The Establishment and Evaluation Model of the Thematic Deep-Learning Teaching Module by Kai-Chao Yao, Li-Chiou Hsu, Jiunn-Shiou Fang, Yi-Jung Chen, Zhou-Kai Guo

“…The psychomotor scale established by the scholars was adopted and revised, including this study’s technical ability indicators. …”
Get full text

Large Language Models (LLMs) as Traffic Control Systems at Urban Intersections: A New Paradigm by Sari Masri, Huthaifa I. Ashqar, Mohammed Elhenawy

“…The study utilizes their logical reasoning, scene understanding, and decision-making capabilities to optimize throughput and provide feedback based on traffic conditions in real time. …”
Get full text

Developing an Intelligent Resume Screening Tool With AI‐Driven Analysis and Recommendation Features by K. L. Abhishek, M. Niranjanamurthy, Shonit Aric, Syed Immamul Ansarullah, Anurag Sinha, G. Tejani, Mohd Asif Shah

“…ABSTRACT Current resume screening relies on manual review, causing delays and errors in evaluating large volumes of resumes. …”
Get full text

Prediction of clinical stages of cervical cancer via machine learning integrated with clinical features and ultrasound-based radiomics by Maochun Zhang, Qing Zhang, Xueying Wang, Xiaoli Peng, Jiao Chen, Hanfeng Yang

“…Plot calibration curves and clinical decision curves were used to assess model efficacy. …”
Get full text

Water Mass Transformation Budgets in Finite‐Volume Generalized Vertical Coordinate Ocean Models by Henri F. Drake, Shanice Bailey, Raphael Dussin, Stephen M. Griffies, John Krasting, Graeme MacGilchrist, Geoffrey Stanley, Jan‐Erik Tesdal, Jan D. Zika

“…We illustrate key aspects of the methodology through the analysis of a polygonal region of the Greater Baltic Sea in a regional demonstration simulation using the Modular Ocean Model v6 (MOM6). …”
Get full text

Large Language Models in Transportation: A Comprehensive Bibliometric Analysis of Emerging Trends, Challenges, and Future Research by Mahbub Hassan, Md. Emtiaz Kabir, Muzammil Jusoh, Hong Ki An, Michael Negnevitsky, Chengjiang Li

“…The study used Scopus as the primary data source, applying Bibliometrix, VOSviewer, and Python for performance analysis and science mapping. …”
Get full text

Efficient diagnosis of diabetes mellitus using an improved ensemble method by Blessing Oluwatobi Olorunfemi, Adewale Opeoluwa Ogunde, Ahmad Almogren, Abidemi Emmanuel Adeniyi, Sunday Adeola Ajagbe, Salil Bharany, Ayman Altameem, Ateeq Ur Rehman, Asif Mehmood, Habib Hamam

“…The first phase utilized J48, Classification and Regression Tree (CART), and Decision Stump (DS) to create a random forest model. …”
Get full text

Machine Learning for Identifying Damage and Predicting Properties in 3D-Printed PLA/Lygeum Spartum Biocomposites by Khalil Benabderazag, Moussa Guebailia, Zouheyr Belouadah, Lotfi Toubal, Salah Eddine Tachi

“…The processed dataset, comprising six normalized features (cumulative rise, duration, count, frequency, energy, and amplitude) was used to train four ML models: Random Forest Regression (RFR), Support Vector Regression (SVR), Artificial Neural Networks (ANN), and Decision Trees (DT) implemented in Python using libraries such as scikit-learn, pandas, and numpy. …”
Get full text

Analysis of the most influential factors affecting outcomes of lung transplant recipients: a multivariate prediction model based on UNOS Data by Reza Safdari, Marsa Gholamzadeh, Hamidreza Abtahi, Mehrnaz Asadi Gharabaghi

“…Subsequently, we developed a web-based decision support tool using Python and the Streamlit framework based on the best-fine-tuned model.Conclusion The deployment of the ML model has the potential to act as an automated tool to aid physicians in assessing the priority of lung transplants and identifying significant factors that play a role in patient survival.…”
Get full text

EzSkiROS: enhancing robot skill composition with embedded DSL for early error detection by Momina Rizwan, Christoph Reichenbach, Ricardo Caldas, Matthias Mayr, Volker Krueger

“…We describe design patterns suitable for robot programming and show how to use these design patterns for DSL embedding in Python, using two case studies on an open-source robot skill platform SkiROS2, designed for the composition of robot skills. …”
Get full text

Processing of Polymers Stress Relaxation Curves Using Machine Learning Methods by Anton S. Chepurnenko, Tatiana N. Kondratieva, Ebrahim Al-Wali

“…Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. …”
Get full text

Clasificación estadística supervisada para analizar el impacto del propóleo sobre las bacterias Actinomyces viscosus y Streptococcus mutans by Herman Alfredo Dávila Pinto, David Sebastián Dávila Vinueza, Milena Guadalupe Castillo Mena, Helen Nicole López Romo

“…Los datos fueron modelados mediante un sistema computacional de clasificación en Python usando árboles de decisión, que permitieron predecir el nivel de sensibilidad bacteriana (sin sensibilidad, baja, alta, extremadamente alta) en función del tipo de bacteria y del halo inhibitorio observado. …”
Get full text

Perturbation based privacy preservation and classification using Jaya Algorithm and Dragonfly Inspired Algorithm by Dipanwita Sen, Bhupati Bhusan Mishra, Prasant Kumar Pattnaik

“…The classical classifiers used are Decision Tree, Random Forest, AdaBoost, KNN and GNB. …”
Get full text

Analysis to Predict the Number of New Students At UNU Pasuruan using Arima Method by Fachri Ayudi Fitrony, Laksmita Dewi Supraba, Tessa Rantung, I Made Artha Agastya, Kusrini Kusrini

“…The analysis is performed using statistical software such as Python to improve the accuracy and efficiency of the process. …”
Get full text

Prediction of stunting and its socioeconomic determinants among adolescent girls in Ethiopia using machine learning algorithms. by Alemu Birara Zemariam, Biruk Beletew Abate, Addis Wondmagegn Alamaw, Eyob Shitie Lake, Gizachew Yilak, Mulat Ayele, Befkad Derese Tilahun, Habtamu Setegn Ngusie

“…Region, poor wealth index, no formal education, unimproved toilet facility, rural residence, not used contraceptive method, religion, age, no media exposure, occupation, and having one or more children were the top attributes to predict stunting. …”
Get full text

Predicting pregnancy loss and its determinants among reproductive-aged women using supervised machine learning algorithms in Sub-Saharan Africa by Tirualem Zeleke Yehuala, Sara Beyene Mengesha, Nebebe Demis Baykemagn

“…Python software was used to process the data, and machine learning techniques such as Random Forest, Decision Tree, Logistic Regression, Extreme Gradient Boosting, and Gaussian were applied. …”
Get full text

Vector-Like Quarks at the LHC: A unified perspective from ATLAS and CMS exclusion limits by R. Benbrik, M. Boukidi, M. Ech-chaouy, S. Moretti, K. Salime, Q. S. Yan

“…The results were computed using VLQBounds, a new Python-based tool specifically developed for this purpose.…”
Get full text

Optimization of rectangular micro-channel heat exchangers for use in HCPV panels through genetic algorithm by Pedro D. Pontes, Luz Elena P. Chenche, João A. Lima, Carolina P. Naveira-Cotta, Ana S. Moita

“…Although only single-phase flows are handled now, the algorithm can be extended to other flow regimes. As key findings, one can stress that the algorithm devised in-house works well in the optimization of the number vs dimensions of straight microchannels, for single-phase flows. …”
Get full text

Digitalization As a Socio-Economic Challenge: Modeling the Impact On the Level of Cybercrime Considering Socio-Economic, Technological and Institutional Factors by Hanna Yarovenko, Olha Horbachova, Roman Bylbas, Dmytro Latysh

“…The scale of cyber incidents is closely related to several additional factors of decisive importance. These include: state regulation of cybersecurity, national legislation, digital competence of users and the technological potential of cybercriminals. …”
Get full text

Improving network security using keyboard dynamics: A comparative study by Ugwunna, C.O., Chukwuogo, O.E., Alabi, O.A., Kareem, M.K., Belonwu, T.S., Oloyede, S.O.

“…According to the results, the accuracy of the Random Forest, Support Vector Machine, KNN, and Decision Tree algorithms are, respectively, 98, 97.55, 97.28, and 94.26%. …”
Get full text