In-Memory Versus Disk-Based Computing with Random Forest for Stock Analysis: A Comparative Study by Chitra Joshi, Chitrakant Banchorr, Omkaresh Kulkarni, Kirti Wanjale

“…As data become increasingly large, diverse and fast-moving, conventional processing systems often fall short of the performance required for modern analytics.Objective: This research seeks to thoroughly assess the performance of two prominent big data processing frameworks-Apache Spark (in-memory computing) and MapReduce (disk-based computing)-with a focus on applying random forest algorithms to predict stock prices. …”
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Combined myocardial perfusion scintigraphy and computed tomography: diagnostic and prognostic value in coronary artery disease by M. O. Gulya, A. V. Mochula, A. N. Maltseva, K. V. Zavadovsky

“…A separate section is devoted to the importance of hybrid imaging in making decisions about myocardial revascularization.…”
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A new risk assessment model of venous thromboembolism by considering fuzzy population by Xin Wang, Yu-Qing Yang, Xin-Yu Hong, Si-Hua Liu, Jian-Chu Li, Ting Chen, Ju-Hong Shi

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Clinical Applications of Fractional Flow Reserve Derived from Computed Tomography in Coronary Artery Disease by Cappi Chan, MSc, Min Wang, PhD, Luoyi Kong, MSc, Leanne Li, MSc, Lawrence Wing Chi Chan, PhD

“…Computer tomography–derived fractional flow reserve (CT-FFR) represents a significant advancement in noninvasive cardiac functional assessment. …”
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Machine learning based shear strength prediction in reinforced concrete beams using Levy flight enhanced decision trees by Aybike Özyüksel Çiftçioğlu, Anıl Delikanlı, Torkan Shafighfard, Faramarz Bagherzadeh

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Diagnostics and prediction of intracranial hypertension on primary computed tomography in patients with severe traumatic brain injury by A. V. Oshorov, K. R. Muradyan, A. M. Turkin, D. M. Chelushkin, Ya. A. Latyshev, E. V. Aleхandrova, Yu. V. Strunina, G. V. Danilov, I. A. Savin, A. D. Kravchuk

“…The mean ONSD-CT can be used to diagnose ICH along with such signs of ICP as level of mesencephalic cisterna compression and midline  shift and to make a decision on invasive ICP monitoring. The maximum value of ONSD-CT can be used to assess the probability of ICH in the  first three days after TBI…”
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Implementation of a Digital Model of Thermal Characteristics Based on the Temperature Field by V. V. Pozevalkin, A. N. Polyakov

“…Introduction. Computer modeling allows engineers to make valid design decisions by accurately assessing the thermal characteristics of design objects. …”
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An Interface Design Method Based on Situation Awareness and Immersive Analytics for Augmented and Mixed Reality Decision Support Systems in Construction by Ernesto Pillajo, Claudio Mourgues, Andrés Neyem, Vicente A. González

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Human-Computer Interaction Empowers Construction Safety Management: Breaking Through Difficulties to Achieving Innovative Leap by Hao Peng, Xiaolin Wang, Han Wu, Bo Huang

“…The research results indicate that human–computer interaction technology has achieved remarkable development in four aspects: intelligent monitoring systems, risk assessment and management, ergonomics and cognitive psychology, as well as computer simulation and virtual reality. …”
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Cognitive Bias in Ambiguity Judgements: Using Computational Models to Dissect the Effects of Mild Mood Manipulation in Humans. by Kiyohito Iigaya, Aurelie Jolivald, Wittawat Jitkrittum, Iain D Gilchrist, Peter Dayan, Elizabeth Paul, Michael Mendl

“…Here, we report a novel variant of the task aimed at dissecting the effects of affect manipulations on perceptual and value computations for decision-making under ambiguity in humans. …”
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Digital transformation project risks assessment using hybrid picture fuzzy distance measure-based additive ratio assessment method by Pratibha Rani, Arunodaya Raj Mishra, Adel Fahad Alrasheedi, Dragan Pamucar, Dragan Marinkovic

“…DT is the integration of digital technologies into all disciplines of business from regular activities to strategic decision making. Risk management planning requires projects to assess possible risks that may negatively or positively affect a DT project. …”
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Intersection collision prediction and prevention based on vehicle-to-vehicle (V2V) and cloud computing communication by Min Zeng, Mohd Sani Mohamad Hashim, Mohd Nasir Ayob, Abdul Halim Ismail, Qiling Zang

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Machine learning-based feature selection for ultra-high-dimensional survival data: a computational approach by Nahid Salma, Majid Khan Majahar Ali, Raja Aqib Shamim

“… Ultra-high-dimensional (UHD) survival data presents significant computational challenges in biomedical research, particularly in Renal Cell Carcinoma (RCC), where genomic complexity complicates risk assessment. …”
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Assessing the effectiveness of interdependent corporate sustainability choices by Simone Cenci, Matteo Burato, Marek Rei, Maurizio Zollo

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Soft Computing Solutions for Reducing the Carbon Footprint of Fly Ash Based Concrete. Advances in Civil Engineering by Awoyera, Paul O., Adetola, Joshua, Nayeemuddin, Mohammed, Mewada, Hiren, George Fadugba, Olaolu

“…The construction industry significantly contributes to environmental degradation,with many structures exhibiting high carbon footprints throughout their construction processes and lifespans.Activities such as cement hydration and other commoncon-struction practices substantially influence environmental conditions overtime,necessitating a critical evaluation of material and design choices.This study reported the environmental impact of fly ash(FA),which is largely used to enhance concrete strength.A prediction of two end point indicators,that is,global warming potential(GWP)and CO2 emission using soft computing methods are presented,which are particularly effective for handling complex,non linear relationships in environmental data.To achieve this, two machine learning approaches,the random forest(RF)and decision tree(DT)models,are employed to assess the environ- mental impact of structural materials and designs.Two data sets were obtained from reputable databases,including ResearchGate, Science Direct, Semantic Scholar,and Mendeley Data.The models are trained to explore the potential for optimizing structural designs and material selection stominimize environmental impacts.Feature importance is analyzed using Shapley values,providing insights into the most influential factors affecting GWP and CO2 emission Model performance is evaluated using R2 and root mean square error(RMSE) metrics. …”
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Prevention and management of degenerative lumbar spine disorders through artificial intelligence-based decision support systems: a systematic review by Paolo Giaccone, Federico D’Antoni, Fabrizio Russo, Luca Ambrosio, Giuseppe Francesco Papalia, Onorato d’Angelis, Gianluca Vadalà, Albert Comelli, Luca Vollero, Mario Merone, Rocco Papalia, Vincenzo Denaro

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Comparative Effects of Direct and Metalinguistic Computer-Mediated Feedback on L2 Learners’ Writing Ability and Willingness-to-Write by Mahmood Hashemian, Maryam Farhang-Ju

“…The findings of this study may contribute to understating L2 learners’ needs and considering pedagogical decision-making for course developers and instructors.…”
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Evaluating the Effect of Surrogate Data Generation on Healthcare Data Assessment by Saeid Sanei, Tracey K. M. Lee, Issam Boukhennoufa, Delaram Jarchi, Xiaojun Zhai, Klaus McDonald-Maier

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Computed tomography-derived quantitative imaging biomarkers enable the prediction of disease manifestations and survival in patients with systemic sclerosis by Gabriela Riemekasten, Felix Nensa, Hanna Grasshoff, René Hosch, Malte Maria Sieren, Lennart Berkel, Jörg Barkhausen, Roman Kloeckner, Franz Wegner

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PRO-BiGRU: Performance Evaluation Index System for Hardware and Software Resource Sharing Based on Cloud Computing by Nan Wang

“…The proposed model not only improves the accuracy of performance evaluation but also provides a reliable basis for resource optimization and decision-making in cloud service platforms. The novelty of this research lies in the combination of the PRO algorithm with the BiGRU network, which effectively captures complex data features and enhances the model's reliability and robustness in performance assessment tasks. …”
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