Modeling shows stronger IP protection speeds tech advancement.
problem Effect of intellectual property policy on tech advancement speed.
method Agent-based modeling with varying IP protection levels.
result Stronger IP protection leads to faster technological progress.
Space exploration technology advances exponentially, consistent with Moore's and Wright's laws.
problem Predicting the advancement of space exploration technology.
method Analysis of Moore's and Wright's laws applied to space exploration technology.
result Spacecraft technology advances exponentially, consistent with Moore's and Wright's laws.
Quantum crypto-economics models price risks in blockchain technology.
problem Quantum technology's potential to undermine blockchain security.
method Building financial models to price quantum risk in blockchain scenarios.
result Quantum crypto-economics models can assess and price quantum risks in blockchain.
SafeRNet uses IoT and cloud computing to provide real-time safe routes.
problem High traffic fatality rates despite advanced technology.
method Bayesian network for safe route modeling.
result Demonstrated effectiveness with real traffic data.
Surprise predicts breakthroughs in science and technology.
problem Predicting breakthroughs in science and technology.
method Using embeddings from high-dimensional stochastic block models, predicting combinations with AUC of 95%.
result Breakthroughs often occur when problems from one field are solved by researchers from another field.
The paper proposes an AI and IIoT framework for improved maintenance.
problem Current maintenance practices need improvement with AI and IIoT.
method Review of reliability modeling, introduction of Intelligent Maintenance framework, and novel probabilistic deep learning approach.
result Demonstrated novel probabilistic deep learning reliability modelling in Turbofan Engine Degradation Dataset.
Turing test relevance questioned in age of AI.
problem Relevance of Turing test in AI age.
method Examining cultural and technological context.
result Turing test may not fully capture AI capabilities.
The paper analyzes tech specialization and diversification at various scales.
problem Trade-offs between specialization and diversification in economic development.
method Patent data and Economic Complexity framework.
result Technological Coherence positively impacts growth at metropolitan areas but negatively at larger scales.
Modeling tech transfer to explain convergence in Central and Eastern Europe.
problem Understanding mechanisms of technological diffusion in developing economies.
method Introducing a herding-based mechanism to model technological adoption and productivity growth.
result Explicit analytical solution showing nonlinear convergence to a moving frontier.
Deep learning detects cyber-attacks in smart grid systems.
problem Cyber-attacks on smart grid systems.
method Deep learning-based intrusion detection system trained on industrial dataset.
result Proposed system outperforms Naive Bayes, SVM, and Random Forest.
This paper uses decolonial theory to improve AI's ethical development.
problem AI's risks to vulnerable peoples and negative impacts of innovation.
method Embedding decolonial critical approach in AI technical practice.
result Developing tactics to align AI with ethical principles.
BCIQT model improves ML prediction effectiveness using quantum theory.
problem Improving prediction effectiveness in machine learning models.
method Proposes Binary Classifier Inspired by Quantum Theory (BCIQT) model.
result BCIQT model outperforms state-of-the-art models in recall.
Deep learning enhances bioinformatics and medical data analysis.
problem Challenges in bioinformatics and medical data analysis.
method Application of deep learning methods in bioinformatics and medicine.
result Deep learning improves knowledge discovery in bioinformatics and medicine.
Survey examines ML for IoT security, addressing new challenges.
problem IoT security challenges due to rapid growth and diverse attacks.
method Comprehensive literature review of ML-based security solutions.
result ML provides dynamic and efficient security for IoT.
Survey of assurances for trust in human-autonomy systems.
problem Ensuring trust in human-autonomy systems.
method Survey and review of existing research.
result Refined definition of assurances for trust.
Deep learning powers automotive innovations like self-driving cars.
problem Improving vehicle safety and functionality.
method Deployment of deep learning models in ADAS systems.
result Deep learning enhances performance and functionality of ADAS solutions.
We calculate the optimal solutions of the fully heterogeneous Von Neumann expansion problem with N processes and P goods in the limit N→∞. This model provides an elementary description of the growth of a production economy in the long run. The system turns from a contracting to an expanding phase as N in…
The paper tackles financial market dynamics with new tech-driven data.
problem High-dimensional, high-correlation, and time-varying financial data.
method Developing adaptive multi-factor models and techniques to handle data complexities.
result Improved interpretability, clearer explanations, and better predictions.
Survey examines public views on facial recognition technology.
problem Public acceptance and privacy concerns with facial recognition.
method Cross-national survey of 4 countries.
result Public views vary significantly across countries.
Blockchain and AI improve invoice financing for supply chains.
problem Challenges in invoice financing for upstream suppliers in complex supply chains.
method Combining blockchain and AI technologies to solve financing issues.
result Atomic crosschain functionality enables informed decisions under uncertainty.
The algorithmic trading comes from digitalisation of the processing of trading assets on financial markets. Since 1980 the computerization of the stock market offers real time processing of financial information. This technological revolution has offered processes and mathematic methods to identify best return on trans…
MarketSenseAI uses LLMs to improve stock analysis and outperforms benchmarks.
problem Improving accuracy in stock analysis and selection.
method Combining LLMs with SEC filings, earnings calls, and macroeconomic reports.
result Significant improvement in fundamental analysis accuracy and outperformance of benchmarks.
This paper examines market misconduct in DeFi and proposes regulatory solutions.
problem Novel forms of market misconduct in DeFi.
method Comprehensive analysis, comparative study, empirical measurements, and tailored regulatory framework investigation.
result Identification of key areas for regulatory enhancement in DeFi.
Variable selection in high dimensional space has challenged many contemporary statistical problems from many frontiers of scientific disciplines. Recent technology advance has made it possible to collect a huge amount of covariate information such as microarray, proteomic and SNP data via bioimaging technology while ob…
Optimizes chip component placement with self-alignment for SMT technology.
problem Achieving precise component placement on PCB during SMT process.
method Proposed machine learning algorithms (SVR and RFR) to predict component positions and developed non-linear optimization model.
result RFR model outperforms in predicting component positions before reflow.
This paper evaluates AI ethics guidelines and their implementation.
problem Lack of comprehensive and effective AI ethics guidelines.
method Comprehensive evaluation and comparison of released ethics guidelines.
result Identifies overlaps and omissions in AI ethics guidelines.
Framework simplifies AI access for all.
problem AI's concentration of power leads to inequalities.
method Develops a Python framework for democratizing AI.
result Single interface for various AI solutions.
This research reviews reinforcement learning for optimizing building energy management.
problem Optimizing energy utilization in building management systems.
method Comprehensive review of reinforcement learning applications in building energy management.
result Challenges and future directions in reinforcement learning for building energy management.
Paper proposes a federated graph learning platform to improve financial crime detection.
problem Current financial crime detection methods are ineffective and costly.
method Federated graph learning platform combining federated learning and graph learning.
result Federated model outperforms local model by 20%.
Recent advances in high-throughput cDNA sequencing (RNA-Seq) technology have revolutionized transcriptome studies. A major motivation for RNA-Seq is to map the structure of expressed transcripts at nucleotide resolution. With accurate computational tools for transcript reconstruction, this technology may also become us…
These are expository notes from the 2008 Srni Winter School. They have two purposes: (1) to give a quick introduction to exterior differential systems (EDS), which is a collection of techniques for determining local existence to systems of partial differential equations, and (2) to give an exposition of recent work (jo…
FinTech negatively impacts Chinese banks' financial sustainability.
problem Impact of FinTech on financial sustainability of Chinese commercial banks.
method Three-stage network DEA-Malmquist model and two-way fixed effects model.
result FinTech primarily undermines financial sustainability by eroding loan efficiency and profitability.
OMLT combines ML and optimization for solving complex problems.
problem Solving complex decision-making problems in computer science and engineering.
method OMLT integrates neural networks and gradient-boosted trees into optimization problems using machine learning.
result OMLT seamlessly integrates with Pyomo and solves real-world problems.
High-dimensional statistics advances in complex data domains.
problem Complex, rich datasets challenge traditional methods.
method Evolved to address sophisticated estimation and inference problems.
result Deepened connections with optimization, concentration, and information theory.
ST-GAN predicts stock trends using financial news and data.
problem Predicting financial trends in stock markets.
method ST-GAN combines NLP and technical indicators using GAN technology.
result Significant improvement over existing models in stock price forecasting.
Blockchain disrupts corporate finance, but challenges remain.
problem Challenges in adopting blockchain for corporate finance.
method Exploring the impact of blockchain on corporate finance valuation and capital allocation.
result Blockchain offers new perspectives but faces regulatory, environmental, and legal challenges.
The incidence of malignant melanoma continues to increase worldwide. This cancer can strike at any age; it is one of the leading causes of loss of life in young persons. Since this cancer is visible on the skin, it is potentially detectable at a very early stage when it is curable. New developments have converged to ma…
The paper explores how innovative financing solutions boost Moroccan businesses' performance.
problem Market volatility, ecological transitions, and technological change pose challenges to business sustainability.
method Examines innovative financing solutions like venture capital, green finance, crowdfunding, and blockchain.
result Embracing innovative financial strategies can transform business challenges into opportunities.
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.
New method optimizes deep neural network weights using data statistics.
problem Vanishing/exploding gradient problem and non-convex objective function in DNNs.
method Data-dependent initialization of network weights.
result Our algorithm achieves superior classification accuracy on practical datasets.
Quantum computing promises faster bioinformatics, but challenges remain.
problem Efficient bioinformatics processing and drug discovery.
method Quantum algorithms for optimization, simulation, and machine learning.
result Quantum computing can significantly speed up bioinformatics tasks.
This study analyzes wireless network data using classification techniques.
problem Identify normal and abnormal traffic in wireless networks.
method Used WEKA software with predefined anomaly classes from the MAC layer.
result Classification algorithms show success in detecting anomalies.
CausalBench aims to advance causal learning research with a transparent platform.
problem Lack of unified benchmark datasets, algorithms, metrics, and evaluation interfaces for causal learning.
method Introduces CausalBench, a flexible benchmark framework for causal analysis and machine learning.
result Promotes scientific collaboration, reproducibility, and awareness in causal learning research.
Biotech IPOs in Q1 2021: advanced degrees, clinical trials, and IP key.
problem Identifying traits of biotech startups that go public.
method Database of biotech IPOs, analysis of leadership, technology, clinical trials, and financing.
result Advanced degrees, clinical trials, and IP are important for biotech startups.
Develops a deep learning framework to predict future tech directions for high-tech companies.
problem Difficult task in predicting future R&D trends for high-tech companies due to complexity and variety of factors.
method Deep Technology Forecasting (DTF) framework with three components: PCR, CTR, and DTT neural network.
result DTF framework precisely predicts future tech emphasis of companies using hybrid factors.
Advanced ML/DL models predict stock prices using technical analysis.
problem Accurately predicting stock prices in a complex market.
method Use of deep learning models for stock price prediction.
result Deep learning models can predict stock prices with high accuracy.
Survey of AI in quant finance, from deep learning to LLMs.
problem Improving predictive modeling and automation in asset management.
method Exploring AI contributions to quant investment pipeline, from human-crafted features to LLMs.
result AI has enabled scalable modeling and autonomous agents in quant finance.
This paper examines anomalies and frauds in blockchain networks and proposes detection techniques.
problem Anomalies and frauds undermine blockchain networks' integrity and security.
method Statistical and machine learning methods, game-theoretic solutions, digital forensics, reputation-based systems, and risk assessment techniques.
result Practical applications and insights for enhancing blockchain network security.