Usage Of Intelligence Research Articles

AESTHETICS OF DEEPFAKE ‒ SPHERE OF ART AND ENTERTAINMENT INDUSTRY

The usage of artificial intelligence is one of the main characteristics of contemporary society. Deepfake is one among other forms of AI that uses artificial intelligence called deep learning to make images of fake events. This technology is not just about videos it is about photos and audio, too. It could be applied in different areas such as education, health care, art, commercials, film, propaganda, etc. Authors are interested in deep fakes used in the art and entertainment industry and their effects on audiences and aesthetics. The paper aims to show some characteristics of the aesthetics of deepfake in the context of the contemporary art and entertainment industry. By focusing on the aesthetics of contemporary society, we try to make an aesthetics analysis of deepfakes (Case study 1‒ Wearing Gillian, Gillian Wearing, 2018, Case study 2 ‒ Dali Lives, The Salvador Dali Museum, 2019) to show that contemporary art is more intimate with audience, thanks to usage of AI; also engagement of people is bigger than in traditional art. The conclusion is that contemporary art remains in the entertainment industry. It looks popular and closer to an audience; also, these spheres have a common and main aesthetic value- entertainment.

Smart Agriculture: Technologies, Practices, and Future Directions

The Internet of Things (IoT) has ushered in a new era of innovative agriculture research. Because IoT is still in its early stages, it must be widely tested before it can be widely deployed in many agricultural applications. In this paper, I look at different prospective IoT applications, as well as the unique concerns and constraints connected with IoT deployment for better farming. The gadgets and wireless communication technologies linked with IoT in agricultural and farming applications are thoroughly researched to focus on the unique requirements. Sensor-enabled IoT systems that deliver intelligent and smart services for smart agriculture are being investigated.
 Several case studies are offered to investigate the existing IoT-based solutions implemented by various organizations, individuals, and groups depending on their deployment criteria. The difficulties in these solutions are addressed, as are the factors for improvement and the future roadmap of work with IoT. Smart farming is a trend that emphasizes the use of information and communications technology (ICT) in machinery, equipment, and sensors in network-based hi-tech farm supervision cycles. Innovative technologies such as the Internet of Things (IoT) and cloud computing are expected to spur growth and kickstart the usage of robotics and artificial intelligence in agriculture. Such radical departures are upsetting established agricultural practices while also posing several obstacles. This study explores the techniques and equipment utilized in wireless sensor applications in IoT agriculture, as well as the predicted problems encountered when integrating technology with traditional farming practices. Furthermore, this technical knowledge is useful to growers during crop times ranging from planting to harvest, and applications in packing and transportation are being researched.

Unlocking potential: The impact of AI on education technology

According to several international journals, artificial intelligence in education (AIET) is a more recent field in the educational sector. Even though it has been there for close to 30 years, educators are still confused about how to utilize it pedagogically on a larger scale and how it may have a substantial impact on teaching and learning as per SDG-4 Indicator 4.4.1, which tracks the proportion of educators and academia with the necessary information technology skills, putting them on the road to better employment and understanding Education 4.0. This article postulates a review of the impacts of AI in education and briefs the number of published studies in the area of AI in education, which has expanded as a result of the growing usage of artificial intelligence (AI) technology in education. However, extensive evaluations have been conducted to fully study the numerous facets of this topic. This study seeks to address this gap by utilizing PRISMA to detect trends and issues relevant to AI applications in education (AIET) based on publications from 2000 to 2022. The review's findings show that the academic community is becoming more interested in applying AI to education. The primary research questions covered in this study are those related to the origin: Rise in AI, Importance, and Impact of AI on Education Technology, as well as related areas such as intelligent tutoring systems for education AI challenges in the education sector, and future scope of AI and ChatGPT-3 in higher education.

A quick look at the recent advances, current state of utilization and expected future usage of artificial intelligence (AI) in the global textile manufacturing industry

A significant part of the current textile manufacturing industry around the world is managed and governed by individuals who are not sufficiently trained in information technology. While future textile engineers and technologists may come out sufficiently equipped to understand IT and its implications to the textile manufacturing industry, those running the industry today can benefit through simple elaboration of potentially useful IT tools and the many benefits they offer to the textile industry. This is especially true in the case of technologies that surfaced within the last two decades and are already making a sizable impact on products, production processes and the bottom lines of manufacturing industries. Artificial intelligence (AI) and related technologies fall under the category of rapidly emerging technologies that carry the potential to significantly re-shape the global manufacturing and service industries. This paper makes an attempt to describe these technologies and their potential benefits in such a way that textile industry leaders who are not IT experts can understand them to the extent of driving themselves to enthusiastically adopt them.

Mechanical intelligence simplifies control in terrestrial limbless locomotion.

Limbless locomotors, from microscopic worms to macroscopic snakes, traverse complex, heterogeneous natural environments typically using undulatory body wave propagation. Theoretical and robophysical models typically emphasize body kinematics and active neural/electronic control. However, we contend that because such approaches often neglect the role of passive, mechanically controlled processes (those involving "mechanical intelligence"), they fail to reproduce the performance of even the simplest organisms. To uncover principles of how mechanical intelligence aids limbless locomotion in heterogeneous terradynamic regimes, here we conduct a comparative study of locomotion in a model of heterogeneous terrain (lattices of rigid posts). We used a model biological system, the highly studied nematode worm Caenorhabditis elegans, and a robophysical device whose bilateral actuator morphology models that of limbless organisms across scales. The robot's kinematics quantitatively reproduced the performance of the nematodes with purely open-loop control; mechanical intelligence simplified control of obstacle navigation and exploitation by reducing the need for active sensing and feedback. An active behavior observed in C. elegans, undulatory wave reversal upon head collisions, robustified locomotion via exploitation of the systems' mechanical intelligence. Our study provides insights into how neurally simple limbless organisms like nematodes can leverage mechanical intelligence via appropriately tuned bilateral actuation to locomote in complex environments. These principles likely apply to neurally more sophisticated organisms and also provide a design and control paradigm for limbless robots for applications like search and rescue and planetary exploration.

Artificial Intelligence Usage in Higher Education: Academicians' Perspective

Artificial Intelligence Usage in Higher Education: Academicians' Perspective

Prospects for the introduction, usage and responsibility of artificial intelligence in the EU and Ukraine

The development of artificial intelligence and its significant role in economic and social relations, military and cyber threats generated by it indicate the urgency of researching this problem. Ukraine, as a victim of russian large-scale military aggression in 2022, is interested in regulating this area in order to neutralize threats in military and cyberspace.
 The study of the introduction, usage and responsibility of artificial intelligence in the European Union can provide vectors of criminal responsibility of individuals, legal entities, as well as states that implement them in peacetime or wartime with a criminal (terrorist) purpose. An important issue in this study is the possible implementation of artificial intelligence as a tool for criminal justice agencies. The European Commission, taking into account the growing use of artificial intelligence in the European Union, formulated its definition in 2018. In 2020, Ukraine also adopted the Concept of the Development of Artificial Intelligence. However, the fact of harmonization of the legislation of the EU and Ukraine in this area becomes obvious.
 The European Commission's work on artificial intelligence is reflected in the 2018 AI Strategy for Europe, the 2020 White Paper on AI and the recently updated Coordinated Plan on Artificial Intelligence. The preparation of the Artificail Intelligence Act is also underway.
 Analysis of the regulatory framework and positions regarding the implementation, usage and responsibility of artificial intelligence indicate the following trends: 1) the use of artificial intelligence in the European Union is becoming a regulated area that shapes the rights, duties and responsibilities of participants; 2) the usage of artificial intelligence in criminal justice agencies is subject to significant restrictions and prohibitions; 3) responsibility for the use of artificial intelligence and for the dangerous consequences that may be caused by it rests with individuals and legal entities, as well as states, in whose interests it is used.

Peculiarities of the objective side of the failure of the declarant to submit a declaration of a person authorized to perform the functions of the state or local self-government

Peculiarities of the objective side of the failure of the declarant to submit a declaration of a person authorized to perform the functions of the state or local self-government

Legal support of the use of Industry 4.0 technologies in the field of natural resource management and environmental protection

Legal support of the use of Industry 4.0 technologies in the field of natural resource management and environmental protection

Towards Legal Regulations of Generative AI in the Creative Industry

Objective: this article aims to answer the following questions: 1. Can generative artificial intelligence be a subject of copyright law? 2. What risks the unregulated use of generative artificial intelligence systems can cause? 3. What legal gaps should be filled in to minimize such risks?Methods: comparative legal analysis, sociological method, concrete sociological method, quantitative data analysis, qualitative data analysis, statistical analysis, case study, induction, deduction.Results: the authors identified several risks of the unregulated usage of generative artificial intelligence in the creative industry, among which are: violation of copyright and labor law, violation of consumers rights and the rise of public distrust in government. They suggest that a prompt development of new legal norms can minimize these risks. In conclusion, the article constants that states have already begun to realize that the negative impact of generative artificial intelligence on the creative industry must not be ignored, hence the development of similar legal regulations in states with completely different regimes.Scientific novelty: the article provides a comprehensive study of the impact of generative artificial intelligence on the creative industry from two perspectives: the perspective of law and the perspective of the industry. The empirical basis of it consists of two international surveys and an expert opinion of a representative of the industry. This approach allowed the authors to improve the objectivity of their research and to obtain results that can be used for finding a practical solution for the identified risks. The problem of the ongoing development and popularization of generative artificial intelligence systems goes beyond the question “who is the author?” therefore, it needs to be solved by introduction of other than the already existing mechanisms and regulations - this point of view is supported not only by the results of the surveys but also by the analysis of current lawsuits against developers of generative artificial intelligence systems.Practical significance: the obtained results can be used to fasten the development of universal legal rules, regulations, instruments and standards, the current lack of which poses a threat not only to human rights, but also to several sectors within the creative industry and beyond.

Aligning community outreach initiatives with SDGs in a higher education institution with artificial intelligence

PurposeConsidering the role of community outreach of a Higher Education Institution (HEI) in promoting sustainable regional development, based on the objectives of the UN 2030 Agenda, the present study aims to verify, with the usage of an Artificial Intelligence (AI) tool, the alignment of community outreach actions of an HEI to the SDGs and identify its actions with the greatest impact. Design/methodology/approachThe study is descriptive through a case study at a university in Brazil. Documentary analysis was carried out using data on more than 15,000 community outreach projects developed from 2009 to 2022, using natural language processing (NLP). In addition to the descriptive aspects, combining NLP with statistical techniques allowed us to discuss the alignment between community outreach projects and the SDGs from a longitudinal perspective. FindingsThe results demonstrated that the main SDGs in community outreach actions are SDG 17: Partnerships and Means of Implementation; SDG 4: Quality Education; SDG 12: Sustainable Consumption and Production and SDG 8: Decent Work and Economic Growth. These results are prominent because community outreach aims to establish a dialogical relationship between society and the university, conceiving the exchange of knowledge based on the actions developed and sharing knowledge with those involved in community extension. OriginalityThe use of AI technologies to identify and monitor data on community outreach actions in HEI towards the SDGs, and to propose ways to share this information with internal and external stakeholders of the institution.

AI Generated Music

In last few years we noticed that the usage of artificial intelligence growing very fast which is implemented in the photography, videography, computer vision and many Moe topics which we can’t explain in this paper but the point is AI is used everywhere. AI music generation is on of them in which we generate music through the AI with the help of machine learning models, we can generate music with the integration of AI generated music composition, emotional analysis, music generation algorithms, culture and genre exploration, purpose of music, music recommendations, copyright and ethical consideration, neuroscience, education and creativity, public perception. Our research paper is for the best music generation for the listeners of emotional music, cultural music and who wants the different music quality and quantity apart from the copyright issues.

Scientometric analysis on the use of ChatGPT, artificial intelligence, or intelligent conversational agent in the role of medical training

IntroductionIn recent times, there has been a noticeable surge in the usage of artificial intelligence, including ChatGPT and other types, in the field of health sciences education. In this regard, an exploratory bibliometric study was carried out to examine the utilization of smart conversational agents, ChatGPT, and artificial intelligence bots in medical education. MethodsA retrospective, observational, cross-sectional bibliometric analysis was employed to assess the scientific publications listed in Scopus. This study was conducted on March 11, 2023 in search for information in Scopus. A total of 220 relevant documents were identified that were available in the Scopus database during the period between 2017 and 2022. Elsevier's SciVal software was used. Subsequently, statistical tables and graphs were prepared for presentation in Bibliometrix software. ResultsAmong the authors, Timothy W. Bickmore, from the United States, has the highest number of publications (10) and citations received (172), and an h-index of 45, suggesting a significant influence in the field of study. The subcategory with the highest academic output is Health Informatics with 133 publications, while Geriatrics and Gerontology has the least with only 3. Most of the analyzed publications (44.2%) originated from collaborations within the same country. Notably, the Swiss Federal Institute of Technology Zurich and Imperial College London stood out with 12 publications each that received over 200 citations indicating their significant impact on their respective fields. Despite having the highest number of academic publications (15), Brazil had a relatively low field-weighted citation impact (0.64) and received the lowest number of citations (81). A clustering analysis was performed on a sample of 10 concepts using 2 dimensions. The results indicated that all terms were part of the same cluster. Notably, the terms 'conversational agents', 'chatbots', 'conversational agent', and 'chatbot' were closely related. ConclusionsIt was found that the American Bickmore, Timothy W., led the top-10 researchers, and that the Health Informatics subject area was the most predominant. However, Brazil and Germany were the leading countries in terms of research output that was mainly published in high impact journals (Q1).

I am therefore, I do: a fit perspective of decision-making styles and business intelligence usage

ABSTRACT Individual differences affect how Business Intelligence (BI) systems are used and utilised. Decision-making styles which were regarded as learned habits of how individuals make a decision were believed to be described by two main important aspects including information use and focus are chosen as individual differences in this research. Two view of fit were drawn from the theory to explain how individual differences predict BI usage; Fit as Matching and Fit as Moderation. A total of 122 valid responses were collected. The results of empirical data analyses show that only the rational decision-making style and BI usage is found to be fit as matching. When taking a fit perspective as moderating, the analyses show interesting results. Computer self-efficacy was found to positively moderate the relationship between the avoidant decision-making style and BI usage. Task equivocality was also found to positively moderate the relationship between the spontaneous decision-making style and BI usage. The findings imply different alternative actions for organisation to motivate the use of BI system for individuals with different decision-making styles.

Examining The Attitudes of E-Sports Players Towards Artificial Intelligence Techologies

This study aimed to examine the attitudes of e-sports participants toward artificial intelligence (AI) based on a variety of socio-demographic variables. A total of 206 e-sports participants selected through convenience sampling were administered the "Attitude Towards Artificial Intelligence Scale" adapted by Kaya et al. (2022). SPSS 29.0.1.0 (171) was used to analyse the data. For data analysis, the Whitney U and Kruskal Wallis tests were utilized. According to the results of the analysis, there was no significant difference in the age variable, whereas the gender variable produced results that favoured male e-sports participants. In addition, it was discovered that individuals who used technological devices during exercise more frequently had a more positive attitude towards AI. In conclusion, men participants have a more optimistic view of artificial intelligence than female participants. These results illustrate the connection between technology usage and perception of artificial intelligence. It can be hypothesized that individuals who frequently use technological devices during exercise are more conversant with technology and, as a result, have a more favourable attitude towards artificial intelligence. These results indicate that technology utilization influences the adoption and acceptance of AI technologies.

The impact of artificial intelligence systems in micropalaeontology

The discipline of micropalaeontology, fundamental in Geology, has witnessed substantial technological advancements in recent decades, aided by the exploitation of Artificial Intelligence (AI) systems to facilitate microfossil identification. This perspective paper explores the transformative role of AI in micropalaeontology, particularly in species identification, and its potential to help with the interpretation of microfossil assemblages. While it is argued that AI cannot fully replicate the expertise of a micropalaeontologist, an abundance of scientific studies shows the promising success of AI becoming adept at accurately identifying microfossil species.

Physician Entrepreneurs and AI Technology: An In-depth Study of Knowledge, Competence, Adoption, and Sustainability in the GCC Region

In recent years, the usage of artificial intelligence (AI) has grown significantly, and its implementation is now widespread across all industries worldwide. In terms of finances, the business sector is aware of the importance of AI in healthcare. Physician entrepreneurship is a familiar idea that has developed over time. Doctors who are also entrepreneurs have broadened their areas of expertise and taken on more primary clinical duties. This study aims to assess the knowledge, competency, adaptability, and sustainability of artificial intelligence (AI) technology among physician entrepreneurs in GCC nations. This study will focus on how AI technology is used in the healthcare industry.A sample of 220 respondents will be used in this study's survey. Out of the 220 participants, 152 males (69.09%) and68 females (30.9%) were included in the study. Based on the results of the structural equation model, competence, adaptability, and sustainability contribute to artificial intelligence and have a significant positive impact. After analyzing the interview responses, it is clear that incorporating AI into a company demands a considerable investment in employees, technology, and software. This study focused on how well physician entrepreneurs understand, use, and maintain artificial intelligence regarding knowledge, competency, adaptability, and sustainability. However, comparative research was conducted only for developed countries with similar or different settings.

Deciphering Academicians' Usage of Artificial Intelligence among Academicians in Higher Education Institutions

Deciphering Academicians' Usage of Artificial Intelligence among Academicians in Higher Education Institutions

AI and Machine Learning in Fintech Companies

The vast amount of data technology in organizations causes the need to understand the factors of how to use this data and for understanding. To make the most of the company's data there is a need to be an awareness of the latest trends and technology in the business analytics space. These predictions will help organizations prepare for the future of business analytics and stay agile. Technology disruption and dramatic shifts in consumer banking lay the basis for new banking S- curve business models, Further COVID-19 pandemic has accelerated these trends. This paper examines the Applications of Artificial Intelligence and Machine Learning, which are two related technologies that are playing a paramount role in Fintech companies in the present-day scenario. This paper explores the operational efficiency of Artificial Intelligence and Machine Learning capabilities and their future opportunities in Fintech Services. The present study adopts a conceptual Model. The study attempts to discover patterns in the usage and effectiveness of Artificial Intelligence and Machine Learning capabilities in FinTech Companies. The major implication of the research is fraud detection where data and machine learning an analytical solution can be embedded in the operational process and automatically isolate or minimize financial fraud. Artificial Intelligence and Machine learning help FinTech companies to detect sub spinous incidents instantaneously and expedite the time to respond. In addition, the applications of Artificial Intelligence and Machine Learning lead to operational efficiency in Fintech companies.

Indigenous and Disruptive Remote Patient Monitoring Devices - A Case Study on AI in Healthcare

The evolution of Industry 4.0 technologies has facilitated the growth of technologically driven healthcare solutions, disrupting, and significantly challenging the way the sector works and moving towards Healthcare 4.0. The global interest in Artificial Intelligence (AI) in the healthcare sector is increasing tremendously in comparison to other sectors. A rapidly ageing population with increasing health complications has led to the rise of AI-driven Remote Patient Monitoring (RPM) devices, where a patient can be monitored in the comfort of a home, using the latest communication and sensor technologies. This study aims to understand the usage of Artificial Intelligence (AI) as a healthcare disruptor, capturing the ever-increasing demands concerning the remote patient monitoring industry, making huge improvements, and redefining the way how healthcare can be provided, for timely and cost-effective solutions. The analysis of these remote monitoring devices has been done through a case study approach. For this purpose, two AI-enabled remote patient monitoring devices Dozee.ai and Qure.ai, have been taken which have been assisting patients and doctors in the diagnosis of health vitals remotely. Data has been taken from secondary sources to analyze the concept of indigenous and disruptive innovations. Both the apps have been quite successful in their diagnosis of Covid positive patients and have assisted both patients and healthcare personnel during critical times. Despite the huge advantages of AI-enabled RPM devices, they are vulnerable to data hacking and privacy issues. Any errors in these devices can pose potential risks to patients’ health.