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427 papers

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Multi-Perspective Ensemble Stratification-Driven Quality of Life Assessment for Transformative Planning of Coastal Communities

This study proposes a multi-perspective ensemble stratification framework that integrates heterogeneous data and diverse clustering models to comprehensively characterize household vulnerability and identify key drivers of quality of life in coastal Nigerian communities, thereby enabling more effective, evidence-based transformative planning and resource allocation aligned with sustainable development goals.

Taiwo Olapeju Olaleye, Taiwo Ajayi, Oluwasegun Dada, Temitope Aderele, Segun Akintunde, Oluwasefunmi Arogundade2026-08-14
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Distribution Analysis of Discrete States: reconstructing transition processes from time-resolved state distributions

This paper introduces Distribution Analysis of Discrete States (DADS), a general framework that reconstructs underlying transition processes from observed state distributions by modeling them as flow networks, establishing a rigorous typology of non-identifiability, and validating the approach through seven diverse case studies and self-correcting diagnostic tests.

Thomas Potempa2026-08-14
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Q-Multi-Criteria Consensus Model: Synthesizing cognitive priority structures from multi-actor disagreement

This paper introduces the Q-Multi-Criteria Consensus Model (Q-MCCM), a hybrid framework that synthesizes subjective disagreements into shared priority structures by combining Q-methodology with an algorithmic Best–Worst Method, thereby enabling robust institutional decision-making in contexts where priorities must be negotiated rather than alternatives selected.

Marek Deja2026-08-14
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The Role of Statistics in the Advancement of Artificial Intelligence and Modern Technology

This study utilizes machine learning time series modeling and correlation analysis of publication data from 1991 to 2023 to demonstrate that statistics serves as a central, tightly coupled driver of Artificial Intelligence and modern technology advancement, with both fields exhibiting strong positive growth trends and a statistically significant interdependence projected to continue through 2030.

H. C. Iwu, D. C. Bartholomew, C. J. Ijemba2026-08-14
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Investigating Students' Critical Thinking Development in Data-Driven Statistical Decision Making through Mindtools-Based Learning Game Interactions

This quasi-experimental study demonstrates that a spreadsheet-based learning game designed as a Mindtool significantly enhances undergraduate students' critical thinking skills and evolves their decision-making processes from reliance on single indicators to reflective evidence evaluation in data-driven statistical contexts.

BUDI SASOMO, Cholis Sa’dijah, Lathiful Anwar, Rustanto Rahardi, Sisworo Sisworo, Tomi Listiawan, Siti Faizah, Abdul Qoha (…)2026-08-13
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Data-Driven Spatial Weight Matrices for Space-Time Autoregressive Models: A Similarity-Based Framework with an Application to Global Temperature Dynamics

This paper proposes a data-driven framework for constructing spatial weight matrices based on statistical similarity rather than geographical proximity to enhance Space-Time Autoregressive models, demonstrating through global temperature analysis that similarity-based specifications, particularly those using Hamming distance, significantly improve forecasting accuracy compared to conventional contiguity-based approaches.

Edoardo Otranto2026-08-13
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Assessing Feature Selection Strategies in INLA: TraditionalStepwise Regression versus Machine Learning

This study demonstrates that integrating machine learning-based feature selection (specifically BART and SVR) with Bayesian hierarchical spatial models (INLA-SPDE) significantly outperforms traditional stepwise regression in reducing prediction error and bias, thereby yielding more accurate small-area estimates with well-calibrated uncertainty.

Xiangyue Huo, Chibuzor Christopher Nnanatu2026-08-13
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Robustness of sustainable aviation fuel supplier rankings under alternative fuzzy representations and MCDM methods

This study validates the robustness of SAF1 as the top-ranked sustainable aviation fuel supplier across various fuzzy representations and MCDM methods, while highlighting that although the leading candidate remains consistent, the complete supplier ordering varies and should be treated as a priority for further due diligence rather than an automatic selection.

Büşra ALTINKAYNAK2026-08-13
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Agreement Between Fitzpatrick-17k Skin-Type Labels Is Metric- and Stratum-Dependent: A Chance-Corrected Reanalysis

This paper reanalyzes the Fitzpatrick-17k dataset using chance-corrected statistics to demonstrate that label agreement between annotation sources is highly dependent on the chosen metric and skin-type stratum, revealing significant discrepancies—particularly for darker skin tones—that necessitate transparent reporting of methodology and per-stratum confidence intervals in dermatology AI research.

Niya Pennie2026-08-13