Predicting Landslide Deposit Zones: Insights from Advanced Sampling Strategies in the Ilopango Caldera, El Salvador by Laura Paola Calderon-Cucunuba, Abel Alexei Argueta-Platero, Tomás Fernández, Claudio Mercurio, Chiara Martinello, Edoardo Rotigliano, Christian Conoscenti

“…This study aimed to evaluate the predictive capability of identifying where displaced material might be deposited by using different inventories of specific parts of a landslide, including the source area, intermediate area, and deposition area. …”
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Deep learning-based analysis of daily activity patterns of farmed dromedary camels by Rama Al-Khateeb, Nabil Mansour, Nabil Mansour, Shaher Bano Mirza, Fouad Lamghari

“…In Phase 2, the study expanded to include six camels, enabling an evaluation of individual behavioral variations. The YOLOv7 object detection algorithm was used to train and validate the model on images extracted from the recordings, achieving high accuracy in detecting and classifying the defined activities.ResultsThe results showed notable variations in activity patterns between Phases 1 and 2. …”
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Monitoring of Indoor Air Quality in a Classroom Combining a Low-Cost Sensor System and Machine Learning by Ioannis D. Apostolopoulos, Eleni Dovrou, Silas Androulakis, Katerina Seitanidi, Maria P. Georgopoulou, Angeliki Matrali, Georgia Argyropoulou, Christos Kaltsonoudis, George Fouskas, Spyros N. Pandis

“…ML-based calibration was investigated for the CO, NO, NO₂, and O₃ sensors using measurements by reference instruments for training and evaluation. Among the eleven ML algorithms tested, the Support Vector Regression performed better for the calibration of the CO, NO₂, and O₃ sensors. …”
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Trusted Energy-Aware Hierarchical Routing (TEAHR) for Wireless Sensor Networks by Vikas, Charu Wahi, Bharat Bhushan Sagar, Manisha Manjul

“…The comparisons of TEAHR with conventional techniques show that the proposed algorithm reduces total latency by 15%, enhances energy efficiency by around 20%, and maintains a stable packet forwarding rate, which is highly desirable for accurate operation in adversarial environments, as demonstrated through comparative analysis. …”
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Capacity Prognostics of Marine Lithium-Ion Batteries Based on ICPO-Bi-LSTM Under Dynamic Operating Conditions by Qijia Song, Xiangguo Yang, Telu Tang, Yifan Liu, Yuelin Chen, Lin Liu

“…Finally, to prevent the interference of test data during model training, which could lead to evaluation errors, the training dataset is used for parameter fitting, the validation dataset for hyperparameter adjustment, and the test dataset for the model performance evaluation. …”
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Identification breeds equity: the regulation effect of group decision-making on beauty premium by Lu Cheng, Qingguo Ma, Yijin He, Yulin Tan, Linanzi Zhang, Wenwei Qiu

“…For exploring the underlying mechanism, this study employed a genetic-algorithm-based modelling method to analyse participants’ trial-by-trial dynamic adjustment in group environment. …”
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Generalizing location-centric variations to enhance contactless human activity recognition by Fawad Khan, Syed Yaseen Shah, Jawad Ahmad, Alanoud Al Mazroa, Adnan Zahid, Muhammed Ilyas, Qammer Hussain Abbasi, Syed Aziz Shah

“…To address this challenge, in this study, we present a novel federated learning (FL) algorithm designed to train a robust global model from local datasets in different localizations. …”
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Defining disease phenotypes using national linked electronic health records: a case study of atrial fibrillation. by Katherine I Morley, Joshua Wallace, Spiros C Denaxas, Ross J Hunter, Riyaz S Patel, Pablo Perel, Anoop D Shah, Adam D Timmis, Richard J Schilling, Harry Hemingway

“…<h4>Results</h4>The phenotype algorithm incorporated 286 codes: 201 Read, 63 BNF, 18 ICD-10, and four OPCS-4. …”
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New Method for Interpreting Gas and Water Production in Horizontal Gas Wells Based on Array Flow Imaging Logging by CHEN Haixiang, ZHENG Xiaomin, LIU Heng, LUO Ning, YANG Guofeng, CHEN Meng

“…Using an interpolation iteration algorithm, the accurate quantitative calculation of gas and water phase flow rates in horizontal wells is achieved, effectively eliminating the impact of changes in probe spatial positions during different measurement runs on the calculated apparent fluid velocity and water holdup. …”
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Integrating Machine Learning Workflow into Numerical Simulation for Optimizing Oil Recovery in Sand-Shale Sequences and Highly Heterogeneous Reservoir by Dung Bui, Abdul-Muaizz Koray, Emmanuel Appiah Kubi, Adewale Amosu, William Ampomah

“…This paper aims to evaluate the efficiency of various machine learning algorithms integrating with numerical simulations in optimizing oil production for a highly heterogeneous reservoir. …”
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Preoperative diagnosis of meningioma sinus invasion based on MRI radiomics and deep learning: a multicenter study by Yuan Gui, Wei Hu, Jialiang Ren, Fuqiang Tang, Limei Wang, Fang Zhang, Jing Zhang

“…Finally, diagnosis models were constructed using the random forest (RF) algorithm. Additionally, the diagnostic performance of different models was evaluated using receiver operating characteristic (ROC) curves, and AUC values of different models were compared using the DeLong test. …”
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Simultaneous determination of 7 thiols associated proteins in lymphoma patients’serum and cerebrospinal fluid by UHPLC-HRMS technique by Qingkun Ma, Mei Zhang, Yongshuai Fan, Han Zhao, Kun Wang, Xiaojing Wang, Yanling Mu

“…Furthermore, a novel PCNSL monitoring model was developed based on different those combined with machine learning algorithm. …”
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Machine learning assisted estimation of total solids content of drilling fluids by B.T. Gunel, Y.D. Pak, A.Ö. Herekeli, S. Gül, B. Kulga, E. Artun

“…In the final stage, different evaluation metrics were employed to evaluate and compare the performance of different classes of machine learning models. …”
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Free-living use of artificial pancreas for children with type 1 diabetes: systematic review by Klemen Dovc, Gül Yeşiltepe Mutlu, Yury I. Philippov, Dmitry N. Laptev, Evgenia M. Patrakeeva, Lubov O. Chernilova, Alsu G. Zalevskaya, Marina V. Shestakova, Tadej Battelino

“…Only 3 RCT showed decrease of the time in range within 24 h evaluation period. In one RCT the significant positive differences have been shown in the time in range for dual hormone closed-loop glucose control system in compare with insulin-only artificial pancreas. …”
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Expeditious Dynamic Clustering in Preprocessing for High-Performance Classification by Anamika Pimpa, Narissara Eiamkanitchat

“…The accuracy of classification algorithms across different applications is significantly influenced by data preprocessing. …”
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Energy and Reserve Scheduling of Distribution Network in Presence of Electric Vehicle Aggregators: A Decentralized Approach by Atena Tazikeh Lemeski, Reza Ebrahimi, Alireza Zakariazadeh, Keyvan Firuzi

“…The proposed distributed algorithm is tested and evaluated on a standard distribution network consisting of AGG and DGs. …”
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Optimizing Metro Passenger Flow Prediction: Integrating Machine Learning and Time-Series Analysis with Multimodal Data Fusion by Li Wan, Wenzhi Cheng, Jie Yang

“…First, the STL decomposition algorithm is applied to break down the preprocessed data into trend terms, periodic terms, and irregular fluctuation terms. …”
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Using Time Clusters for Following Users’ Shifts in Rating Practices by Dionisis Margaris, Costas Vassilakis

“…Users that enter ratings for items follow different rating practices, in the sense that, when rating items, some users are more lenient, while others are stricter. …”
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Maximum Energy Absorbed from the Persian Gulf Waves Considering Uncertainty in Power Take off Parameters by Mohammad Jalali, Reihaneh Kardehi Moghaddam, Naser Pariz

“…In this scheme, to consider high uncertainty in the parameters of the power take-off system in different atmospheric conditions and improve controller performance, a new improved black hole algorithm is introduced to tune fuzzy controller parameters. …”
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Clustering OKU Timur Script Images using VGG Feature extraction and K-Means by Liu Toriko, Susan Dian Purnamasari, Yesi Novaria Kunang, Ilman Zuhri Yadi, Andri Andri

“…Features are extracted using the VGG16 model, which are then clustered with the K-Means algorithm. Clustering performance is evaluated based on the percentage of correctly grouped characters. …”
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