scholarly journals APPLICATION OF ARTIFICIAL INTELLIGENCE (AI) TO ASSESS THE ROLE OF COVID-19 LOCKDOWN IN THE DOMAIN OF ESTUARINE ACIDIFICATION

2021 ◽  
Vol 16 (12) ◽  
Author(s):  
Sitangshu Roy
Keyword(s):  
Artificial Intelligence ◽  
Computer Science ◽  
Bay Of Bengal ◽  
Ground Zero ◽  
Data Set ◽  
Estuarine Acidification

The branch of computer science that deals with the simulation of variables with the help of a computer are termed Artificial Intelligence (AI). Here we attempt to predict the pace of acidification in the Digha coast of the Bay of Bengal based on available datasets of more than three decades. The ground zero observation on the data set reveals a decreasing trend of pH since 1984 with a sudden hike in premonsoon 2020, the period coinciding with the COVID 19 lockdown phase in the Indian sub-continent.

scholarly journals Prioritizing and Analyzing the Role of Climate and Urban Parameters in the Confirmed Cases of COVID-19 Based on Artificial Intelligence Applications

2020 ◽  
Vol 17 (10) ◽  
pp. 3730 ◽  
Author(s):  
Sina Shaffiee Haghshenas ◽  
Behrouz Pirouz ◽  
Sami Shaffiee Haghshenas ◽  
Behzad Pirouz ◽  
Patrizia Piro ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Infectious Disease ◽  
Relative Humidity ◽  
Cost Function ◽  
Selection Process ◽  
Environmental Parameters ◽  
Pso Algorithm ◽  
Data Set ◽  
De Algorithm

Nowadays, an infectious disease outbreak is considered one of the most destructive effects in the sustainable development process. The outbreak of new coronavirus (COVID-19) as an infectious disease showed that it has undesirable social, environmental, and economic impacts, and leads to serious challenges and threats. Additionally, investigating the prioritization parameters is of vital importance to reducing the negative impacts of this global crisis. Hence, the main aim of this study is to prioritize and analyze the role of certain environmental parameters. For this purpose, four cities in Italy were selected as a case study and some notable climate parameters—such as daily average temperature, relative humidity, wind speed—and an urban parameter, population density, were considered as input data set, with confirmed cases of COVID-19 being the output dataset. In this paper, two artificial intelligence techniques, including an artificial neural network (ANN) based on particle swarm optimization (PSO) algorithm and differential evolution (DE) algorithm, were used for prioritizing climate and urban parameters. The analysis is based on the feature selection process and then the obtained results from the proposed models compared to select the best one. Finally, the difference in cost function was about 0.0001 between the performances of the two models, hence, the two methods were not different in cost function, however, ANN-PSO was found to be better, because it reached to the desired precision level in lesser iterations than ANN-DE. In addition, the priority of two variables, urban parameter, and relative humidity, were the highest to predict the confirmed cases of COVID-19.

Applications of AI in Financial System

2017 ◽  
pp. 101-109
Author(s):  
Santosh Kumar ◽  
Roopali Sharma
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Decision Analysis ◽  
Computer Science ◽  
Investment Decision ◽  
Analysis Tool ◽  
Changing Environment ◽  
Human Interference ◽  
Applications Of Ai

Role of computers are widely accepted and well known in the domain of Finance. Artificial Intelligence(AI) methods are extensively used in field of computer science for providing solution of unpredictable event in a frequent changing environment with utilization of neural network. Professionals are using AI framework into every field for reducing human interference to get better result from few decades. The main objective of the chapter is to point out the techniques of AI utilized in field of finance in broader perspective. The purpose of this chapter is to analyze the background of AI in finance and its role in Finance Market mainly as investment decision analysis tool.

Conclusion

2021 ◽  
pp. 127-132
Author(s):  
Simone Natale
Keyword(s):  
Artificial Intelligence ◽  
Social Media ◽  
Computer Science ◽  
Interface Design ◽  
External World ◽  
The Social ◽  
Social Meanings ◽  
Computer Scientists ◽  
Historical Trajectory

The historical trajectory examined in this book demonstrates that humans’ reactions to machines that are programmed to simulate intelligent behaviors represent a constitutive element of what is commonly called AI. Artificial intelligence technologies are not just designed to interact with human users: they are designed to fit specific characteristics of the ways users perceive and navigate the external world. Communicative AI becomes more effective not only by evolving from a technical standpoint but also by profiting, through the dynamics of banal deception, from the social meanings humans project onto situations and things. In this conclusion, the risks and problems related to AI’s banal deception are explored in relationship with other AI-based technologies such as robotics and social media bots. A call is made for initiating a more serious debate about the role of deception in interface design and computer science. The book concludes with a reflection on the need to develop a critical and skeptical stance in interactions with computing technologies and AI. In order not to be found unprepared for the challenges posed by AI, computer scientists, software developers, designers as well as users have to consider and critically interrogate the potential outcomes of banal deception.

scholarly journals Artificial Intelligence Competencies for Data Science Undergraduate Curricula

2019 ◽  
Vol 33 ◽  
pp. 9746-9747
Author(s):  
Andrea Danyluk ◽  
Scott Buck
Keyword(s):  
Artificial Intelligence ◽  
Computer Science ◽  
Data Science ◽  
Task Force ◽  
Undergraduate Curriculum ◽  
Short Paper ◽  
Undergraduate Level ◽  
Programs Of Study

In August 2017, the ACM Education Council initiated a task force to add to the broad, interdisciplinary conversation on data science, with an articulation of the role of computing discipline-specific contributions to this emerging field. Specifically, the task force is seeking to define what the computing contributions are to this new field, in order to provide guidance for computer science or similar departments offering data science programs of study at the undergraduate level. The ACM Data Science Task Force has completed the initial draft of a curricular report. The computing-knowledge areas identified in the report are drawn from across computing disciplines and include several sub-areas of AI. This short paper describes the overall project, highlights AI-relevant areas, and seeks to open a dialog about the AI competencies that are to be considered central to a data science undergraduate curriculum.

Applications of AI in Financial System

2020 ◽  
pp. 23-30 ◽  
Author(s):  
Santosh Kumar ◽  
Roopali Sharma
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Decision Analysis ◽  
Computer Science ◽  
Investment Decision ◽  
Analysis Tool ◽  
Changing Environment ◽  
Human Interference ◽  
Applications Of Ai

Role of computers are widely accepted and well known in the domain of Finance. Artificial Intelligence(AI) methods are extensively used in field of computer science for providing solution of unpredictable event in a frequent changing environment with utilization of neural network. Professionals are using AI framework into every field for reducing human interference to get better result from few decades. The main objective of the chapter is to point out the techniques of AI utilized in field of finance in broader perspective. The purpose of this chapter is to analyze the background of AI in finance and its role in Finance Market mainly as investment decision analysis tool.

Management of Economics and State "Bottom"

2020 ◽  
Vol 17 (6) ◽  
pp. 76-91
Author(s):  
E. D. Solozhentsev
Keyword(s):  
Quality Of Life ◽  
Artificial Intelligence ◽  
Probabilistic Models ◽  
Human Life ◽  
Special Software ◽  
Human Quality ◽  
Relationship Of ◽  
The Relationship

The scientific problem of economics “Managing the quality of human life” is formulated on the basis of artificial intelligence, algebra of logic and logical-probabilistic calculus. Managing the quality of human life is represented by managing the processes of his treatment, training and decision making. Events in these processes and the corresponding logical variables relate to the behavior of a person, other persons and infrastructure. The processes of the quality of human life are modeled, analyzed and managed with the participation of the person himself. Scenarios and structural, logical and probabilistic models of managing the quality of human life are given. Special software for quality management is described. The relationship of human quality of life and the digital economy is examined. We consider the role of public opinion in the management of the “bottom” based on the synthesis of many studies on the management of the economics and the state. The bottom management is also feedback from the top management.

Artificial intelligence and the management transformation

2020 ◽  
Vol 16 (4) ◽  
pp. 600-612
Author(s):  
L.F. Nikulin ◽  
V.V. Velikorossov ◽  
S.A. Filin ◽  
A.B. Lanchakov
Keyword(s):  
Artificial Intelligence ◽  
Social Life ◽  
Soft Power ◽  
Process Integration ◽  
Management Practice ◽  
Scientific School ◽  
Strategic Culture ◽  
Analysis And Synthesis ◽  
And Training

Subject. The article discusses how management transforms as artificial intelligence gets more important in governance, production and social life. Objectives. We identify and substantiate trends in management transformation as artificial intelligence evolves and gets more important in governance, production and social life. The article also provides our suggestions for management and training of managers dealing with artificial intelligence. Methods. The study employs methods of logic research, analysis and synthesis through the systems and creative approach, methodology of technological waves. Results. We analyzed the scope of management as is and found that threats and global challenges escalate due to the advent of artificial intelligence. We provide the rationale for recognizing the strategic culture as the self-organizing system of business process integration. We suggest and substantiate the concept of soft power with reference to strategic culture, which should be raised, inter alia, through the scientific school of conflict studies. We give our recommendations on how management and training of managers should be improved in dealing with artificial intelligence as it evolves. The novelty hereof is that we trace trends in management transformation as the role of artificial intelligence evolves and growth in governance, production and social life. Conclusions and Relevance. Generic solutions are not very effective for the Russian management practice during the transition to the sixth and seventh waves of innovation. Any programming product represents artificial intelligence, which simulates a personality very well, though unable to substitute a manager in motivating, governing and interacting with people.

Exchange Spin Coupling from Gaussian Process Regression

2020 ◽  
Author(s):  
Marc Philipp Bahlke ◽  
Natnael Mogos ◽  
Jonny Proppe ◽  
Carmen Herrmann
Keyword(s):  
Machine Learning ◽  
Gaussian Process ◽  
Gaussian Process Regression ◽  
Molecular Magnets ◽  
Molecular Structures ◽  
Spin Coupling ◽  
Structure Property ◽  
Data Set ◽  
Uncertainty Estimates

Heisenberg exchange spin coupling between metal centers is essential for describing and understanding the electronic structure of many molecular catalysts, metalloenzymes, and molecular magnets for potential application in information technology. We explore the machine-learnability of exchange spin coupling, which has not been studied yet. We employ Gaussian process regression since it can potentially deal with small training sets (as likely associated with the rather complex molecular structures required for exploring spin coupling) and since it provides uncertainty estimates (“error bars”) along with predicted values. We compare a range of descriptors and kernels for 257 small dicopper complexes and find that a simple descriptor based on chemical intuition, consisting only of copper-bridge angles and copper-copper distances, clearly outperforms several more sophisticated descriptors when it comes to extrapolating towards larger experimentally relevant complexes. Exchange spin coupling is similarly easy to learn as the polarizability, while learning dipole moments is much harder. The strength of the sophisticated descriptors lies in their ability to linearize structure-property relationships, to the point that a simple linear ridge regression performs just as well as the kernel-based machine-learning model for our small dicopper data set. The superior extrapolation performance of the simple descriptor is unique to exchange spin coupling, reinforcing the crucial role of choosing a suitable descriptor, and highlighting the interesting question of the role of chemical intuition vs. systematic or automated selection of features for machine learning in chemistry and material science.

The Role of Theories of Embodied Cognition in Research and Modeling of Emotions

2019 ◽  
Vol 62 (5) ◽  
pp. 124-138
Author(s):  
Alexandra V. Shiller
Keyword(s):  
Artificial Intelligence ◽  
Embodied Cognition ◽  
Mirror Neurons ◽  
Empirical Studies ◽  
Unknown Quantity ◽  
Emotional Processes ◽  
Strong Artificial Intelligence ◽  
European Philosophy ◽  
Postmodern Philosophy

The article analyzes the role of theories of embodied cognition for the development of emotion research. The role and position of emotions changed as philosophy developed. In classical and modern European philosophy, the idea of the “primacy of reason” prevailed over emotions and physicality, emotions and affective life were described as low-ranking phenomena regarding cognitive processes or were completely eliminated as an unknown quantity. In postmodern philosophy, attention focuses on physicality and sensuality, which are rated higher than rational principle, mind and intelligence. Within the framework of this approach, there is a recently emerged theory of embodied cognition, which allows to take a fresh look at the place of emotions in the architecture of mental processes – thinking, perception, memory, imagination, speech. The article describes and analyzes a number of empirical studies showing the impossibility of excluding emotional processes and the significance of their research for understanding the architecture of embodied cognition. However, the features of the architecture of embodied cognition remain unclear, and some of the discoveries of recent years (mirror neurons or neurons of simulation) rather raise new questions and require further research. The rigorously described and clear architecture of the embodied cognition can grow the theoretical basis that will allow to advance the studies of learning processes, language understanding, psychotherapy techniques, social attitudes and stereotypes, highlight the riddle of consciousness and create new theories of consciousness or even create an anthropomorphic artificial intelligence that is close to “strong artificial intelligence.”

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