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result(s) for
"Outer space Exploration Forecasting."
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Mankind beyond Earth
Seeking to reenergize Americans' passion for the space program, the value of further exploration of the Moon, and the importance of human beings on the final frontier, Claude A. Piantadosi presents a rich history of American space exploration and its major achievements. He emphasizes the importance of reclaiming national command of our manned program and continuing our unmanned space missions, and he stresses the many adventures that still await us in the unfolding universe. Acknowledging space exploration's practical and financial obstacles, Piantadosi challenges us to revitalize American leadership in space exploration in order to reap its scientific bounty. Piantadosi explains why space exploration, a captivating story of ambition, invention, and discovery, is also increasingly difficult and why space experts always seem to disagree. He argues that the future of the space program requires merging the practicalities of exploration with the constraints of human biology. Space science deals with the unknown, and the margin (and budget) for error is small. Lethal near-vacuum conditions, deadly cosmic radiation, microgravity, vast distances, and highly scattered resources remain immense physical problems. To forge ahead, America needs to develop affordable space transportation and flexible exploration strategies based in sound science. Piantadosi closes with suggestions for accomplishing these goals, combining his healthy skepticism as a scientist with an unshakable belief in space's untapped—and wholly worthwhile—potential.
eBook
Extreme Magnetic Storm of May 10–19, 2024: Coupling between Neutral and Charged Components of the Upper Atmosphere and the Effect on Radio Systems
Active exploration of space for communication, navigation, and Earth remote sensing in recent decades has drawn increased attention to the study of the Sun’s impact on the Earth and requires creating effective models for space weather forecast. Magnetic storms that produce disturbances in the ionosphere and atmosphere are the strongest manifestation of space weather. Among such events is the magnetic storm that started on May 10, 2024, during which the auroral oval reached 19° N. Over the past 20 years since the last magnetic storm of similar intensity was observed, new scientific facilities have been put into operation as part of the National Heliogeophysical Complex of the Russian Academy of Sciences. A huge decrease in the electron density (by a factor of five relative to the background level) and record-breaking airglow of the upper atmosphere (the atomic oxygen red line airglow exceeded 25 kR) compared to the strongest storms in solar cycle 23 were recorded. The combined optical and radio-physical measurements in Eastern Siberia, supported by data from global networks, demonstrated the correlation between the temperature increase in the upper atmosphere and a strong decrease in the ionospheric electron density at mid-latitudes due to increased recombination during the storm. Combined measurements from ionosonde and high-frequency radar networks have shown a significant deterioration in the conditions of radio wave propagation. The complementarity of the currently deployed scientific instruments opens up new opportunities for monitoring the state of the near-Earth space, as well as for studying and modeling dynamic processes during such extreme phenomena with unprecedented detail.
Journal Article
Space 2069 : after Apollo: back to the Moon, to Mars, and beyond
Half a century after Apollo 11 we have still not returned to the Moon, but that is about to change. The thirteenth person to walk on the Moon could soon be part of a crew establishing a base on the lip of a crater at the lunar south pole. The discovery of ice in the eternal shadows of the polar regions transforms our ability to live on the Moon. From bases on the Moon we can make the long, lonely and dangerous voyage to Mars, where there is also ice. The obstacles are many, not least the fragilities of the human body. And what type of world would the first Mars explorers find?
BOOK
Symmetry-Aware Short-Term Load Forecasting in Distribution Networks: A Synergistic Enhanced KMA-MVMD-Crossformer Framework
Accurate and efficient short-term load forecasting is crucial for the secure and stable operation and scheduling of power grids. Addressing the inability of traditional Transformer-based prediction models to capture symmetric correlations between different feature sequences and their susceptibility to multi-scale feature influences, this paper proposes a short-term power distribution network load forecasting model based on an enhanced Komodo Mlipir Algorithm (KMA)—Multivariate Variational Mode Decomposition (MVMD)-Crossformer. Initially, the KMA is enhanced with chaotic mapping and temporal variation inertia weighting, which strengthens the symmetric exploration of the solution space. This enhanced KMA is integrated into the parameter optimization of the MVMD algorithm, facilitating the decomposition of distribution network load sequences into multiple Intrinsic Mode Function (IMF) components with symmetric periodic characteristics across different time scales. Subsequently, the Multi-variable Rapid Maximum Information Coefficient (MVRapidMIC) algorithm is employed to extract features with strong symmetric correlations to the load from weather and date characteristics, reducing redundancy while preserving key symmetric associations. Finally, a power distribution network short-term load forecasting model based on the Crossformer is constructed. Through the symmetric Dimension Segmentation (DSW) embedding layer and the Two-Stage Attention (TSA) mechanism layer with bidirectional symmetric correlation capture, the model effectively captures symmetric dependencies between different feature sequences, leading to the final load prediction outcome. Experimental results on the real power distribution network dataset show that: the Root Mean Square Error (RMSE) of the proposed model is as low as 14.7597 MW, the Mean Absolute Error (MAE) is 13.9728 MW, the Mean Absolute Percentage Error (MAPE) reaches 4.89%, and the coefficient of determination (R2) is as high as 0.9942.
Journal Article
Space weather: the solar perspective
The Sun, as an active star, is the driver of energetic phenomena that structure interplanetary space and affect planetary atmospheres. The effects of Space Weather on Earth and the solar system is of increasing importance as human spaceflight is preparing for lunar and Mars missions. This review is focusing on the solar perspective of the Space Weather relevant phenomena, coronal mass ejections (CMEs), flares, solar energetic particles (SEPs), and solar wind stream interaction regions (SIR). With the advent of the STEREO mission (launched in 2006), literally, new perspectives were provided that enabled for the first time to study coronal structures and the evolution of activity phenomena in three dimensions. New imaging capabilities, covering the entire Sun-Earth distance range, allowed to seamlessly connect CMEs and their interplanetary counterparts measured in-situ (so called ICMEs). This vastly increased our knowledge and understanding of the dynamics of interplanetary space due to solar activity and fostered the development of Space Weather forecasting models. Moreover, we are facing challenging times gathering new data from two extraordinary missions, NASA’s Parker Solar Probe (launched in 2018) and ESA’s Solar Orbiter (launched in 2020), that will in the near future provide more detailed insight into the solar wind evolution and image CMEs from view points never approached before. The current review builds upon the Living Reviews article by Schwenn from 2006, updating on the Space Weather relevant CME-flare-SEP phenomena from the solar perspective, as observed from multiple viewpoints and their concomitant solar surface signatures.
Journal Article
Analyzing social media, analyzing the social? A methodological discussion about the demoscopic and predictive potential of social media
The impact of computational technologies and the worldwide use of Internet entails a theoretical and methodological challenge for social scientists, considering the purpose of observing, interpreting and explaining human and social behaviour. Today, the digital environment seems to be an adequate space for this exploration and the emergence of the Web 2.0 offers common people the possibility of expressing and sharing their opinions on a daily basis. Due to the ubiquity of technology, Internet and social media in people’s lives, socialization and its expressiveness have changed. If this is the case, the means to measure the perceptions, opinions and judgements of citizens should also change. The immense quantity of data available to be analysed today poses a challenge for the traditional scientific model. In this sense, it could be necessary for social research to move towards the analysis of the web and consider the potential predictive capacity of digital demoscopy. A new field of study has opened, with interest in exploring the predictive capacity of social media in electoral contexts. As a research group comprised by linguists, communication experts and engineers we explored the predictive potential of social media in three national elections that took place in Chile during 2017. Our objective was to explore a methodological design that allows predicting the result of political elections through the use of inductive algorithms and the automatic processing of messages with political opinion in social media. Through computational intelligence, we were able to follow, collect and analyse millions of tweets, and to improve our forecast each time. Our learning based on empirical research was fundamental to improve our procedures and to refine our variables and, thus, improve our prediction.
Journal Article
Automated Scheduling for NASA's Deep Space Network
This article describes the Deep Space Network (DSN) scheduling engine (DSE) component of a new scheduling system being deployed for NASA's Deep Space Network. The DSE provides core automation functionality for scheduling the network, including the interpretation of scheduling requirements expressed by users, their elaboration into tracking passes, and the resolution of conflicts and constraint violations. The DSE incorporates both systematic search‐ and repair‐based algorithms, used for different phases and purposes in the overall system. It has been integrated with a web application that provides DSE functionality to all DSN users through a standard web browser, as part of a peer‐to‐peer schedule negotiation process for the entire network. The system has been deployed operationally and is in routine use, and is in the process of being extended to support long‐range planning and forecasting and near real‐time scheduling.
Journal Article