Research on the strategy of intelligent analysis to improve sports person psychological experience in the era of artificial intelligence

Artificial intelligence (AI) is an excellent potential technology that is evolving day-to-day and a critical avenue for exploration in the world of computer science & engineering. Owing to the vast volume of data and the eventual need to turn this data into usable knowledge and realistic solutions, artificial intelligence approaches and methods have gained substantial prominence in the knowledge economy and community world in general. AI revolutionizes and raises athletics to an entirely different level. Although it is clear that analytics and predictive research have long played a vital role in sports, AI has a massive effect on how games are played, structured, and engaged by the public. Apart from these, AI helps to analyze the mental stability of the athletes. This research proposes the Artificial Intelligence assisted Effective Monitoring System (AIEMS) for the specific intelligent analysis of sports people’s psychological experience. The comparative analysis suggests the best AI strategies for analyzing mental stability using different criteria and resource factors. It is observed that the growth in the present incarnation indicates a promising future concerning AI use in elite athletes. The study ends with the predictive efficiency of particular AI approaches and procedures for further predictive analysis focused on retrospective methods. The experimental results show that the proposed AIEMS model enhances the athlete performance ratio of 98.8%, emotion state prediction of 95.7%, accuracy ratio of 97.3%, perception level of 98.1%, and reduces the anxiety and depression level of 15.4% compared to other existing models.

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Towards a Customized¬ Awareness Campaign to Educate the Public about COVID-19: Development and Validation of a Messaging Campaign to Promote Precautionary Behavior Using Geospatial Intelligence in Saudi Arabia (Preprint)

10.2196/preprints.26856 ◽

2020 ◽

Author(s):

Mayda Alrige ◽

Hind Bitar Bitar ◽

Maram Meccawi ◽

Balakrishnan Mullachery

Keyword(s):

Artificial Intelligence ◽

Saudi Arabia ◽

Content Validity ◽

Awareness Campaign ◽

Artificial Intelligence Technique ◽

The Public ◽

High Infection ◽

Local Map ◽

The City ◽

Intelligence Technique

BACKGROUND Designing a health promotion campaign is never an easy task, especially during a pandemic of a highly infectious disease, such as Covid-19. In Saudi Arabia, many attempts have been made toward raising the public awareness about Covid-19 infection-level and its precautionary health measures that have to be taken. Although this is useful, most of the health information delivered through the national dashboard and the awareness campaign are very generic and not necessarily make the impact we like to see on individuals’ behavior. OBJECTIVE The objective of this study is to build and validate a customized awareness campaign to promote precautionary health behavior during the COVID-19 pandemic. The customization is realized by utilizing a geospatial artificial intelligence technique called Space-Time Cube (STC) technique. METHODS This research has been conducted in two sequential phases. In the first phase, an initial library of thirty-two messages was developed and validated to promote precautionary messages during the COVID-19 pandemic. This phase was guided by the Fogg Behavior Model (FBM) for behavior change. In phase 2, we applied STC as a Geospatial Artificial Intelligence technique to create a local map for one city representing three different profiles for the city districts. The model was built using COVID-19 clinical data. RESULTS Thirty-two messages were developed based on resources from the World Health Organization and the Ministry of Health in Saudi Arabia. The enumerated content validity of the messages was established through the utilization of Content Validity Index (CVI). Thirty-two messages were found to have acceptable content validity (I-CVI=.87). The geospatial intelligence technique that we used showed three profiles for the districts of Jeddah city: one for high infection, another for moderate infection, and the third for low infection. Combining the results from the first and second phases, a customized awareness campaign was created. This awareness campaign would be used to educate the public regarding the precautionary health behaviors that should be taken, and hence help in reducing the number of positive cases in the city of Jeddah. CONCLUSIONS This research delineates the two main phases to developing a health awareness messaging campaign. The messaging campaign, grounded in FBM, was customized by utilizing Geospatial Artificial Intelligence to create a local map with three district profiles: high-infection, moderate-infection, and low-infection. Locals of each district will be targeted by the campaign based on the level of infection in their district as well as other shared characteristics. Customizing health messages is very prominent in health communication research. This research provides a legitimate approach to customize health messages during the pandemic of COVID-19.

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Living machines in our cultural imagination

10.1093/oso/9780199674923.003.0061 ◽

2018 ◽

Author(s):

Michael Szollosy

Keyword(s):

Artificial Intelligence ◽

Science Fiction ◽

Public Perceptions ◽

Human Condition ◽

Cultural Imagination ◽

The Public ◽

The Enlightenment ◽

The Future ◽

Public Imagination ◽

The Human Condition

Public perceptions of robots and artificial intelligence (AI)—both positive and negative—are hopelessly misinformed, based far too much on science fiction rather than science fact. However, these fictions can be instructive, and reveal to us important anxieties that exist in the public imagination, both towards robots and AI and about the human condition more generally. These anxieties are based on little-understood processes (such as anthropomorphization and projection), but cannot be dismissed merely as inaccuracies in need of correction. Our demonization of robots and AI illustrate two-hundred-year-old fears about the consequences of the Enlightenment and industrialization. Idealistic hopes projected onto robots and AI, in contrast, reveal other anxieties, about our mortality—and the transhumanist desire to transcend the limitations of our physical bodies—and about the future of our species. This chapter reviews these issues and considers some of their broader implications for our future lives with living machines.

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Radiology Community Attitude in Saudi Arabia about the Applications of Artificial Intelligence in Radiology

Healthcare ◽

10.3390/healthcare9070834 ◽

2021 ◽

Vol 9 (7) ◽

pp. 834

Author(s):

Magbool Alelyani ◽

Sultan Alamri ◽

Mohammed S. Alqahtani ◽

Alamin Musa ◽

Hajar Almater ◽

...

Keyword(s):

Artificial Intelligence ◽

Saudi Arabia ◽

Vital Role ◽

Human Machine Interaction ◽

The Future ◽

Level Of Knowledge ◽

Electronic Questionnaires ◽

Machine Interaction ◽

Applications Of Ai

Artificial intelligence (AI) is a broad, umbrella term that encompasses the theory and development of computer systems able to perform tasks normally requiring human intelligence. The aim of this study is to assess the radiology community’s attitude in Saudi Arabia toward the applications of AI. Methods: Data for this study were collected using electronic questionnaires in 2019 and 2020. The study included a total of 714 participants. Data analysis was performed using SPSS Statistics (version 25). Results: The majority of the participants (61.2%) had read or heard about the role of AI in radiology. We also found that radiologists had statistically different responses and tended to read more about AI compared to all other specialists. In addition, 82% of the participants thought that AI must be included in the curriculum of medical and allied health colleges, and 86% of the participants agreed that AI would be essential in the future. Even though human–machine interaction was considered to be one of the most important skills in the future, 89% of the participants thought that it would never replace radiologists. Conclusion: Because AI plays a vital role in radiology, it is important to ensure that radiologists and radiographers have at least a minimum understanding of the technology. Our finding shows an acceptable level of knowledge regarding AI technology and that AI applications should be included in the curriculum of the medical and health sciences colleges.

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Uncovering Prospective Role and Applications of Existing and New Nutraceuticals from Bacterial, Fungal, Algal and Cyanobacterial, and Plant Sources

Sustainability ◽

10.3390/su13073671 ◽

2021 ◽

Vol 13 (7) ◽

pp. 3671

Author(s):

Jameel R. Al-Obaidi ◽

Khalid H. Alobaidi ◽

Bilal Salim Al-Taie ◽

David Hong-Sheng Wee ◽

Hasnain Hussain ◽

...

Keyword(s):

Human Health ◽

Well Being ◽

Vital Role ◽

Biologically Active ◽

Future Perspective ◽

The Public ◽

Biological Sources ◽

Pharmaceutical Properties ◽

Plant Sources ◽

Health And Well Being

Nutraceuticals are a category of products more often associated with food but having pharmaceuticals property and characteristics. However, there is still no internationally accepted concept of these food-pharmaceutical properties, and their interpretation can differ from country to country. Nutraceuticals are used as part of dietary supplements in most countries. They can be phytochemicals which are biologically active and have health benefits. These can be supplied as a supplement and/or as a functional food to the customer. For human health and longevity, these materials are likely to play a vital role. Consumption of these items is typical without a therapeutic prescription and/or supervision by the vast majority of the public. The development of nutraceuticals can be achieved through many bioresources and organisms. This review article will discuss the current research on nutraceuticals from different biological sources and their potential use as an agent for improving human health and well-being, as well as the gaps and future perspective of research related to nutraceutical development.

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Artificial Intelligence: The Attitude of the Public and Representatives of Various Industries

Journal of Risk and Financial Management ◽

10.3390/jrfm14080339 ◽

2021 ◽

Vol 14 (8) ◽

pp. 339

Author(s):

Tatjana Vasiljeva ◽

Ilmars Kreituss ◽

Ilze Lulle

Keyword(s):

Artificial Intelligence ◽

Primary Data ◽

Structured Interviews ◽

The Public ◽

Qualitative And Quantitative ◽

Public Survey ◽

Significant Difference ◽

Main Factors ◽

Negative Factors ◽

Near Future

This paper looks at public and business attitudes towards artificial intelligence, examining the main factors that influence them. The conceptual model is based on the technology–organization–environment (TOE) framework and was tested through analysis of qualitative and quantitative data. Primary data were collected by a public survey with a questionnaire specially developed for the study and by semi-structured interviews with experts in the artificial intelligence field and management representatives from various companies. This study aims to evaluate the current attitudes of the public and employees of various industries towards AI and investigate the factors that affect them. It was discovered that attitude towards AI differs significantly among industries. There is a significant difference in attitude towards AI between employees at organizations with already implemented AI solutions and employees at organizations with no intention to implement them in the near future. The three main factors which have an impact on AI adoption in an organization are top management’s attitude, competition and regulations. After determining the main factors that influence the attitudes of society and companies towards artificial intelligence, recommendations are provided for reducing various negative factors. The authors develop a proposition that justifies the activities needed for successful adoption of innovative technologies.

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Prediction of Multi-Scalar Standardized Precipitation Index by Using Artificial Intelligence and Regression Models

Climate ◽

10.3390/cli9020028 ◽

2021 ◽

Vol 9 (2) ◽

pp. 28

Author(s):

Anurag Malik ◽

Anil Kumar ◽

Priya Rai ◽

Alban Kuriqi

Keyword(s):

Artificial Intelligence ◽

Fuzzy Inference ◽

Standardized Precipitation Index ◽

Meteorological Drought ◽

Vital Role ◽

Precipitation Index ◽

Visual Interpretation ◽

Inference System ◽

Drought Prediction ◽

Optimal Functioning

Accurate monitoring and forecasting of drought are crucial. They play a vital role in the optimal functioning of irrigation systems, risk management, drought readiness, and alleviation. In this work, Artificial Intelligence (AI) models, comprising Multi-layer Perceptron Neural Network (MLPNN) and Co-Active Neuro-Fuzzy Inference System (CANFIS), and regression, model including Multiple Linear Regression (MLR), were investigated for multi-scalar Standardized Precipitation Index (SPI) prediction in the Garhwal region of Uttarakhand State, India. The SPI was computed on six different scales, i.e., 1-, 3-, 6-, 9-, 12-, and 24-month, by deploying monthly rainfall information of available years. The significant lags as inputs for the MLPNN, CANFIS, and MLR models were obtained by utilizing Partial Autocorrelation Function (PACF) with a significant level equal to 5% for SPI-1, SPI-3, SPI-6, SPI-9, SPI-12, and SPI-24. The predicted multi-scalar SPI values utilizing the MLPNN, CANFIS, and MLR models were compared with calculated SPI of multi-time scales through different performance evaluation indicators and visual interpretation. The appraisals of results indicated that CANFIS performance was more reliable for drought prediction at Dehradun (3-, 6-, 9-, and 12-month scales), Chamoli and Tehri Garhwal (1-, 3-, 6-, 9-, and 12-month scales), Haridwar and Pauri Garhwal (1-, 3-, 6-, and 9-month scales), Rudraprayag (1-, 3-, and 6-month scales), and Uttarkashi (3-month scale) stations. The MLPNN model was best at Dehradun (1- and 24- month scales), Tehri Garhwal and Chamoli (24-month scale), Haridwar (12- and 24-month scales), Pauri Garhwal (12-month scale), Rudraprayag (9-, 12-, and 24-month), and Uttarkashi (1- and 6-month scales) stations, while the MLR model was found to be optimal at Pauri Garhwal (24-month scale) and Uttarkashi (9-, 12-, and 24-month scales) stations. Furthermore, the modeling approach can foster a straightforward and trustworthy expert intelligent mechanism for projecting multi-scalar SPI and decision making for remedial arrangements to tackle meteorological drought at the stations under study.

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How and where is artificial intelligence in the public sector going? A literature review and research agenda

Government Information Quarterly ◽

10.1016/j.giq.2019.07.004 ◽

2019 ◽

Vol 36 (4) ◽

pp. 101392 ◽

Cited By ~ 19

Author(s):

Weslei Gomes de Sousa ◽

Elis Regina Pereira de Melo ◽

Paulo Henrique De Souza Bermejo ◽

Rafael Araújo Sousa Farias ◽

Adalmir Oliveira Gomes

Keyword(s):

Artificial Intelligence ◽

Public Sector ◽

Literature Review ◽

Research Agenda ◽

The Public

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Autonomous vehicles: a review of the ethical, social and economic implications of the AI revolution

International Journal of Intelligent Unmanned Systems ◽

10.1108/ijius-07-2020-0027 ◽

2020 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Shweta Banerjee

Keyword(s):

Artificial Intelligence ◽

Autonomous Vehicles ◽

Design Methodology ◽

Technological Advancement ◽

Economic Implications ◽

Content Type ◽

The Public ◽

Autonomous Cars ◽

The Subject ◽

Practical Implications

PurposeThere are ethical, legal, social and economic arguments surrounding the subject of autonomous vehicles. This paper aims to discuss some of the arguments to communicate one of the current issues in the rising field of artificial intelligence.Design/methodology/approachMaking use of widely available literature that the author has read and summarised showcasing her viewpoints, the author shows that technology is progressing every day. Artificial intelligence and machine learning are at the forefront of technological advancement today. The manufacture and innovation of new machines have revolutionised our lives and resulted in a world where we are becoming increasingly dependent on artificial intelligence.FindingsTechnology might appear to be getting out of hand, but it can be effectively used to transform lives and convenience.Research limitations/implicationsFrom robotics to autonomous vehicles, countless technologies have and will continue to make the lives of individuals much easier. But, with these advancements also comes something called “future shock”.Practical implicationsFuture shock is the state of being unable to keep up with rapid social or technological change. As a result, the topic of artificial intelligence, and thus autonomous cars, is highly debated.Social implicationsThe study will be of interest to researchers, academics and the public in general. It will encourage further thinking.Originality/valueThis is an original piece of writing informed by reading several current pieces. The study has not been submitted elsewhere.

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The Application of Artificial Intelligence in Ocean Development: In the View of World Expo 2010

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.347-350.2335 ◽

2013 ◽

Vol 347-350 ◽

pp. 2335-2339

Author(s):

Yang Yu ◽

Zhen Xing Cheng

Keyword(s):

Artificial Intelligence ◽

Global Ocean ◽

Integration Platform ◽

The Public ◽

Network Expansion ◽

Traditional Research ◽

Artificial Intelligence Technology ◽

World Expo ◽

Function Integration ◽

Marine Applications

Under the background of global ocean development, artificial intelligence has increasing importance which urges the improvement of traditional research and exploration methods. Marine applications of artificial intelligence have been further practiced and expanded by Shanghai World Expo, which reflect in at least three major areas: firstly, the foundations of technical thought kernel, network expansion and intelligent navigation are laid in Maritime Internet of Things; secondly, in the field of far-reaching sea exploration, unmanned probe (deep-sea robot) relied on artificial intelligence technology has gradually become a major force in international competition; thirdly, as an ocean information and management comprehensive integration platform, digital ocean is applied to crack ocean information solitary island, jumbled information and other difficult problems through cooperation development, function integration and affinity services, enhancing the public ocean consciousness.

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Corporate Governance of Artificial Intelligence in the Public Interest

Information ◽

10.3390/info12070275 ◽

2021 ◽

Vol 12 (7) ◽

pp. 275

Author(s):

Peter Cihon ◽

Jonas Schuett ◽

Seth D. Baum

Keyword(s):

Artificial Intelligence ◽

Corporate Governance ◽

Law Enforcement ◽

Nonprofit Organizations ◽

Public Interest ◽

Department Of Defense ◽

The Public ◽

Wide Range ◽

The Media ◽

The U.S

Corporations play a major role in artificial intelligence (AI) research, development, and deployment, with profound consequences for society. This paper surveys opportunities to improve how corporations govern their AI activities so as to better advance the public interest. The paper focuses on the roles of and opportunities for a wide range of actors inside the corporation—managers, workers, and investors—and outside the corporation—corporate partners and competitors, industry consortia, nonprofit organizations, the public, the media, and governments. Whereas prior work on multistakeholder AI governance has proposed dedicated institutions to bring together diverse actors and stakeholders, this paper explores the opportunities they have even in the absence of dedicated multistakeholder institutions. The paper illustrates these opportunities with many cases, including the participation of Google in the U.S. Department of Defense Project Maven; the publication of potentially harmful AI research by OpenAI, with input from the Partnership on AI; and the sale of facial recognition technology to law enforcement by corporations including Amazon, IBM, and Microsoft. These and other cases demonstrate the wide range of mechanisms to advance AI corporate governance in the public interest, especially when diverse actors work together.

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