DGD Gallery stores and shares digital research data online.
problem Storing and sharing of digital research data.
method Online web service for storage, sharing, and publication.
result Publicly available digital research data.
On-device research index
arXiv research
A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
169,341 papers · 148 categories
Trend · papers per month
48 results for “digital research data”
This paper reviews digital transformation research from 2011-2024, focusing on corporate finance.
problem Lack of systematic review in digital transformation from corporate finance perspective.
method Combines bibliometric and content analysis methods.
result Emerging and rapidly growing focus on digital transformation, particularly in developed countries.
Research aims to make AI decisions in digital pathology more understandable to pathologists.
problem Making AI decisions in digital pathology more understandable and interpretable.
method Combining machine learning with human intelligence to balance AI and human capabilities.
result Combining AI and human intelligence to improve diagnostic accuracy and understanding.
Digital financial services enhance firm performance through improved market share and profitability.
problem Insufficient academic attention to the impact of digital financial services on firm performance.
method Systematic review of literature, classification of methodologies, and identification of research gaps.
result Digital financial services significantly impact firm performance but have not received adequate academic attention.
GANs help create realistic synthetic health data, boosting medical research.
problem Challenges in creating realistic synthetic health data due to private patient data.
method Generative Adversarial Networks (GANs) to learn and produce synthetic health data.
result GANs can produce realistic synthetic health data, overcoming challenges in OHD.
New framework explains leading digit patterns without probabilistic assumptions.
problem Explaining leading digit distributions without relying on probabilistic models.
method Shift-invariant functional equation and affine-plus-periodic formulas.
result Unified mathematical foundation for understanding digit distributions.
Surrogate models enhance digital twin technology for dynamic systems.
problem Lack of clarity and effective methods for digital twin applications.
method Exploration of Gaussian process (GP) emulators within digital twin framework.
result Surrogate models like GP emulators are effective for digital twin development.
Automated digital twin discovery from biological data improves drug discovery and personalized medicine.
problem Developing reliable digital twins from noisy, incomplete biological data.
method Symbolic and sparse regression, Bayesian frameworks, deep learning, and large language models.
result Sparse regression generally outperforms symbolic regression, especially with Bayesian frameworks.
Introduces MLM dataset for multitask learning across multiple languages and modalities.
problem Training and evaluating multitask systems on diverse data.
method Develops a new benchmark dataset with semantic data and modalities.
result Demonstrates challenges in generalizing on diverse data.
Incorrect fixed point results in digital topology are corrected.
problem Incorrect fixed point results in digital topology.
method Analysis of recent papers in digital topology.
result Corrected incorrect conclusions in fixed point results.
Incorrect fixed point results in digital topology are debunked.
problem Incorrect fixed point results in digital topology.
method Mimicking classical topology tools.
result Many recent fixed point results are incorrect or trivial.
Study reveals jumps in crypto markets predict future prices.
problem Understanding jumps in high frequency digital asset markets.
method High frequency crypto data analysis, econometric modeling.
result Intra-day jumps significantly influence end of day returns.
The study uses Benford's law to test financial data reliability in developing countries.
problem Detecting and removing anomalies in financial reports.
method Benford's law first significant digit and distribution distances tests.
result Financial data distributions better follow Benford's law after anomalies are removed.
CrowdLLM uses LLMs and generative models to create diverse digital populations.
problem Lack of diversity and accuracy in digital populations created by LLMs.
method Integrates pretrained LLMs and generative models to enhance diversity and fidelity.
result CrowdLLM achieves promising performance in accuracy and distributional fidelity.
Digital personas improve survey results for stable attributes but fail for subjective responses.
problem When can digital personas reliably approximate human survey findings?
method Using LISS panel, constructed personas from background variables and survey histories, tested against held-out post-cutoff answers.
result Digital personas improve alignment with human response distributions for stable attributes but fail for subjective responses.
This study identifies financial risk paths in digital-transformed enterprises.
problem Identifying financial risks in digital-transformed enterprises.
method DEMATEL-ISM-MICMAC method.
result Political and economic environment affects enterprise's financial structure.
The abstract covers various aspects of eBusiness and eGovernment, including digital currencies, m-government services, gender inclusivity, eLearning, export performance, SME digitalization, and banking customer behavior.
problem Various challenges and opportunities in eBusiness and eGovernment.
method Critical review, UTAUT model with perceived risk theory, GAD approach, inductive research paradigm, one-on-one interviews, survey questionnaires, convenience sampling.
result Impediments to eLearning uptake, gender inclusivity in e-procurement, export performance of manufacturing firms, SME digitalization impact, measuring and modeling framework for Internet banking customers.
Cryptocurrencies use blockchain tech for secure transactions, offering new research opportunities.
problem Misunderstanding of cryptocurrency technology and lack of empirical data.
method Analyzing detailed transaction data and summarizing statistics.
result Opportunity for academic research in financial economics.
This paper uses LLMs to streamline industrial data-centric R&D cycles.
problem High costs in human, computational, and time resources in data-centric R&D.
method Explores how large language models can understand domain-specific requirements and automate R&D tasks.
result Promising results show potential for automating industrial data-centric R&D cycles.
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.
Research identifies four motivational groups for crypto-metaverse landowners.
problem Understanding motivations of retail investors in the crypto-metaverse.
method Detailed financial behavior survey and principal components analysis.
result Four distinct motivational groups identified: Aesthetics, Social, Speculation, Innovation.
CitySim: A Drone-Based Vehicle Trajectory Dataset for Safety Oriented Research and Digital Twinscs.CV
CitySim dataset captures vehicle trajectories for safety research.
problem Lack of fine-grain vehicle trajectories for safety-oriented research.
method Five-step procedure: video stabilization, object filtering, stitching, detection, and error filtering.
result CitySim dataset improves safety evaluations and facilitates digital-twin research.
Quantifying the Blockchain Trilemma: A Comparative Analysis of Algorand, Ethereum 2.0, and Beyondecon.GN
This study evaluates Algorand and Ethereum 2.0 for blockchain trilemma challenges.
problem Balancing decentralization, security, and scalability in blockchain systems.
method Comparative analysis of Algorand and Ethereum 2.0 using metrics for decentralization, scalability, and security.
result Each system has strengths in addressing the blockchain trilemma, providing insights for other blockchain technologies.
This study synthesizes stablecoin systems and develops a performance evaluation framework.
problem Fragmented academic research on stablecoins across economics, law, and computer science.
method Multi-method research design including literature synthesis, performance evaluation framework, and case study.
result Unified taxonomy and performance evaluation framework for stablecoin design.
AI improves precision health through adaptive interventions.
problem Improving healthcare through personalized and dynamic treatments.
method Reinforcement learning (RL) for adaptive interventions in digital health.
result RL shows promise in dynamic healthcare problems.
The study uses supervised learning to classify research data by discipline.
problem Automatically categorizing research data by discipline for scientometric analysis.
method Used a large dataset of 609,524 records for training and evaluation, employing tree-based models and neural networks.
result Multi-layer perceptron models outperformed Long Short-Term Memory models in multi-label classification tasks.
Machine learning automates digitization of historical data.
problem Manual transcription is costly and difficult for large, detailed datasets.
method Apply machine learning techniques for unsupervised layout classification and attention-based neural networks.
result Machine learning can automate the digitization process for historical data.
Study evaluates digital transformation impact on financial performance using LLMs.
problem Measuring and understanding the impact of digital transformation on financial performance.
method Constructed DT indicators from company reports; analyzed effects of different digital technologies.
result Digital transformation improves financial performance, but varies by technology.
DIGIT is a low-cost tactile sensor for in-hand manipulation.
problem Difficulty in sensing contact forces limits robotic manipulation.
method DIGIT miniaturizes and improves a vision-based tactile sensor.
result DIGIT enables better control of interactions with the environment.
Orchestrating the Twin Transition in GBS: A Socio-Technical Framework
problem MNCs' need to harmonize digital efficiency with environmental stewardship
method Technology Roadmapping (TRM) with ICT-centric innovation ecosystem toolkit
result Central 'operational airlock' for GBS in harmonizing digital and environmental transformation
Study shows 'Belt and Road' node cities boost digital finance in China.
problem Impact of 'Belt and Road' node cities on digital inclusive finance.
method Descriptive analysis, literature review, theoretical model, differential differential method.
result Establishment of 'Belt and Road' node cities promotes digital inclusive finance in China, with Internet development as a mediating variable.
This research assesses uncertainty quantification and sensitivity analysis for DTs in nuclear fuel performance.
problem Understanding the reliability and performance of advanced nuclear fuels using DTs.
method Introduces ML-based uncertainty quantification and sensitivity analysis methods applied to BISON fuel performance code.
result Demonstrates the effectiveness of DTs in multi-criteria decision-making for nuclear fuel performance.
Machine learning identifies types of alterations in historical manuscripts.
problem Understanding and categorizing alterations in historical manuscripts.
method Alteration Latent Dirichlet Allocation (alterLDA) model.
result High performance in recognizing alterations on labelled data, and interesting insights on unlabelled data.
Wikipedia and Digital Currencies: Interplay Between Collective Attention and Market Performancephysics.soc-ph
Study shows Wikipedia views correlate with digital currency market performance.
problem Lack of systematic investigation into online attention and crypto market dynamics.
method Quantified the interplay between Wikipedia attention and digital currency market performance using edit history and view history.
result A simple trading strategy informed by Wikipedia views outperformed classic strategies.
Deep Neural Operator Driven Real Time Inference for Nuclear Systems to Enable Digital Twin Solutionsstat.ML
DeepONet accelerates nuclear DT inference with high accuracy and efficiency.
problem Real-time prediction and model evaluation in nuclear systems.
method Deep Neural Operator (DeepONet) for surrogate modeling.
result DeepONet outperforms traditional ML methods in accuracy and speed.
Rotation-equivariant CNNs improve tumor detection in pathology.
problem Improving tumor detection in digital pathology images.
method Rotation-equivariant CNNs leveraging image symmetry.
result Significant improvement in tumor detection performance.
Bitcoin volatility can be predicted from price and alternative data.
problem Predicting Bitcoin volatility from market data.
method Modeling Bitcoin volatility using price, volatility momentum, and alternative data like sentiment and engagement.
result Bitcoin volatility can be predicted with a lag of several hours.
This paper reviews bank performance determinants, highlighting future research areas.
problem Understanding bank performance factors to improve sector efficiency and knowledge.
method Analysis of 54 studies in peer-reviewed journals.
result Bank performance factors remain largely unexplored, especially post-COVID-19.
Digital money could reduce germ spread during coronavirus.
problem Spreading of germs via paper money during coronavirus.
method Policy recommendations for mobile wallets, digital currencies, and data protection.
result Adopting digital money can help reduce germ spread.
This survey analyzes knowledge discovery in cryptocurrency transactions.
problem Understanding user behaviors and collective actions in cryptocurrency transactions.
method Data mining techniques and literature review.
result Classified existing research into three aspects and discussed major findings.
New handwritten digits dataset for Kannada script.
problem Lack of datasets for Kannada numeral digits.
method Developed Kannada-MNIST and Dig-MNIST datasets.
result Initial CNN accuracy is lower than MNIST, indicating a challenge in generalization.
Study uses web search data to analyze tech startups growth.
problem Analyzing growth dynamics of tech startups.
method Utilized Google Trends data for 241 US-based tech startups.
result Web search traffic correlates positively with tech startup growth.
Social media enhances or diminishes scientific status, depending on usage.
problem Impact of social media on scientific stratification and mobility.
method Logistic Attribution Analysis combining statistical and machine learning methods.
result Social media promotes stratification and mobility, but beyond a threshold, it negatively impacts status.
AWDO trains neural networks for digit classification.
problem Training feedforward neural networks.
method Adaptive Wind Driven Optimization (AWDO).
result AWDO outperforms steepest descent method in digit classification.
Deep RL optimizes sensor placement in digital twins for dynamic data acquisition.
problem Limited applicability of traditional sensor placement techniques for online applications.
method Formulates sensor placement as a Markov decision process and uses deep reinforcement learning.
result Improves predictive accuracy and reliability of digital twins through adaptive sensor repositioning.
This research predicts Bitcoin prices using wavelet and deep stacking approach.
problem Predicting price fluctuations of Bitcoin due to its price volatility.
method Wavelet for noise removal, deep learning models (neural networks and transformers), feature selection.
result The model achieved high accuracy in predicting Bitcoin prices at different time intervals.
New Ising models improve consensus clustering on specialized hardware.
problem Consensus clustering optimization problems.
method Formulated consensus clustering as Ising models and evaluated on specialized hardware.
result Our Ising models outperform existing techniques on consensus clustering.
Smart Contract-Enabled Procurement under Bounded Demand Variability: A Truncated Normal Approachq-fin.GN
Study develops smart contract framework for procurement under demand variability.
problem Operational and economic implications of smart contract adoption under moderate uncertainty.
method Multi-supplier model with endogenized adoption costs, supplier readiness, and inventory penalties; analytical and numerical results.
result Partial adoption strategies support moderate demand variability, while excessive digital investment reduces profitability.