Qingsong Wang, Weiguo Zhang, Yongjun Zhang, Xiaoshuang Li, Fei Liu

“…Then, the Radial Basis Function (RBF) network, improved by the Locally Linear Embedding (LLE) algorithm and the Particle Swarm Optimization (PSO), is applied to predict the risk level. …”
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Wound imaging software and digital platform to assist review of surgical wounds using patient smartphones: The development and evaluation of artificial intelligence (WISDOM AI stud... by Melissa Rochon, Judith Tanner, James Jurkiewicz, Jacqueline Beckhelling, Akuha Aondoakaa, Keith Wilson, Luxmi Dhoonmoon, Max Underwood, Lara Mason, Roy Harris, Karen Cariaga

“…Secondary objectives focused on specificity, positive predictive value (PPV), and negative predictive value (NPV) for various wound features.…”
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Robust techno-economic optimization of energy hubs under uncertainty using active learning with artificial neural networks by Aya M. A. Heikal, Shady H. E. Abdel Aleem, Ragab A. El-Sehiemy, Almoataz Y. Abdelaziz

“…Results demonstrate significant improvements in system reliability, cost efficiency, and flexible operation, validating the effectiveness of ANN-based AL to optimize EHs management and ensure sustainable operation complexities. The AL algorithm enhances the ANN model’s predictive ability, resulting in a 57.9% decrease in operating costs and a 0.010682 loss of energy supply probability (LESP) value. …”
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Full-scale simulator to test a control system of an engine-propeller powerplant of a convertible aerial vehicle by D. V. Vereshchikov, I. K. Makarov, I. S. Moiseeva, S. M. Barantsev

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Developing an Artificial Neural Network-Based Grading Model for Energy Consumption in Residential Buildings by Yaser Shahbazi, Sahar Hosseinpour, Mohsen Mokhtari Kashavar, Mohammad Fotouhi, Siamak Pedrammehr

“…The collected data informed the ANN model, enabling accurate predictions for existing and future constructions. The results demonstrate that the model achieves a remarkable prediction error of just 0.001, facilitating efficient energy assessments without requiring extensive modeling expertise. …”
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Blinded Validation of Breath Biomarkers of Lung Cancer, a Potential Ancillary to Chest CT Screening. by Michael Phillips, Thomas L Bauer, Renee N Cataneo, Cassie Lebauer, Mayur Mundada, Harvey I Pass, Naren Ramakrishna, William N Rom, Eric Vallières

“…The algorithm predicted discriminant function (DF) values in blinded replicate breath VOC samples analyzed independently at two laboratories (A and B). …”
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Hybrid Artificial Neural Network Activation Function to Reduce Water Wastage in Agricultural Irrigation by Baraa H. Jawad, Ola A. Alwesabi, Nibras Abdullah, Ahmed Abed Mohammed

“…The study proposes a hybrid activation function based on the Artificial Neural Network algorithm. This function is used to classify the need for irrigation in various crops and predict the best time of the day for watering. …”
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Explainable artificial intelligence visions on incident duration using eXtreme Gradient Boosting and SHapley Additive exPlanations by Khaled Hamad, Emran Alotaibi, Waleed Zeiada, Ghazi Al-Khateeb, Saleh Abu Dabous, Maher Omar, Bharadwaj R.K. Mantha, Mohamed G. Arab, Tarek Merabtene

“…This study introduces an application of Explainable Artificial Intelligence (XAI) using eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP) to analyze the complexities of traffic incident duration prediction. Utilizing a substantial dataset of over 366,000 records from the Houston traffic management center, the study innovates in the domain of traffic analytics by predicting incident durations and revealing the contribution of each predictive variable. …”
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A new method for determining factors Influencing productivity of deep coalbed methane vertical cluster wells by HUANG Li, XIONG Xianyue, WANG Feng, SUN Xiongwei, ZHANG Yixin, ZHAO Longmei, SHI Shi, ZHANG Wen, ZHAO Haoyang, JI Liang, DENG Lin

“…This method leverages the advantages of multiple machine-learning algorithms, demonstrating strong operability and improving the accuracy of CBM dynamic predictions. …”
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