Artificial Intelligence Concepts Research Articles

Metaphor analysis on pre-service early childhood teachers’ conception of AI (Artificial Intelligence) education for young children

This study explored PEC teacher’ (pre-service early childhood teachers’) conception of AI (Artificial Intelligence) education for young children by using metaphor analysis. Through exploring the conceptual metaphors of AI education for young children with 137 undergraduate students majoring in ECE (early childhood education) at I University in the central part of the United States, this present study tried to figure out the educationally meaningful direction of AI education for young children. The surveys were composed with open questions to find out PEC teachers’ metaphor of AI education for young children and they were distributed to research subjects. Collected data were named, classified, categorised, and finally, 7 categories out of 137 metaphors were analysed through the step of confirming. PEC teachers in this study had positive metaphorical concepts such as ‘possibility of play and experience’', ‘future essentials’, ‘innovation and change’, ‘convenience’, ‘assistant teacher’, and negative metaphorical concepts such as ‘double-sided meaning’, ‘Complexity’ of AI education for young children. PEC teachers’ beliefs about teaching-and-learning theory and methods related to AI education in ECE settings can be an important indicator of what thoughts and attitudes teachers will have when they implement the AI-related curriculum. Therefore, since PEC teachers have direct responsibility of planning and implementing AI education at ECE institutions, their conception of AI education in ECE would provide an important insight for shaping AI education for young children in the future.

Research on momentum strategy and contrarian strategy in AI stock prediction

The emergence of ChatGPT has significantly enhanced the recognition and acceptance of artificial intelligence concept stocks within the Chinese stock market. Nevertheless, the short- and long-term fluctuations in the prices of AI companies remain uncertain. Therefore, the purpose of this research is to determine optimal strategy for evaluating the suitability of the contrarian strategy versus the momentum strategy in predicting the stock prices of AI concept stocks in the Chinese stock market. Based on a cross-comparison of the Chinese financial data sources iFinD and Wind Economic Database (EDB), this study collects the price data of AI concept stocks over the past six months, starting from the date of ChatGPT's publication. This study employ Python to model stock price movements for both the momentum and reversal strategies. The goodness of fit is evaluated by comparing the modeled stock prices with the actual stock prices. This study demonstrates that the momentum strategy exhibits greater explanatory power than the contrarian strategy, accurately predicting 84.21% of artificial intelligence concept stocks. However, other studies suggest that while AI concept stocks continue to rise, momentum strategies remain effective, whereas when market sentiment cools down, contrarian strategies become more suitable for Chinese AI concept stocks. Hence, in China, the effectiveness of these strategies may vary depending on the prevailing market conditions.

Sądowe podejmowanie decyzji i interpretowalna sztuczna inteligencja (XAI) – spostrzeżenia z japońskiego systemu sądowego

The recent development of artificial intelligence (AI) in information technology (IT) is remarkable. These developments have led to claims that AI can be used in courts to replace judges. In the article, the author addresses a matrix of these issues using the concept of explainable AI (XAI). The article examines how regulation can ensure that AI is ethical, and how this ethicality is closely related to (XAI). It concludes that, in the current context, the contribution of AI to the decision-making process is limited by the lack of sufficient explainability and interpretability of AI, although these aspects are adequately addressed and discussed. In addition, it is crucial to consider the impact of AI’s contribution on the legal authority that forms the foundation of the justice system, and a possible approach is suggested to consider conducting an experimental study as AI arbitration.

AI Based Video Processing using OO

The increase in digital video material has increased the requirement for efficient video processing methods. Conventional techniques of video processing are sometimes time-consuming and reliant on substantial user intervention, resulting in decreased efficiency and precision. Video processing based on Artificial Intelligence (AI) is developing as a feasible alternative to conventional approaches. In this study, we investigate the application of Object-Oriented AI concepts to video processing. Our method utilizes object identification and recognition algorithms based on deep learning to recognize and track objects in video streams. In addition, we illustrate the efficacy of our method by applying it to a variety of actual video processing settings

Artificial Intelligence Techniques in Medical Imaging: A Systematic Review

This scientific review presents a comprehensive overview of medical imaging modalities and their diverse applications in artificial intelligence (AI)-based disease classification and segmentation. The paper begins by explaining the fundamental concepts of AI, machine learning (ML), and deep learning (DL). It provides a summary of their different types to establish a solid foundation for the subsequent analysis. The prmary focus of this study is to conduct a systematic review of research articles that examine disease classification and segmentation in different anatomical regions using AI methodologies. The analysis includes a thorough examination of the results reported in each article, extracting important insights and identifying emerging trends. Moreover, the paper critically discusses the challenges encountered during these studies, including issues related to data availability and quality, model generalization, and interpretability. The aim is to provide guidance for optimizing technique selection. The analysis highlights the prominence of hybrid approaches, which seamlessly integrate ML and DL techniques, in achieving effective and relevant results across various disease types. The promising potential of these hybrid models opens up new opportunities for future research in the field of medical diagnosis. Additionally, addressing the challenges posed by the limited availability of annotated medical images through the incorporation of medical image synthesis and transfer learning techniques is identified as a crucial focus for future research efforts.

Transforming neonatal care with artificial intelligence: challenges, ethical consideration, and opportunities.

Artificial intelligence (AI) offers tremendous potential to transform neonatology through improved diagnostics, personalized treatments, and earlier prevention of complications. However, there are many challenges to address before AI is ready for clinical practice. This review defines key AI concepts and discusses ethical considerations and implicit biases associated with AI. Next we will review literature examples of AI already being explored in neonatology research and we will suggest future potentials for AI work. Examples discussed in this article include predicting outcomes such as sepsis, optimizing oxygen therapy, and image analysis to detect brain injury and retinopathy of prematurity. Realizing AI's potential necessitates collaboration between diverse stakeholders across the entire process of incorporating AI tools in the NICU to address testability, usability, bias, and transparency. With multi-center and multi-disciplinary collaboration, AI holds tremendous potential to transform the future of neonatology.

ИСПОЛЬЗОВАНИЕ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА В БУХГАЛТЕРСКОМ УЧЕТЕ И АУДИТЕ: НОВЫЕ ВОЗМОЖНОСТИ

In the modern world, innovations in information technology are the main component of the development of the digital economy; they have a strong impact on almost all spheres of society. The rapid development of these innovations has significantly influenced many professions. Many industries have become less in demand, but most industries have become more developed and prosperous. As for accounting and auditing, this industry belongs to the second category; it is being modernized every day. This industry does not stand still with the development of information technology. Machine learning, financial robots and adaptive intelligence are already becoming part of routine workflow. The scientific article discusses the development of intelligent accounting, the introduction of artificial intelligence in the field of accounting and auditing. The article describes in detail the concept of artificial intelligence and defines its main tasks in accounting and auditing, also identifies the main directions of digitalization of accounting and conducts a SWOT analysis of the use of artificial intelligence in accounting

Law and technology: The impact of innovations on the legal system and its regulation

The relevance of this study is due to the introduction of technologies into the legal sphere, as well as their rapid development, which causes the inconsistency of conventional legislation with the emerging social relations. Thus, the purpose of this study was to research the impact of digital technologies on the modern legal society and their legislative regulation to formulate ways to improve and further develop this area. The methods used in this study were the following: historical, comparative legal, statistical, forecasting. The main results of this study are as follows: the concepts of technology, innovation, digitalisation, and artificial intelligence were investigated; the legal regulation of these concepts in both Ukrainian and foreign legislation was examined. The study also identified the main problems and risks associated with the use of digital technologies, including problems related to user security, personal data protection, copyright. Solutions and legislative changes regulating the field of technology were also covered using evidence from the United States of America, Switzerland, Japan, the United Kingdom, Canada. The study analysed the impact of artificial intelligence on the ethical aspects of the work of a lawyer. The study also highlighted the future vision and consequences of the use of technology in various spheres of public life. It was found that digitalisation and the introduction of technology into public spheres of life require flexibility and readiness for change from the legal sphere, as well as the need to strike a balance between innovative changes and the guarantee of fundamental human rights. Considering the international standards that were investigated, it was found that the key area that requires additional protection in the digital age is data privacy and confidentiality. The findings of this study can be used as a basis for improving the legislative framework that governs relations in the field of technology use by lawyers, sociologists, and legislators

Practices of artificial intelligence to improve the business in Bangladesh

This research paper explores the practices of artificial intelligence (AI) and its impact on improving businesses in Bangladesh through the review of existing literature and primary data analysis. Additionally, a conceptual analysis has been conducted on key AI concepts and their potential applications in the Bangladeshi business context. The study's objectives include providing a detailed understanding of specific AI technologies, measuring the benefits of AI, assessing the challenges faced by the industry in implementing AI and finding probable solutions to overcome these challenges. Data were collected from 120 respondents from 10 types of businesses in Bangladesh and analyzed using MS Excel and SPSS (V. 25). According to the results, using AI in enterprises may have a significant positive impact on efficiency, decision-making, production, cost, fraud detection, and supply chain optimization. However, obstacles to AI deployment include a lack of qualified personnel, poor data quality, money, infrastructure, and legal frameworks. Businesses should raise employee understanding of AI, look for diversified financing and qualified personnel, work with the government on infrastructure support and legislation, address concerns about job displacement through training, and encourage employee acceptance of change in order to overcome these challenges. Businesses in Bangladesh may improve operations and competitiveness by using these techniques. Business executives, decision-makers, and academics interested in maximizing the potential of AI and enhancing business outcomes in Bangladesh might learn from this study.

Java-Powered AI: Implementing Intelligent Systems with Code

The fusion of Artificial Intelligence (AI) and Java programming offers a powerful synergy, enabling developers to create intelligent systems and applications with efficiency, robustness, and scalability. This paper explores the amalgamation of Java's versatility and AI's cognitive capabilities, presenting various techniques, libraries, and methodologies that leverage Java's strengths in building AI-driven solutions. The paper commences with an overview of AI concepts and the landscape of Java's role in AI development. It delves into fundamental AI algorithms, such as machine learning, natural language processing (NLP), computer vision, and reinforcement learning, elucidating their implementation in Java through frameworks like Deeplearning, Weka, and Apache OpenNLP. Furthermore, it discusses the utilization of Java in crafting intelligent agents and exploring techniques for creating autonomous decision-making systems, expert systems, and heuristic-driven algorithms. It highlights the integration of Java with AI-enabled tools, emphasizing the importance of data preprocessing, feature engineering, and model deployment. Moreover, the paper examines the challenges and opportunities in Java-based AI development, addressing concerns related to performance optimization, compatibility with diverse data sources, and the interoperability of AI modules. Finally, the paper concludes with a glimpse into the future of Java-powered AI, envisioning advancements in Java libraries, frameworks, and methodologies that will foster the creation of more sophisticated, intelligent systems.

Generative Artificial Intelligence Terminology: A Primer for Clinicians and Medical Researchers.

Generative artificial intelligence (AI) is rapidly transforming the medical field, as advanced tools powered by large language models (LLMs) make their way into clinical practice, research, and education. Chatbots, which can generate human-like responses, have gained attention for their potential applications. Therefore, familiarity with LLMs and other promising generative AI tools is crucial to harness their potential safely and effectively. As these AI-based technologies continue to evolve, medical professionals must develop a strong understanding of AI terminologies and concepts, particularly generative AI, to effectively tackle real-world challenges and create solutions. This knowledge will enable healthcare professionals to utilize AI-driven innovations for improved patient care and increased productivity in the future. In this brief technical report, we explore 20 of the most relevant terminology associated with the underlying technology behind LLMs and generative AI as they relate to the medical field and provide some examples of how these topics relate to healthcare applications to help in their understanding.

Future Applications of Artificial Intelligence for the Egyptian Universal Health Insurance System

Artificial intelligence refers to simulating the human intelligence in machines. As it is present in all aspects of life, it has a great impact on the healthcare systems. In this article, the concept of artificial intelligence and its expected role on healthcare systems are presented. The Egyptian Universal Health Insurance system is presented as a case study.

Situating artificial intelligence in organization: A human-machine relationship perspective

The increasing advancements in artificial intelligence (AI) technology have resulted in greater adoption of intelligent devices, such as industrial and service robots. Such context substantially influences the routine processes of operations, thereby promoting the ongoing evolutionary development of human-machine interaction. Here, we analyze an interesting article published in the Academy of Management Review (AMR) by Ayenda Kemp, who proposes the concept of situated AI for discussing AI-driven competitive advantages. In our alternative framework of situating AI in the organization, we identify three aspects of the human-machine relationship—cohesion, autonomy, and equality—and associate them with three redefined situating activities—anchoring, bounding, and calibrating, to bring the full potential of AI to an organization. We believe this defined framework can further contribute to relevant literature in the field of digital economy.

Understanding Interplay Role of Augmented Reality, Virtual Reality, Computer Vision, Artificial Intelligence and Human Psychology

A very long ago since the origin of human life, vision is one of the essential and useful sense organ which is beautiful but complex. Simply it is co-related with machines for example computers. Some years ago it was very difficult to interpret vision process with the help of machines. Computer vision is the concept taken from human vision working mechanism. Likewise human eyes capture image or video, send signals to brain to process and then interpret, like physiology of pathway of vision, similarly computer vision is also captures image or video through camera send input for processing through special software algorithm and interpreted. This concept some years ago was dream but thanks to innovation in computer field. Many of scientist tried to work on it but few are successful. This computer vision takes the help of artificial intelligence to train computers to understand and to interpret the actual visual area or field. Basic concept of artificial intelligence is an intelligence used by “trained” machines verses an intelligence used “naturally” by animals and humans. Various innovative technologies are used to give better results in any sector. One of the most famous technology is used now a days is artificial intelligence for example in healthcare sectors. These all AR, VR, AI are used for better and bright future. Like for example early diagnosis and bad prognosis can be detected in early phases of disease course. The base concept of all such newer technologies are higher sense organs of human being like again for example computer vision is the concept innovated on the base of visual pathway of human eye. All of these process of vision and its interpretation or understanding and replying according to diagnosis shows involvement of psychology. This psychological aspect is taken as toolkit by many of researchers and they are developing modern technologies such as computer vision, artificial intelligence. As all of these are modern technologies one has to use if wisely. It mostly depends upon the intentions of the person or industry or institution what net result they are giving to society.

Artificial Intelligence Empowered Nuclear Medicine and Molecular Imaging in Cardiology: A State-of-the-Art Review.

Nuclear medicine and molecular imaging plays a significant role in the detection and management of cardiovascular disease (CVD). With recent advancements in computer power and the availability of digital archives, artificial intelligence (AI) is rapidly gaining traction in the field of medical imaging, including nuclear medicine and molecular imaging. However, the complex and time-consuming workflow and interpretation involved in nuclear medicine and molecular imaging, limit their extensive utilization in clinical practice. To address this challenge, AI has emerged as a fundamental tool for enhancing the role of nuclear medicine and molecular imaging. It has shown promising applications in various crucial aspects of nuclear cardiology, such as optimizing imaging protocols, facilitating data processing, aiding in CVD diagnosis, risk classification and prognosis. In this review paper, we will introduce the key concepts of AI and provide an overview of its current progress in the field of nuclear cardiology. In addition, we will discuss future perspectives for AI in this domain.

Cultivation of human centered artificial intelligence: culturally adaptive thinking in education (CATE) for AI.

Artificial Intelligence (AI) has become ubiquitous in human society, and yet vast segments of the global population have no, little, or counterproductive information about AI. It is necessary to teach AI topics on a mass scale. While there is a rush to implement academic initiatives, scant attention has been paid to the unique challenges of teaching AI curricula to a global and culturally diverse audience with varying expectations of privacy, technological autonomy, risk preference, and knowledge sharing. Our study fills this void by focusing on AI elements in a new framework titled Culturally Adaptive Thinking in Education for AI (CATE-AI) to enable teaching AI concepts to culturally diverse learners. Failure to contextualize and sensitize AI education to culture and other categorical human-thought clusters, can lead to several undesirable effects including confusion, AI-phobia, cultural biases to AI, increased resistance toward AI technologies and AI education. We discuss and integrate human behavior theories, AI applications research, educational frameworks, and human centered AI principles to articulate CATE-AI. In the first part of this paper, we present the development a significantly enhanced version of CATE. In the second part, we explore textual data from AI related news articles to generate insights that lay the foundation for CATE-AI, and support our findings. The CATE-AI framework can help learners study artificial intelligence topics more effectively by serving as a basis for adapting and contextualizing AI to their sociocultural needs.

The use of artificial intelligence during the educational process for students with attention deficit and hyperactivity disorder

This research paper delves into the transformative potential of artificial intelligence (AI) in education, with a specific focus on students with Attention Deficit Hyperactivity Disorder (ADHD). It examines both the advantages and challenges associated with the integration of artificial intelligence into educational practices. Beginning with an overview of artificial intelligence's emerging role in education, the paper explores the characteristics and symptoms of ADHD, tracing its historical evolution. This sets the stage for an in-depth discussion of the signs and symptoms of ADHD and the need for tailored educational approaches. The study further deepens into the concept of artificial intelligence, elucidating its capacity to replicate human mental capabilities and its growing significance in education, particularly within the realm of special education. The legislative landscape within the European Union (EU) and Greece regarding AI integration in education is also outlined. After the literature overview, artificial intelligence's pivotal role in education is highlighted, encompassing personalized learning experiences, virtual tutors, and its positive impact on student engagement, critical thinking, and problem-solving skills. The challenges posed by artificial intelligence integration are meticulously explored, including ethical concerns, biases in automated assessments, and the importance of fostering stakeholder awareness and education. Additionally, the operational prerequisites for AI implementation are addressed, encompassing both technical infrastructure and human resources. Special emphasis is placed on the necessity for adequate training and support for students and teachers, alongside the challenge of ensuring access to essential technical resources. In conclusion, the paper underscores the substantial potential of artificial intelligence to reshape education while acknowledging the importance of addressing ethical concerns and ensuring equitable access to artificial intelligence technologies. This research underscores the pivotal role of artificial intelligence in adapting to the evolving demands of 21st-century education, with a strong emphasis on personalized learning and learner-centered approaches.

Unleashing the Power and Assessing the Impact of Artificial Intelligence in Teaching and Learning

Abstract: As a transformative technology, Artificial Intelligence (AI) has the potential to revolutionize a wide range of industries, including education. The purpose of this study was to find out how the concept of artificial intelligence can be applied in teaching and learning and also assess the impact of Artificial Intelligence in education. In recent years, AI applications have gained significant momentum in the field of teaching and learning, offering new opportunities to enhance educational practices, personalizes learning experiences, and improves student outcomes. This research paper aims to explore the power of AI in education and assess its impact on teaching and learning. Furthermore, it investigates the potential benefits and challenges associated with the integration of AI in education.

AGI-agent cognitive architecture agica - axiomatic approach

For the last half of the century there were proposed and modeled several dozen cognitive architectures as the models of mind. As one of the results of this Standard Model of the Mind was proposed and discussed in 2017 (now known also as “Common Model of Cognition”). It accumulated lessons learned in one structure. In the articles published in 2016-2018, the author formulated main definitions of the concepts of Artificial General Intelligence (AGI): AGI-Individual Type, AGI-Collective Type, AGI-Consciousness, AGI-Thought, AGI-Knowledge, AGI-Emotions. The author’s approach belongs to the direction Embodied Cognition in Cognitive Science and is following named “axiomatic approach” in Artificial Intelligence. The definitions proposed by the author are of constructive type from mathematical point of view and can be modeled by the existing software & hardware tools and methods. In this article the author is proposing AGI-Agent cognitive architecture AGICA as detailed modification of Standard Model of the Mind. It can be used in the development of universal operating system for AGI-robots

Identifying the components of foundational Artificial Intelligence (AI) literacy - Early results from a Delphi study

This article provides some initial results from the first phase of a Delphi study to identify the critical components of an Artificial Intelligence (AI) literacy curriculum. This article explores the study results that address a four-level capability model, but only the lowest level of this model. The Delphi panel comprised 17 experts in AI, and the first round of the study used a survey to gather the experts' responses in three areas that were based on previous literature - knowledge (and concepts) of AI, skills related to AI, and understanding AI in context. A structured thematic analysis revealed several themes under these categories. For foundational knowledge and concepts, it was determined that three areas were needed, namely 1) what is AI? 2) applications of AI, and 3) AI technologies. Skills were divided into cognitive and technical skills, with cognitive skills further divided into 21st-century and applied skills. Understandings comprised social issues, risks, and debates. The repeated ideas that formed these themes gave rich insights into how an AI literacy curriculum might be structured and provided a firm foundation for subsequent rounds of the study, which will involve further iteration and consolidation of these ideas.