scholarly journals Space Computation Sciences Leveraging Cloud Computing, Artificial Intelligence, and Advanced Analytics to Power Innovation: A Review Report

2018 ◽  
Vol 5 (2) ◽  
pp. 89-90
Author(s):  
Takudzwa Fadziso
Keyword(s):  
Artificial Intelligence ◽  
Data Analytics ◽  
Technological Innovations ◽  
Space Technology ◽  
The Moon ◽  
Space Industry ◽  
New Space ◽  
Advanced Analytics ◽  
Cloud Technologies ◽  
Modern Technologies

In order to realize the goal of exploring and discovering new worlds, technological innovations are important. The space industry has been growing since the first space ship landed on the moon in the Apollo 11 mission. Huge leaps in space technology experienced since then combined with modern technologies such Artificial Intelligence, Data Analytics and Cloud technology can help space explorers to go further in space and explore territories not reached before, and potentially uncover new space phenomena. The objective of this research is to explore how space computation sciences can leverage Artificial Intelligence, Cloud technologies, and Advanced Data Analysis to power innovations.

The Nature of Intelligent Analytics

2021 ◽  
pp. 1-21
Author(s):  
Zhaohao Sun ◽  
Andrew Stranieri
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Research And Development ◽  
Business Intelligence ◽  
Data Analytics ◽  
Data Science ◽  
Big Data Analytics ◽  
Business Analytics ◽  
Novel Approach ◽  
Advanced Analytics

Intelligent analytics is an emerging paradigm in the age of big data, analytics, and artificial intelligence (AI). This chapter explores the nature of intelligent analytics. More specifically, this chapter identifies the foundations, cores, and applications of intelligent big data analytics based on the investigation into the state-of-the-art scholars' publications and market analysis of advanced analytics. Then it presents a workflow-based approach to big data analytics and technological foundations for intelligent big data analytics through examining intelligent big data analytics as an integration of AI and big data analytics. The chapter also presents a novel approach to extend intelligent big data analytics to intelligent analytics. The proposed approach in this chapter might facilitate research and development of intelligent analytics, big data analytics, business analytics, business intelligence, AI, and data science.

scholarly journals Ζητήματα Βιοηθικής της Βιοαστροναυτικής

Bioethica ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 20
Author(s):  
George Profitiliotis (Γεώργιος Προφητηλιώτης)
Keyword(s):  
Space Research ◽  
Technological Innovations ◽  
Extraterrestrial Life ◽  
Academic Literature ◽  
Space Industry ◽  
Bioethical Issues ◽  
New Space ◽  
Space Economy ◽  
Life On Earth ◽  
Example Space

The rise of emergent space initiatives -especially of private ones- has begun to push the boundaries of the space industry, thanks to technological innovations that will soon be able to significantly facilitate the development of previously neglected pioneering fields, such as, for example, space research and exploration, space resources utilization, and human access to space. The invigoration and the forthcoming growth of this new space economy in the aforementioned pioneering fields are expected to bring forward important bioethical issues. The purpose of this paper is to summarize the most important of these issues, after a review of a significant number of relevant publications in the international academic literature. In particular, this paper will present bioethical issues in the field of bioastronautics -especially in light of future missions to Mars- that refer to both life on Earth, i.e. microorganisms, plants, animals and humans, and to potential extraterrestrial life. Given the accelerating rate of developments, the best time to discuss these issues, in order to inform policymaking, is now.

Computing Possible Futures

2019 ◽  
Author(s):  
William B. Rouse
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Computational Modeling ◽  
Mental Model ◽  
Data Analytics ◽  
Computational Models ◽  
Senior Managers ◽  
Interactive Visualizations ◽  
Use Of Models ◽  
Better Than

This book discusses the use of models and interactive visualizations to explore designs of systems and policies in determining whether such designs would be effective. Executives and senior managers are very interested in what “data analytics” can do for them and, quite recently, what the prospects are for artificial intelligence and machine learning. They want to understand and then invest wisely. They are reasonably skeptical, having experienced overselling and under-delivery. They ask about reasonable and realistic expectations. Their concern is with the futurity of decisions they are currently entertaining. They cannot fully address this concern empirically. Thus, they need some way to make predictions. The problem is that one rarely can predict exactly what will happen, only what might happen. To overcome this limitation, executives can be provided predictions of possible futures and the conditions under which each scenario is likely to emerge. Models can help them to understand these possible futures. Most executives find such candor refreshing, perhaps even liberating. Their job becomes one of imagining and designing a portfolio of possible futures, assisted by interactive computational models. Understanding and managing uncertainty is central to their job. Indeed, doing this better than competitors is a hallmark of success. This book is intended to help them understand what fundamentally needs to be done, why it needs to be done, and how to do it. The hope is that readers will discuss this book and develop a “shared mental model” of computational modeling in the process, which will greatly enhance their chances of success.

Familienunternehmen und Personalmaßnahmen in Krisenphasen

2021 ◽  
Author(s):  
Daniel Ludwig
Keyword(s):  
Artificial Intelligence ◽  
Research Methods ◽  
Quantitative Research ◽  
Family Businesses ◽  
Research Assistant ◽  
Quantitative Research Methods ◽  
Personnel Practices ◽  
Advanced Analytics

This work examines family and non-family businesses and their use of personnel practices in times of crisis. The detailed questions that it addresses are, firstly, whether these types of businesses, in connection with crisis indicators, exert an influence on the use of personnel practices. Secondly, the study clarifies whether there are differences between family and non-family businesses and to what extent this is influenced by varying crisis indicators. The author previously worked as a research assistant, during which time, in addition to the topics covered in this work, he was primarily concerned with quantitative research methods. Since completing his dissertation, he has been working in the field of advanced analytics and artificial intelligence.

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