Uncertainty Quantification of State Variables Trajectories in the Context of Inverse Problems: An Approach from Bayesian Inference and FDA
本文针对逆问题中状态变量的不确定性量化问题，提出了一种结合贝叶斯推断和功能数据分析的方法，通过模拟研究验证了该方法的有效性。
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Representative Papers
DialSort: Non-Comparative Integer Sorting via the Self-Indexing Principle: Architecture, Implementation, and Substrate-Aware Analysis
This work proposes DialSort, a novel integer sorting architecture that fundamentally rethinks the role of histograms by treating them directly as the final sorted output rather than an intermediate structure. Leveraging a self-indexing principle, DialSort maps keys to their ordered positions in memory, thereby entirely eliminating the prefix-sum phase common in traditional approaches. It introduces a Conflict Resolution Network (CRN) that requires only equality checks, enabling comparison-free parallel writes. Combined with a pipelined addition-reduction tree and a bounded integer-domain memory access model, DialSort achieves a 39.77× speedup over std::sort on an 8-thread x86-64 platform, attaining a peak throughput of 115.9 million keys per second. It consistently outperforms counting sort, IPS4o, and ska_sort while passing all 208 correctness tests.
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The Real Interest Rate as a Control Variable in the Open Economy
This study investigates the structure, dynamic mechanisms, and role as a policy instrument of the real interest rate in an open-market economy. Departing from conventional paradigms, it explicitly models the real interest rate as a control variable within a dynamic general equilibrium framework for open economies and endogenizes its relationship with expected future multi-factor productivity and the utility discount rate. Building on an extension of the Cass–Koopmans–Ramsey model, the analysis reveals that an increase in productivity expectations simultaneously raises both the real interest rate and wage levels. This finding not only uncovers a co-movement mechanism between interest rates and wages but also confirms the model’s consistency with classical growth theory, thereby highlighting its theoretical novelty and explanatory power.
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Measuring What Cannot Be Surveyed: LLMs as Instruments for Latent Cognitive Variables in Labor Economics
Traditional survey instruments struggle to accurately capture the latent cognitive content embedded in occupational tasks, limiting the measurement of key variables such as exposure to artificial intelligence (AI). This study proposes leveraging large language models (LLMs) as a tool for latent variable measurement, using Claude Haiku 4.5 to generate cognitive dimension scores from 18,796 task descriptions in O*NET and constructing an augmented human capital index (AHC_o) to quantify occupation-level AI exposure. The research provides the first systematic validation of LLMs’ capacity to reliably measure latent constructs in labor economics, distinguishing between AI’s augmentation and substitution effects. Results show that AHC_o exhibits high correlation with existing AI exposure metrics (r ≤ 0.85), strong cross-model scoring reliability (Pearson r = 0.76), and a 25% reduction in measurement error using ORIV estimation relative to OLS, demonstrating significantly improved measurement precision.
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From Automation to Augmentation: A Framework for Designing Human-Centric Work Environments in Society 5.0
This study addresses the absence of an actionable and measurable human-centric framework for integrating AI technologies in enterprises, which hinders the evaluation and optimization of human–AI collaboration. It endogenizes human–AI augmentation as a joint function φ(D, W) of technology deployment (D) and five-dimensional workplace design (W), and for the first time demonstrates that human-centric design maximizes profitability once cognitive capital exceeds a critical threshold. Drawing on a PRISMA-guided systematic review, multiple regression analyses, and theory-driven scale development, and leveraging a large-scale manufacturing dataset from Colombia’s EDIT initiative, the research empirically shows that high-quality management practices significantly amplify returns on technology investment (interaction coefficient = 0.304, p < 0.01). It identifies decision authority allocation as a key constraint and task orchestration as the weakest dimension, culminating in the WADI diagnostic tool—a 36-item instrument—and a human-centric workplace design framework aligned with Society 5.0.
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Uncertainty Quantification of State Variables Trajectories in the Context of Inverse Problems: An Approach from Bayesian Inference and FDA
本文针对逆问题中状态变量的不确定性量化问题，提出了一种结合贝叶斯推断和功能数据分析的方法，通过模拟研究验证了该方法的有效性。
0 citationsRead paper
DialSort: Non-Comparative Integer Sorting via the Self-Indexing Principle: Architecture, Implementation, and Substrate-Aware Analysis
This work proposes DialSort, a novel integer sorting architecture that fundamentally rethinks the role of histograms by treating them directly as the final sorted output rather than an intermediate structure. Leveraging a self-indexing principle, DialSort maps keys to their ordered positions in memory, thereby entirely eliminating the prefix-sum phase common in traditional approaches. It introduces a Conflict Resolution Network (CRN) that requires only equality checks, enabling comparison-free parallel writes. Combined with a pipelined addition-reduction tree and a bounded integer-domain memory access model, DialSort achieves a 39.77× speedup over std::sort on an 8-thread x86-64 platform, attaining a peak throughput of 115.9 million keys per second. It consistently outperforms counting sort, IPS4o, and ska_sort while passing all 208 correctness tests.
0 citationsRead paper
The Real Interest Rate as a Control Variable in the Open Economy
This study investigates the structure, dynamic mechanisms, and role as a policy instrument of the real interest rate in an open-market economy. Departing from conventional paradigms, it explicitly models the real interest rate as a control variable within a dynamic general equilibrium framework for open economies and endogenizes its relationship with expected future multi-factor productivity and the utility discount rate. Building on an extension of the Cass–Koopmans–Ramsey model, the analysis reveals that an increase in productivity expectations simultaneously raises both the real interest rate and wage levels. This finding not only uncovers a co-movement mechanism between interest rates and wages but also confirms the model’s consistency with classical growth theory, thereby highlighting its theoretical novelty and explanatory power.
0 citationsRead paper
Measuring What Cannot Be Surveyed: LLMs as Instruments for Latent Cognitive Variables in Labor Economics
Traditional survey instruments struggle to accurately capture the latent cognitive content embedded in occupational tasks, limiting the measurement of key variables such as exposure to artificial intelligence (AI). This study proposes leveraging large language models (LLMs) as a tool for latent variable measurement, using Claude Haiku 4.5 to generate cognitive dimension scores from 18,796 task descriptions in O*NET and constructing an augmented human capital index (AHC_o) to quantify occupation-level AI exposure. The research provides the first systematic validation of LLMs’ capacity to reliably measure latent constructs in labor economics, distinguishing between AI’s augmentation and substitution effects. Results show that AHC_o exhibits high correlation with existing AI exposure metrics (r ≤ 0.85), strong cross-model scoring reliability (Pearson r = 0.76), and a 25% reduction in measurement error using ORIV estimation relative to OLS, demonstrating significantly improved measurement precision.
0 citationsRead paper
From Automation to Augmentation: A Framework for Designing Human-Centric Work Environments in Society 5.0
This study addresses the absence of an actionable and measurable human-centric framework for integrating AI technologies in enterprises, which hinders the evaluation and optimization of human–AI collaboration. It endogenizes human–AI augmentation as a joint function φ(D, W) of technology deployment (D) and five-dimensional workplace design (W), and for the first time demonstrates that human-centric design maximizes profitability once cognitive capital exceeds a critical threshold. Drawing on a PRISMA-guided systematic review, multiple regression analyses, and theory-driven scale development, and leveraging a large-scale manufacturing dataset from Colombia’s EDIT initiative, the research empirically shows that high-quality management practices significantly amplify returns on technology investment (interaction coefficient = 0.304, p < 0.01). It identifies decision authority allocation as a key constraint and task orchestration as the weakest dimension, culminating in the WADI diagnostic tool—a 36-item instrument—and a human-centric workplace design framework aligned with Society 5.0.
0 citationsRead paper