AI-Enabled IoT for Food Computing: Challenges, Opportunities, and Future Directions by Zohra Dakhia, Mariateresa Russo, Massimo Merenda

“…Unlike traditional food systems, which primarily focus on production and safety, food computing leverages AI for intelligent decision making and the IoT for real-time monitoring, enabling significant advancements in areas such as supply chain optimization, food safety, and personalized nutrition. …”
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Computational Linguistics Applications in AI-Based Investment and Cost Structuring Models by Miralieva Dilafruz, Ramatov Jumaniyoz, Azimova Lola, Khusamiddinova Malika, Alimbaeva Shahlo, Omonova Laylo

“…Artificial intelligence is an influential technological paradigm that is quickly and comprehensively transforming financial decision-making systems worldwide. This study aims to focus on computational and economic implications of computational linguistics techniques and to enrich the existing literature in AI-driven investment modeling. …”
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Fuzzy-Based Decision Support for Strategic Management: Evaluating Electric Vehicle Attractiveness in the Digital Era by Sónia Gouveia, Daniel H. de la Iglesia, José Luís Abrantes, Alfonso J. López Rivero, Eduardo Gouveia

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Experience in the application of computer modeling in the development of oil fields under conditions of uncertainty by Mukhametshin Vyacheslav Sh., Gilyazetdinov Ruslan, Khamzin Rinat

“…The work is devoted to solving one of the urgent problems of computer modeling of oil field development processes – reducing the influence of a high level of uncertainty and disequilibrium of geological and field parameters on the effectiveness of management decision-making. …”
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Topic Level Visualization of Student Enrollment Records in a Computer Science Curriculum by Eliot Bethke, Jennifer R. Amos

“…These activities often require multiple people with deep knowledge of the coursework as well as the discipline(s) involved to pour over scattered documentation and comparatively limited assessment data in order to make an informed decision. …”
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Quantitative structure property relationship and multiattribute decision analysis of antianginal drugs using topological indices by Muhammad Waheed Rasheed, Abid Mahboob, Ali Ovais, Nimra Shabbir, Abdu Alameri

“…Furthermore, by combining these descriptors with the multi-attribute decision-making additive ratio assessment technique, we achieve robust and reliable drug rankings. …”
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Knowledge Acquisition for the Stunting Prevention Expert System (SIPENTING) using Decision Tree and Grid Search by Azhar Basir, Fitri Ayuning Tyas

“…Stunting can be diagnosed even before birth by assessing the nutritional status of pregnant women. …”
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Using Situational Judgement Test to Assess The ‘Pancasila’ Student Profiles Construct: A Systematic Literature Review by Tri Wahyuni, Wardani Rahayu, Dali Santun Naga

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Fuzzy Computation Tree Temporal Logic with Quality Constraints and Its Model Checking by Xianfeng Yu, Yongming Li, Shengling Geng, Huirong Li

“…This treatise represents a significant contribution to the field by integrating quality constraint functions and predicates into Possibility Computation Tree Temporal Logic (PoCTL), thus giving rise to Fuzzy Computation Tree Temporal Logic with Quality Constraints (QFCTL). …”
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Secondary use of health records for prediction, detection, and treatment planning in the clinical decision support system: a systematic review by Dipendra Pant, Øystein Nytrø, Bennett L. Leventhal, Carolyn Clausen, Kaban Koochakpour, Line Stien, Odd Sverre Westbye, Roman Koposov, Thomas Brox Røst, Thomas Frodl, Norbert Skokauskas

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MCDM Approach to Assess Innovation and Entrepreneurship Education in Higher Vocational Colleges under IndetermSoft Set by Mingfang Liu, Chuang Li

“…We use the concept of multi-criteria decision-making (MCDM) to deal with different criteria. …”
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A model of malignant risk prediction for solitary pulmonary nodules on 18F‐FDG PET/CT: Building and estimating by MingMing Yu, ZhenGuang Wang, GuangJie Yang, Yuan Cheng

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Multi-physiological signal fusion for objective emotion recognition in educational human–computer interaction by Wanmeng Wu, Enling Zuo, Weiya Zhang, Xiangjie Meng

“…A convolutional neural network (CNN) with attention mechanisms was employed as the decision-making model.ResultsThe proposed system demonstrated superior accuracy in recognizing emotional states than existing methods. …”
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Rapid Computation of Seismic Loss Curves for Canadian Buildings Using Tail Approximation Method by Payam Momeni, Katsuichiro Goda, Navid Sirous, Sheri Molnar

“…Traditional seismic risk assessments often require specialized expertise and extensive computational time, making probabilistic seismic risk evaluations less accessible to practitioners and decision-makers. …”
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Simulating hierarchical data to assess the utility of ecological versus multilevel analyses in obtaining individual-level causal effects by Lydia Kakampakou, Jonathan Stokes, Andreas Hoehn, Marc de Kamps, Wiktoria Lawniczak, Kellyn F. Arnold, Elizabeth M. A. Hensor, Alison J. Heppenstall, Mark S. Gilthorpe

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Herding behavior, disposition effect, and investment decisions: A multi-mediation analysis of risk perception and dividend policy by Sarfaraz Ahmed Bhutto, Nazia Nazeer, Muhammad Saad, Kewal Talreja

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Fairness in Healthcare Services for Italian Older People: A Convolution-Based Evaluation to Support Policy Decision Makers by Davide Donato Russo, Frida Milella, Giuseppe Di Felice

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Classification of biomedical lung cancer images using optimized binary bat technique by constructing oblique decision trees by Shobha Aswal, Neelu Jyothi Ahuja, Ritika Mehra

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Forgetting phenomena in the Iowa Gambling Task: a new computational model among diverse participants by Tiancheng Yang, Chenghan Xie, Xuehe Wang

“…IntroductionThe Iowa Gambling Task (IGT) is a widely used paradigm for evaluating decision-making and executive functioning, yet existing computational models seldom account for the phenomenon of forgetting, which is critical to understanding dynamic decision processes.MethodsWe developed the Exploitation and Exploration with Forgetting (EEF) model, which integrates a dynamic forgetting parameter (λ) and participants' first-choice priors into a unified reinforcement-learning framework. …”
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Memory Constraints in Uncertainty Misestimation: A Computational Model of Working Memory and Environmental Change Detection by Li Xin Lim, Rei Akaishi, Sébastien Hélie

“…Reinforcement learning models often rely on uncertainty estimation to guide decision-making in dynamic environments. However, the role of memory limitations in representing statistical regularities in the environment is less understood. …”
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