In recent years numerous advanced malware, aka advanced persistent threats (APT) are allegedly developed by nation-states. The task of attributing an APT to a specific nation-state is extremely challenging for several reasons. Each nation-state has usually more than a single cyber unit that develops such advanced malwa…
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48 results for “United Nations”
End-to-End Deep Neural Networks and Transfer Learning for Automatic Analysis of Nation-State Malwarecs.CR
Deep neural networks classify nation-state malware with high accuracy.
problem Classifying and attributing advanced persistent threats (APT) from nation-states.
method Used deep neural networks to analyze malware behavior in a sandbox, learning high-level feature abstractions.
result Achieved 98.6% accuracy in classifying 1000 Chinese and Russian APTs.
Machine learning predicts homicide clearance rates with SHAP explaining key features.
problem Predicting and explaining homicide clearance rates in the US.
method Nine algorithmic approaches compared; XGBoost selected. SHAP used for feature importance.
result XGBoost best predicts national homicide clearance rates; SHAP reveals key features.
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.
The Security of the United Kingdom Electricity Imports under Conditions of High European Demandecon.EM
Energy policy in Europe has been driven by the three goals of security of supply, economic competitiveness and environmental sustainability, referred to as the energy trilemma. Although there are clear conflicts within the trilemma, member countries have acted to facilitate a fully integrated European electricity marke…
Detects and maps informal settlements using satellite data.
problem Mapping informal settlements for aid distribution.
method Combining satellite data and machine learning for roofing material detection.
result Effective aid distribution through accurate settlement mapping.
Mapping Informal Settlements in Developing Countries with Multi-resolution, Multi-spectral Datacs.LG
Detects and maps informal settlements in developing countries using satellite imagery.
problem Mapping informal settlements for aid delivery.
method Two methods: LR Sentinel-2 imagery and VHR satellite imagery.
result Successfully mapped informal settlements with LR satellite imagery.
D-ETM models document topics over time using embeddings and variational inference.
problem Capturing evolving topic patterns in sequential documents.
method Combines D-LDA and word embeddings, using random walk priors and variational inference.
result D-ETM outperforms D-LDA on document completion tasks, learning more diverse and coherent topics.
This study analyzes global terrorist attacks using data mining techniques.
problem Efficient analysis and prediction of global terrorist attacks.
method Data mining classification techniques, including Lazy Tree, Multilayer Perceptron, Multiclass, and Naïve Bayes.
result Identified trends in attack frequency and locations.
We investigate relationship between annual electric power consumption per capita and gross domestic production (GDP) per capita for 131 countries. We found that the relationship can be fitted with a power-law function. We examine the relationship for 47 prefectures in Japan. Furthermore, we investigate values of annual…
I studied the convergence of regional house prices to national prices in USA by analyzing time-series of house price indices of 9 Census Divisions. I found the evidence of the convergence in some parts of the country using asymmetric unit root tests. The fact that the evidence of the convergence is not present in large…
AquaSight detects water impurity using deep learning.
problem Water pollution and lack of affordable water quality assessment.
method Convolutional Neural Networks for automated water impurity detection.
result Deep learning model achieved 96% accuracy in detecting water contamination.
Developing Knowledge States: Technology and the Enhancement of National Statistical Capacityq-fin.GN
National statistical systems are the enterprises tasked with collecting, validating and reporting societal attributes. These data serve many purposes - they allow governments to improve services, economic actors to traverse markets, and academics to assess social theories. National statistical systems vary in quality, …
Signature of maturity in cryptocurrency volatilityphysics.soc-ph
Study shows cryptocurrency price fluctuations become more similar to national currencies over time.
problem Understanding the volatility and inequality in cryptocurrency prices.
method Calculated inequality measures (Gini, Kolkata indices, factor) for cryptocurrency and national currency price fluctuations over 10 years.
result Cryptocurrency price fluctuations become more similar to national currencies over time.
Every year at the United Nations, member states deliver statements during the General Debate discussing major issues in world politics. These speeches provide invaluable information on governments' perspectives and preferences on a wide range of issues, but have largely been overlooked in the study of international pol…
Data mining revealed a cluster of economic, psychological, social and cultural indicators that in combination predicted corruption and wealth of European nations. This prosperity syndrome of self-reliant citizens, efficient division of labor, a sophisticated scientific community, and respect for the law, was clearly di…
Study shows how national culture influences investors' tendency to hold or sell stocks.
problem Investors' tendency to hold or sell stocks varies internationally.
method Examined brokerage data from 83 countries, analyzed cultural dimensions and age/gender.
result National culture, specifically long-term orientation and indulgence, influences the disposition effect.
This study analyzes economic policy uncertainty indices using visibility graphs.
problem Understanding the role of economic policy uncertainty in global economies.
method Visibility graph algorithm applied to economic policy uncertainty indices.
result The economic policy uncertainty indices exhibit persistent behavior and scale-free networks.
Public debt is one of the important economic variables that quantitatively describes a nation's economy. Because bankruptcy is a risk faced even by institutions as large as governments (e.g. Iceland), national debt should be strictly controlled with respect to national wealth. Also, the problem of eliminating extreme p…
Cointegration helps insurers understand long-range mortality patterns.
problem Insurers struggle to detect long-range dependence in their mortality data.
method Cointegration techniques applied to mixed fractional Brownian motion (mfBm) to capture long-range dependence.
result Cointegration brings long-range dependence information from national mortality data to insurers' models.
Study shows racial bias in health data, which can be reduced with simple techniques.
problem Racial bias in health indicators measured by the Medical Expenditure Panel Survey (MEPS).
method Used publicly available and nationally representative MEPS data to show bias in predictive models for care management.
result Racial bias can be significantly reduced using simple mitigation techniques.
Why do nations produce scientific research? This is a fundamental problem in the field of social studies of science. The paper confronts this question here by showing vital determinants of science to explain the sources of social power and wealth creation by nations. Firstly, this study suggests a new general definitio…
The DoD needs a robust process to evaluate AI/ML model performance and robustness.
problem AI/ML models are brittle and nonrobust, posing risks in national security.
method Reviews AI/ML development process and best practices for evaluation.
result Recommendations for DoD evaluators to ensure robust AI/ML capabilities.
Study examines how BRICS nations' economies respond to COVID-19.
problem Impact of COVID-19 on BRICS nations' economic indicators.
method Structural variable autoregression (SVAR) to analyze growth, exchange rate, and stock market data.
result COVID-19 shock to exchange rate growth persists for 10+ days, stock market growth for 15 days.
Ecological systems have a high level of complexity combined with stability and rich biodiversity. Recently, the analysis of their properties and evolution has been pushed forward on a basis of concept of mutualistic networks that provides a detailed understanding of their features being linked to a high nestedness of t…
Textual data predicts electricity consumption and weather.
problem Lack of textual data in time series prediction models.
method Used TF-IDF and neural word embeddings to predict time series from text.
result Textual data can predict time series with sufficient accuracy.
I studied what role the US stock markets and money markets have possibly played in the Gross Private Domestic Investment (GPDI) of the United States from the year 1959 to the year 2001, Gross Private Domestic Investment refers to the total amount of investment spending by businesses and firms located within the borders…
New complete panel dataset for LMICs helps analyze innovation and development.
problem Lack of complete data for empirical analyses in LMICs.
method Predictive Mean Matching multiple imputation technique.
result Created a large dataset of 47 variables for 82 LMICs from 2005-2019.
Study examines the impact of employment benefit costs on firm profitability.
problem Impact of employment benefit costs on firm profitability.
method Panel data regression analysis using E-Views.
result There is a significant positive relationship between employment benefit costs and firm profitability.
We propose a novel multi-layered nonlinear model that is able to capture and predict the housing-demographic dynamics of the real-state market by simulating the transitions of owners among price-based house layers. This model allows us to determine which parameters are most effective to smoothen the severity of a poten…
SaML guides ML models to avoid survey biases.
problem ML models trained on survey data often ignore survey design metadata.
method Nine-step guideline for incorporating survey design metadata in ML lifecycle.
result SaML provides valid population inference from survey data.
REGOMAX analyzes EU economies' sensitivity to petroleum and gas trade from major exporters.
problem Analyzing EU economies' sensitivity to petroleum and gas trade from major exporters.
method Reduced Google matrix (REGOMAX) algorithm applied to UN COMTRADE data.
result Shows sensitivity of each EU country to petroleum and gas trade from Russia, USA, Saudi Arabia, and Norway.
Mathematical models help keep vaccine prices low.
problem Pricing COVID-19 vaccines to ensure affordability and profitability.
method Optimization and game theory approaches modeling a duopoly market.
result Government can negotiate low prices while manufacturers earn profits.
ESN model helps understand climate event impacts.
problem Understanding complex climate event impacts.
method Feature importance methods for ESNs on spatio-temporal climate data.
result Characterized relationships between Mount Pinatubo eruption variables.
GDP of China is about 11 trillion dollars and GDP of the United States is about 18 trillion dollars. Suppose that we know for the coming years, economy of the US will experience a real growth rate equal to \%3 and economy of China will experience a real growth as of \%6. Now, the question is how long does it take for e…
We aim to create a framework for transfer learning using latent factor models to learn the dependence structure between a larger source dataset and a target dataset. The methodology is motivated by our goal of building a risk-assessment model for surgery patients, using both institutional and national surgical outcomes…
One unexamined assumption in foreign ownership regulation is the notion that majority voting rights translate to 'effective control'. This assumption is so deeply entrenched in foreign investments law that possession of majority voting rights can determine the nationality of a corporation and its capacity to engage in …
CPAS uses machine learning to plan hospital resources for COVID-19.
problem Forecasting hospital resource demands during the COVID-19 pandemic.
method Combining machine learning algorithms with diverse data sources.
result CPAS successfully managed hospital resource planning in the UK.
System builds Somali ASR for UN humanitarian efforts.
problem Developing ASR for under-resourced Somali language.
method Acoustic model training with annotated speech, neural architectures, language model data augmentation, acoustic data perturbation.
result Best system achieved 53.75% word error rate.
Paper presents an econophysics model for mixed economies.
problem Understanding mixed economies in various countries.
method Developed an econophysics model with a reduced state sector participation.
result Proposed a new model with a 10-15% state sector participation.
We propose a diffusion process to describe the global dynamic evolution of credit operations at a national level given observed operations at a subnational level in a sovereign country. Empirical analysis with a unique dataset from Brazilian federate constituents supports the conclusions. Despite the heterogeneity obse…
Multiplex Dirichlet stochastic block model for clustering multidimensional compositional networksstat.ME
Proposes a new model for clustering multiplex networks with compositional data.
problem Clustering multiplex networks with multiple types of relations and compositional data.
method Multiplex Dirichlet stochastic block model for compositional networks.
result Validated through simulation and applied to international export data.
Analyzes national real estate investment risks and returns.
problem Investors and home buyers face increasing costs and risks.
method Examines economic vulnerabilities and traditional market analysis.
result Ensures positive returns and fair prices for real estate investments.
Using the United Nations Commodity Trade Statistics Database [http://comtrade.un.org/db/] we construct the Google matrix of the world trade network and analyze its properties for various trade commodities for all countries and all available years from 1962 to 2009. The trade flows on this network are classified with th…
A Natural Disasters Indexq-fin.RM
NDI aims to forecast future natural disasters risk for insurers.
problem Increasing intensity and frequency of natural disasters.
method Develops a Natural Disasters Index (NDI) based on NOAA data.
result NDI forecasts future natural disasters risk for insurers.
Foreign policy analysis has been struggling to find ways to measure policy preferences and paradigm shifts in international political systems. This paper presents a novel, potential solution to this challenge, through the application of a neural word embedding (Word2vec) model on a dataset featuring speeches by heads o…
Study uses Google matrix analysis to show how COVID-19 changed international trade flows.
problem Impact of COVID-19 on international trade patterns.
method Google matrix analysis of World Trade Network (WTN), including PageRank, CheiRank, and reduced Google matrix.
result Significant changes in international trade flows due to the pandemic, affecting export and import balances.
Understanding cities is central to addressing major global challenges from climate and health to economic resilience. Although increasingly perceived as fundamental socio-economic units, the detailed fabric of urban economic activities is only now accessible to comprehensive analyses with the availability of large data…