3,179 research outputs found
Relaxed Game Chromatic Numbers of Complete Multipartite Graphs
Competitive graph coloring is investigated by studying a game with two players, Alice and Bob, on a finite graph G with a set of r colors. Alice and Bob alternately color the vertices of G with legal colors. In the k-relaxed coloring game, a color c is legal for a vertex v if v has at most k neighbors previously colored c. New results about the 0, 1, and 2-relaxed game chromatic numbers will be presented, completely classifying the 0 and 1-relaxed games and partially classifying the 2-relaxed game. These results will be presented in the context of previous research and given a direction of where they need to go next
Forecasting the Prices of Cryptocurrencies using a Novel Parameter Optimization of VARIMA Models
This work is a comparative study of different univariate and multivariate time series predictive models as applied to Bitcoin, other cryptocurrencies, and other related financial time series data. ARIMA models, long regarded as the gold standard of univariate financial time series prediction due to both its flexibility and simplicity, are used a baseline for prediction. Given the highly correlative nature amongst different cryptocurrencies, this work aims to show the benefit of forecasting with multivariate time series models—primarily focusing on a novel parameter optimization of VARIMA models outlined in this paper.
These models are trained on 3 years of historical data, aggregated from different cryptocurrency exchanges by Coinmarketcap.com, which includes: daily average prices and trading volume. Historical time series data of traditional market data, including the stock Nvidia, the de facto leading manufacture of gaming GPU’s, is also analyzed in conjunction with cryptocurrency prices, as gaming GPU’s have played a significant role in solving the profitable SHA256 hashing problems associated with cryptocurrency mining and have seen equivalently correlated investor attention as a result. Models are trained on this historical data using moving window subsets, with window lengths of 100, 200, and 300 days and forecasting 1 day into the future. Validation of this prediction against the actually price from that day are done with following metrics: Directional Forecasting (DF), Mean Absolute Error (MAE), and Mean Squared Error (MSE)
Evaluation of a global soil moisture product from finer spatial resolution sar data and ground measurements at Irish sites
In the framework of the European Space Agency Climate Change Initiative, a global, almost daily, soil moisture (SM) product is being developed from passive and active satellite microwave sensors, at a coarse spatial resolution. This study contributes to its validation by using finer spatial resolution ASAR Wide Swath and in situ soil moisture data taken over three sites in Ireland, from 2007 to 2009. This is the first time a comparison has been carried out between three sets of independent observations from different sensors at very different spatial resolutions for such a long time series. Furthermore, the SM spatial distribution has been investigated at the ASAR scale within each Essential Climate Variable (ECV) pixel, without adopting any particular model or using a densely distributed network of in situ stations. This approach facilitated an understanding of the extent to which geophysical factors, such as soil texture, terrain composition and altitude, affect the retrieved ECV SM product values in temperate grasslands. Temporal and spatial variability analysis provided high levels of correlation (p < 0.025) and low errors between the three datasets, leading to confidence in the new ECV SM global product, despite limitations in its ability to track the driest and wettest conditions
Military, Inc. Private Military Companies And State-Centrism In International Relations.
This study sheds light on the relationship between military privatisation and state-centrism in international relations. The growth of the private military industry has led many to consider the operational implications of the military privatisation program, focusing on the merits of the industry and its inadequate regulation. Few have considered the ontological implications of military privatisation; that as the state outsources what many consider to be its core function and purpose – public security – military privatisation challenges the nature of the state and its central role in international relations. This thesis seeks to further the ontological argument by employing an English School approach to international relations. This approach allows for the puzzle to be interrogated at multiple levels and within three separate yet overlapping realms; the International System, International Society, and World Society. In contrast to existing research, I find that the state remains central to international relations. I conclude that although private military companies do not challenge the notion of state-centrism in international relations, the English School remains a powerful tool for exploring international phenomena. I also demonstrate the need for international relations theory to account for the changing identity of security actors and interplay between states
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A dynamic physical energy model of the United Kingdom
This report describes the structure and simulation results of a dynamic physical model of the UK energy system. The model traces the hourly flows of energy from energy sources through various energy converters and stores to useful energy demands. Effects such as the temporal and climatic dependence of demands have been accounted for. Technical data has been collected so that it is possible to simulate the performance of the system as it was in 1976 or as it might be at some future date. The model has been validated against measured data and has been used to simulate the UK system with changed demands and new conservation and supply technologies
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An investigation of potential periglacial landforms on the northern plains of Mars: an integrated field, laboratory and remote sensing study
In this investigation the hypothesis that the Northern Plains of Mars have been shaped by periglacial processes is assessed. A periglacial formation mechanism has been proposed for a variety of martian landforms. These were examined with a particular focus on clastic patterned ground.
Periglacial environments occur in cold climate regions of Earth due to the repeated freezing and thawing of water, they require the presence of liquid water to develop. Consequently, if martian landforms are periglacial then they would provide a useful geomorphic marker for locations where water has been liquid in the geologically recent past.
The main strand of this investigation consisted of a survey of high resolution images from the Mars Reconnaissance Orbiter spacecraft. Locations with putative periglacial landforms were examined to test this and other formation hypotheses. This series of surveys was supported by two other research activities; two field campaigns were conducted to examine sorted patterned ground in Iceland. Air photographs, verified by in situ observations, were compared to the martian features studied in the main survey. A laboratory study was also conducted with the aim of testing whether periglacial processes were viable under the low temperature conditions found on the martian surface in the present day. This “proof of concept” study proved inconclusive, but is summarised for completeness.
It was found that the morphology and situation of these martian landforms was a reasonable fit for that which would be expected in a periglacial environment. Two alternative theories to explain the formation of martian clastic networks were rejected, as they did not appear to fit with the observed morphologies. It remains uncertain whether periglacial processes are viable on Mars, but they remain the best theory to explain the occurrence of clastic networks on the Northern Plains
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