Visualizes Bangladeshi laws for quicker searching.
problem Difficulty in finding relevant Bangladeshi laws.
method Doc2Vec for node layout, link mining for citation networks, named entity recognition for quick section finding.
result Users find the tool faster and more intuitive for legal research.
Database of Irish parliamentary speeches from 1919-2013.
problem Storing and analyzing historical parliamentary debates.
method Downloaded speeches from official website, processed, parsed, and matched with TD and minister data.
result 4.5 million speeches from 1,178 TDs in a single database.
Researchers in Flint use predictive tools to locate lead pipes.
problem Detecting and replacing lead pipes in Flint, Michigan after water contamination.
method Statistical and machine learning approaches, along with government recommendations.
result Developed a statistical model that adapts to new information.
Machine learning used in German official statistics.
problem Identifying areas and tasks where machine learning is applied in official statistics.
method Surveys conducted at statistical institutions and divisions of Destatis.
result Machine learning methods are used in various statistical areas and tasks.
Machine learning improves official statistics but needs rigorous validation.
problem Lack of methodological robustness in machine learning for official statistics.
method Total Machine Learning Error (TMLE) framework to validate ML models.
result TMLE addresses representativeness and measurement errors in ML models.
This paper examines risks and uncertainties of changing data sources in machine learning for official statistics.
problem Risks and uncertainties associated with changing data sources in machine learning for official statistics.
method An overview of risks, causes, and repercussions of changing data sources, with a checklist of measures.
result Maintaining integrity, reliability, consistency, and relevance in official statistics.
RSI uses Bayesian inference to monitor compliance in rule-governed domains.
problem Structural obstacles in compliance monitoring, including unlabeled outcomes and selective withholding of evidence.
method Rule-State Inference (RSI) treats formalized rules as Bayesian priors and infers compliance states through mean-field variational inference.
result RSI delivers formal guarantees of adaptability, consistency, and convergence, validated on a synthetic enterprise benchmark.
It is demonstrated that the US economy has on the long-term in reality been governed by the Keynesian approach to economics independent of the current official economical policy. This is done by calculating the two-point correlation function between the fluctuations of the DJIA and the US public debt. We find that the …
A quantum framework optimizes collateral allocation for derivatives.
problem Legal constraints and operational rules in collateral allocation for derivatives.
method Certified higher-order quantum framework that normalizes margin requirements and builds a bounded neighborhood of actions.
result Quantum framework improves certified sample quality compared to classical methods.
Research designs first model for Amharic handwritten character recognition.
problem No existing model for Amharic handwritten character recognition.
method Used a convolutional neural network and applied data augmentation and multi-task learning.
result Promising results observed from the enhanced model.
In this paper we present an analysis of power law statistics on land markets. There have been no other studies that have analyzed power law statistics on land markets up to now. We analyzed a database of the assessed value of land, which is officially monitored and made available to the public by the Ministry of Land, …
condLSTM-Q predicts COVID-19 deaths at county level with quantile forecasts.
problem Predicting COVID-19 mortality at fine geographical scales.
method Conditional Long Short-Term Memory networks with quantile output.
result Fine-scale quantile predictions inform about death toll distribution.
This is the less official, English version of the proof of the fact that every closed atoroidal 3-manifold carries finitely many isotopy classes of tight contact structures.
The paper improves ESG taxonomy and classifies sentences as sustainable or unsustainable.
problem Improving ESG taxonomy and classifying sentences based on ESG factors.
method For ESG taxonomy, used Sentence-BERT models. For sentence classification, combined RoBERTa with a multi-layer perceptron.
result Significant performance improvement and high accuracy in classifying sentences.
The study maps ML quality dimensions to fairness, enhancing the QF4SA framework.
problem Ensuring fairness in ML applications at NSOs to avoid social impacts.
method Employing the QF4SA framework, the study maps quality dimensions to fairness and investigates their interactions.
result Fairness is identified as a new quality dimension in the QF4SA framework.
FST.ai 2.0 improves Taekwondo decision-making with AI, reducing review time and increasing trust.
problem Fair, transparent, and explainable decision-making in Taekwondo.
method Pose-based action recognition, epistemic uncertainty modeling, interactive dashboards.
result 85% reduction in decision review time, 93% referee trust in AI-assisted decisions.
A framework assesses the quality of crowdsourced weather data.
problem Quality control and assessment of crowdsourced weather data from third-party stations.
method Proposes a simple, scalable, and interpretable AI/Stats/ML framework to assess TPAWS data.
result Demonstrates the performance of the framework using synthetic and real data.
Task focuses on fact checking in Q&A forums, improving over baseline systems.
problem Fact checking in community Q&A forums to distinguish factual from opinion.
method Two subtasks: distinguishing factual vs. opinion/advice/socializing, predicting answer truthfulness.
result Improved over baseline systems for both subtasks, but not for Subtask B.
This reviews the econophysics activities in Belgium from my admittedly biased point of view. Unknown historical notes or facts are presented for the first time explaining the aims, whence evolution of the research papers and friendly connections with colleagues. Comments on endeavors are also provided. The lack of offi…
Accurate real-time monitoring systems of influenza outbreaks help public health officials make informed decisions that may help save lives. We show that information extracted from cloud-based electronic health records databases, in combination with machine learning techniques and historical epidemiological information,…
Let G be a compact Lie-group, X a compact G-CW-complex. We define equivariant geometric K-homology groups K^G_*(X), using an obvious equivariant version of the (M,E,f)-picture of Baum-Douglas for K-homology. We define explicit natural transformations to and from equivariant K-homology defined via KK-theory (the "offici…
SVHN dataset's split affects generative models but not digit classification.
problem Distribution mismatch between SVHN training and test sets impacts generative models.
method Empirically showed distribution mismatch affects generative models; proposed mixing and re-splitting.
result Distribution mismatch in SVHN dataset significantly impacts probabilistic generative models.
Machine learning improves risk assessment for gender-based violence victims.
problem Accurately predicting recidivism risk in gender-based crime victims.
method Applied machine learning techniques to create models predicting recidivism risk.
result Proposed ML method outperforms classical statistical methods.
In retrospective assessments, internet news reports have been shown to capture early reports of unknown infectious disease transmission prior to official laboratory confirmation. In general, media interest and reporting peaks and wanes during the course of an outbreak. In this study, we quantify the extent to which med…
Study uses Instagram data to predict flu-like illnesses.
problem Influenza surveillance challenges due to resource limitations.
method Machine learning models trained on Instagram data, including visual content.
result Best nowcasting model had an MAE of 11.33 and correlation of 0.963.
MakerDAO's governance is centralized despite its decentralized claim.
problem Decentralization illusion in Decentralized Finance (DeFi) governance.
method Empirical analysis using financial, transaction, network, and sentiment indicators.
result Centralized governance impacts Maker protocol and voting power distribution.
The article proposes modified Gower's coefficients for handling mixed type variables in nearest neighbor methods.
problem Handling mixed type variables in nearest neighbor methods, especially imputation and statistical matching.
method Suggests modifications to the Gower's distance for interval and ratio scaled variables to address unbalanced contributions and outlier sensitivity.
result Improved distance calculations reduce the unbalanced contribution of different variable types and attenuate outlier effects.
This study measures decentralization in blockchain finance governance.
problem Defining and measuring decentralization in blockchain finance applications.
method Aggregating and analyzing empirical data of four finance applications to calculate coefficients for governance token distribution.
result Gauges for objective evaluation of token governance capabilities and limitations.
Study on excess mortality in Germany during 2020-21.
problem Analyzing excess mortality during the pandemic in Germany.
method Empirical study using official death counts.
result Provided conclusions for insurance businesses.
We model bond's price curves corresponding to the sovereign uruguayan debt nominated in USD, as an alternative to the official bond prices publication released by the Central Bank of Uruguay (CBU). Four different gaussian models are fitted, based on historical data issued by the CBU, corresponding to some of the more f…
The study examines how board diversity and CSR committee composition affect corporate governance and financial performance.
problem The relationship between corporate social responsibility (CSR) and corporate governance.
method Theoretical model development based on management and corporate governance theories, focusing on board diversity and CSR committee composition.
result Cognitive and demographic characteristics of board members provide more insights into the link between corporate governance and CSR.
Adaptive AI delegation framework for dynamic decision authority allocation.
problem Dynamic allocation of decision authority to AI-generated recommendations under evolving evidence quality and uncertainty.
method Formulated as a Governance-Aware POMDP, using Bayesian inference for informational state estimation and sequential optimization for authority allocation.
result Sequential Bayesian governance provides the strongest general-purpose policy across AI-quality regimes, adapting to evolving evidence.
AI generates a sequence of death causes from hospital records.
problem Accurate death reporting for vital statistics and policy formulation.
method Neural machine translation models to generate causal chains, incorporating medical domain knowledge.
result Achieved 16.04 BLEU score for generating accurate causal chains.
This paper analyzes voter coalitions in MakerDAO's decentralized governance.
problem Understanding the governance structure and influence of voter coalitions in DAOs.
method Applied clustering algorithm to voting history of MakerDAO to identify voter coalitions.
result The emergence of a dominant voter coalition signals governance centralization in DAOs.
Study shows corporate governance improves stock liquidity with noise traders' participation.
problem Improving liquidity of listed companies' stocks.
method Theoretical model with heterogeneity of investors' beliefs.
result Corporate governance and noise traders' participation synergistically improve stock liquidity.
Study shows death ratio of COVID-19 deaths increases financial volatility.
problem Impact of COVID-19 deaths on financial markets.
method Analysis of VIX index based on daily case reports and death ratios.
result Death ratio positively influences financial volatility.
AI governance lagging in finance despite widespread use.
problem Lack of operational governance frameworks for AI in finance.
method Proposes a four-layer framework with computable instantiations.
result Demonstrates the effectiveness of the proposed framework through a case study.
This paper models yearly exchange rates between USD/KZT, EUR/KZT and SGD/KZT, and compares the actual data with developed forecasts using time series analysis over the period from 2006 to 2014. The official yearly data of National Bank of the Republic of Kazakhstan is used for present study. The main goal of this paper…
This research deals with the mathematical modeling of the physical capital diffusion through the borders of the countries. The physical capital is considered an important variable for the economic growth of a country. Here we use an extension of the economic Solow model to describe how the smuggling affects the economi…
Study examines UK firms' financial performance linked to corporate governance.
problem Impact of corporate governance on UK firms' financial performance.
method Cross-sectional regression analysis of 252 firms in 2014.
result Corporate governance mechanisms have mixed effects on financial performance.
This paper tackles AI model governance challenges in financial services.
problem Challenges in current AI model governance practices in financial services.
method Proposes a system-level framework for increased self-regulation.
result Enhanced model governance and risk management capabilities.
Study finds implicit government guarantee improves municipal investment bond ratings.
problem Questioning the objectivity of municipal investment bond ratings due to implicit government guarantee.
method Text mining of policy documents and PMC index model for implicit guarantee strength calculation.
result Implicit government guarantee boosts municipal investment bond ratings, especially in less developed regions.
BusTr predicts bus travel times from real-time traffic forecasts.
problem Improving accuracy of bus travel time predictions.
method Neural sequence model trained on real-time traffic forecasts.
result BusTr outperforms DeepTTE by 30% in Mean Absolute Percentage Error (MAPE).
Study examines how governance, corruption, and R&D affect economic development.
problem The impact of corruption and governance on economic development.
method General equilibrium model with heterogeneous agents and a government, including corruption as a fraction of tax revenues.
result Redistribution and innovation-led strategies can mitigate the negative effects of corruption on economic development.
Optimization models predict cryptocurrency market equilibria under government seizure risk.
problem Determining cryptocurrency market equilibria under government seizure risk.
method Game-theoretic optimization models with utility functions.
result Existence and uniqueness of Nash equilibrium in cryptocurrency markets.
Study analyzes Brazilian congress members' spending patterns.
problem Lack of transparency in government spending by congress members.
method Neural network-based approach for analyzing and visualizing spending patterns.
result Inspires new machine learning methodologies for government transparency.
This paper measures the intensity of implicit government guarantees using PMC index model.
problem Excessive local government debt due to implicit government guarantees.
method Text mining of policy documents related to municipal investment bonds, PMC index model.
result Recent policies have reduced the intensity of implicit government guarantees.
BARMPy offers a Python package for Bayesian Additive Regression Models.
problem Making complex Bayesian models accessible to machine learning practitioners.
method Object-oriented design compatible with SciKit-Learn, documentation and tutorial provided.
result Ease of use and compatibility with existing machine learning tools.