Evaluating the feasibility of using crystalline patterns induced by PBF-LB to predict strength enhancing orientations by José David Pérez-Ruiz, Luis Norberto López de Lacalle, Wilmer Velilla-Díaz, Jaime A. Mesa, Gaizka Gómez, Heriberto Maury, Gorka Urbikain, Haizea Gonzalez

“…This work presents a unified methodology and models for evaluating the feasibility of leveraging these crystalline patterns, alongside material parameters and manufacturing conditions, to predict orientations that enhance the mechanical strength of PBF-LB components. …”
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Driver drowsiness shield (DDSH): a real-time driver drowsiness detection system by Archita Bhanja, Dibyajyoti Parhi, Dipankar Gajendra, Kreetish Sinha, Arup Kumar Sahoo

“…For this purpose, we utilized an eye image dataset from the MRL Eye Dataset and performed extensive feature engineering and preprocessing to prepare the data for analysis. …”
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Multi-Class Skin Cancer Classification Using a Hybrid Dynamic Salp Swarm Algorithm and Weighted Extreme Learning Machines with Transfer Learning by Ramya Panneerselvam, Sathiyabhama Balasubramaniam

“…The proposed work is implemented as a hybrid model with a dynamic salp swarm algorithm (DSSA) with a weighted extreme learning machine (DSSA-WELM) that addresses the imbalances in the dataset and performs the classification with higher accuracy. …”
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Advancing malware imagery classification with explainable deep learning: A state-of-the-art approach using SHAP, LIME and Grad-CAM. by Sadia Nazim, Muhammad Mansoor Alam, Syed Safdar Rizvi, Jawahir Che Mustapha, Syed Shujaa Hussain, Mazliham Mohd Suud

“…It determines the best-performing model, an ensemble DNNW, for which explainability is provided. …”
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Integrating bulk RNA-seq and scRNA-seq analyses with machine learning to predict platinum response and prognosis in ovarian cancer by Tingting Gao, Peng Zhao, Suxia Han

“…To validate this hypothesis, we explored 7 different machine learning models for predicting platinum chemotherapy response at varying feature gene counts. …”
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Serum peptide biomarkers by MALDI-TOF MS coupled with machine learning for diagnosis and classification of hepato-pancreato-biliary cancers by Piya Prajumwongs, Attapol Titapun, Vasin Thanasukarn, Apiwat Jareanrat, Natcha Khuntikeo, Krit Rattanarak, Nisana Namwat, Poramate Klanrit, Arporn Wangwiwatsin, Jarin Chindaprasirt, Supinda Koonmee, Prakasit Sa-Ngiamwibool, Nattha Muangritdech, Sawanya Charoenlappanit, Janthima Jaresitthikunchai, Sittiruk Roytrakul, Watcharin Loilome

“…The resulting data were randomly split into training and testing sets. Feature selection on the training set identified 71 informative peptide mass fingerprints, which were then used to construct predictive models using SVM and RF algorithms. …”
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Reflection of Qajar Period Social Discourse in Mastooreh Kurdestani Poems With the Approach of Norman Fairclough by Mahin Panahi, Faezeh waezzadeh

“…The fact that he clearly reflected the general situation of Iranians in the Qajar period shows the type of his performance against the ruling discourses in this period, which is based on protest and criticism. …”
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Assessment of the objective conditions of scientific research activity in Russia by V. E. Statsenko

“…Within the framework of the study, a quantitative empirical study was organized and performed based on the use of economic and statistical tools: comparison, dynamic series method, index method, graphical modeling, etc. …”
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EMISSION PROCESSES OF QUANTUM WELL INTERACTION WITH DELTA-LAYER IN pHEMT-HETEROSTRUCTURES by Yana V. Ivanova, George E. Yakovlev, Vasily I. Zubkov

“…The main theoretical technique used in the research is numerical modeling of nanoheterostructure key electronic features by self-consistent solution of Schrödinger and Poisson equations. …”
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SENTIMENT ANALYSIS OF JAKLINGKO APP REVIEWS USING MACHINE LEARNING AND LSTM by Maghfiroh Maulani, Windu Gata

“…Therefore, besides providing insights into user perceptions, this study also proposes improvement strategies aimed at enhancing features and the overall user experience. Given the high proportion of negative sentiment, this research emphasizes the importance of improving the accuracy of sentiment analysis models to generate deeper and more precise insights. …”
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The predictive power of teaching self-efficacy and emotion regulation on work engagement for EFL teachers in higher education by Yan Wang, Lin He, Qing-Yi Wang

“…Correlational analyses were initially performed to examine the relationships among these variables. …”
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The effect of insulin resistance on amygdale glucose metabolism alterations in experimental Alzheimer’s disease by Ya. V. Gorina, Yu. K. Komleva, O. L. Lopatina, A. I. Chernykh, A. B. Salmina

“…The aim of the study was to study the effect of IRAP expression on cells of the neuronal and glial lineage, glucose transporter (GLUT4) expression in the brain amygdala on emotional memory in animals with experimental Alzheimer’s disease.Materials and methods. The study was performed with two experimental models of Alzheimer’s disease in mice. …”
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Preliminary study on the connotation of flexibility in dynamically reconfigurable networks by Dong-nian CHENG, Bin-qiang WANG, Bao-jin WANG, Jian-hui ZHANG

“…From the microscopic and quantitative viewpoints,the connotation of the structural flexibility of reconfigurable networks was explored.More accurately,a key feature,i.e.,the dynamic data channel varying with service demands,of reconfigurable networks was first exhibited and explained.Four dominant implications of the flexibility were then revealed as gradually mapping to demands,keeping global performance good,implicit isolation,and self-driven control.Finally,related quantitative models and methods for both determining the stable deviation of outcomes from demands and computing the volume of resource dynamically reconfigured were investigated by using the exponentially moving average,the n:m voting scheme,Markov decision processes (MDP) and reinforcement learning,respectively.…”
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Impact of DNA methylation on the recurrence risk of stage I non-small cell lung cancer with EGFR mutations by Yunyi Li, Zhihui Yang, Fang Wu, Qingchun Liang, James G. Herman, Malcolm V. Brock, Wenliang Liu, Fenglei Yu, Xue He, Chen Chen

“…We employed stepwise regression to select variables and logistic regression to establish the predictive model. Cross-validation and decision curve analysis were performed. …”
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Integration of agronomic information, vegetation indices (VIs), and meteorological data for phenological monitoring and yield estimation of rice (Oryza sativa L.) by Jorge A. Fernandez-Jibaja, Nilton Atalaya-Marin, Yeltsin A. Álvarez-Robledo, Victor H. Taboada-Mitma, Juancarlos Cruz-Luis, Daniel Tineo, Malluri Goñas, Darwin Gómez-Fernández

“…For yield estimation, feature selection was performed using principal component analysis (PCA) and the least absolute shrinkage and selection operator (LASSO) to increase model efficiency and interpretability. …”
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Physical Information Neural Network-Based Seepage Behavior Analysis of Earth and Rock Dams by XUE binghan, HUANG zhenhua, LEI Jianwei, FANG Hongyuan

“…Further validation is performed using a classic earth-rock dam case study under both homogeneous and heterogeneous conditions. …”
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Evaluation of the pharmacological potential of N-((5-phenyl-6,11-dihydro-[1,2,4]triazolo[1’,5’:1,6]pyrido[3,4-b]indol-2-yl)methyl)benzamides by S. O. Fedotov

“…Advanced molecular docking techniques were employed to identify potential binding sites with model enzymes and to characterize the energetic and spatial features of ligand-target interactions. …”
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The Use of Road Microsimulation Software within BIM Environments: A Preliminary Assessment by Marilisa Botte, Amedeo Zampi, Cristina Oreto, Luca D’Acierno

“…The use of Building Information Modelling (BIM) is becoming increasingly adopted worldwide to support the creation and management of digital environments in which physical and functional features of a facility are modelled. …”
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Usefulness of Radiomics and Kidney Volume Based on Non-Enhanced Computed Tomography in Chronic Kidney Disease: Initial Report by Piotr Białek, Adam Dobek, Krzysztof Falenta, Ilona Kurnatowska, Ludomir Stefańczyk

“…Kidney segmentations, volume measurements, and RDX features extraction were performed. Machine-learning models using RDX were constructed to classify the kidneys as having structural markers of impaired or normal function. …”
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SENTIMENT ANALYSIS OF MERDEKA BELAJAR KAMPUS MERDEKA POLICY USING SUPPORT VECTOR MACHINE WITH WORD2VEC by Nurul Rezki, Sri Astuti Thamrin, Siswanto Siswanto

“…Classification sentiment using support vector machine with Word2Vec feature extraction in this study produces a good model.…”
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