Artificial Intelligence Concepts Research Articles

The breakthrough of philosophy of mind in the construction of artificial intelligence concepts in Marxist philosophy

The breakthrough of philosophy of mind in the construction of artificial intelligence concepts in Marxist philosophy

Sustainable Supply Chain Finance and Supply Networks: The Role of Artificial Intelligence

Supply chain finance (SCF) is receiving increasing awareness in research as a result of uncertainties in the global financing for supply chain (SC). There are limited and fragmented studies in the implementations of financial services in SC management. This article builds on recovery from the financial crisis of 2008 and posts COVID-19 pandemic, where uncertainties crippled SCF providers and brokers services. At the same time, cutting-edge technological advancements such as Artificial Intelligence (AI) are revolutionizing the processes of business ecosystem in which SCF is entrenched. This article thus adopts a fuzzy set theoretical approach to unpack the entities relationship validity for sustainable SCF mate-framework, and the originality of AI concepts to sustainable SCF to identify the issues and inefficiencies. The results indicate that AI contributes significant economic opportunities and deliver the most effective utilization of the supply networks. In addition, the article provides a theoretical contribution to financing in SC and broadens the managerial implications in improving performance.

Modeling of Improved Sine Trigonometric Single Valued Neutrosophic Information based Air Pollution Prediction Approach

Industrialization and urbanization air is getting polluted due to human activities. CO, NO, C6H6, etc., are the major air pollutants. The focus of air pollutants in ambient air is controlled by the climatological parameters including wind direction, atmospheric speed of wind, temperature, and humidity. Air pollution prediction is a critical sector where machine learning (ML) technique plays a major role. Its main purpose is to tackle and understand the damaging effects of air pollutants on the environment and human health. By using a range of ML techniques such as neural networks, regression, and decision trees, we could analyze historical data on air quality alongside geographical and meteorological factors. This allows us to design model that could detect patterns and predict pollution levels. By taking proactive measures such as providing timely alerts to the public, adjusting controls on emissions, and, implementing strategies to reduce pollution, we can work towards creating healthier and cleaner environments. Embracing the potential of artificial intelligence (AI) in air pollution prediction empowers us to protect the well-being of our communities and make informed decisions. Therefore, this study develops an Improved Sine Trigonometric Single Valued Neutrosophic Information based Air Pollution Prediction (ISTSVNI-APP) approach. The major objective of the ISTSVNI-APP technique is to exploit AI concepts with neutrosophic sets (NS) models for the forecasting of air pollution. To do so, the ISTSVNI-APP technique makes use of min-max normalization as the initial preprocessing step. For predicting air pollution, the ISTSVNI-APP technique uses STSVNI approach. To improve the performance of the ISTSVNI-APP technique, modified crow search algorithm (MCSA) is used for the parameter tuning of the STSVNI system. The performance evaluation of the ISTSVNI-APP method is verified utilizing benchmark dataset. The experimental outcomes stated that the ISTSVNI-APP technique gains better performance in predicting air pollution

The authority to prove deepfakes technically and jurisprudentially in artificial intelligence systems

The research aims to demonstrate the authority to prove deepfakes technically and jurisprudentially in artificial intelligence systems, as many people still fear the harm of this development in artificial intelligence, mimicking voice, and image, etc. The research contains the concept of artificial intelligence, details on the method of detecting deepfakes technically, the authority of deepfakes in jurisprudence, and then the result, which is: that ‏probable ‏evidence is considered one of the methods of proof considered in the judiciary in Islam. The means of proof are not limited to a specific number. ‏Therefore, those videos or audio clips that were detected through deepfake tools and whose falsification was not proven are some of the evidence that varies in strength and weakness. That is what the judge and his specialist experts estimate. This means according to the evidence, the authority of rights is proven, or dropped.

Role of Artificial Intelligence in Different Sectors of Society

t was in 1956 that the concept of artificial intelligence came into existence. John McCarthy and Marvin Minsky hosted the Dartmouth Summer Research Project, and here they coined the word “artificial intelligence.” The workshop laid the foundation for the field of artificial intelligence. Back to the current timeline, few studies believe that artificial intelligence will contribute 15.7 trillion dollars to the world economy by the year 2030. A branch of computer science that commands machines to simulate human intelligence, artificial intelligence is bringing a paradigm shift in each sector of society. The smart machines working on the concept of deep learning, are capable of performing tasks and making decisions that only a human mind can. These software systems operate in such a manner that they adapt to the situation. Artificial intelligence has the potential to make society even better by bringing positive changes in healthcare, education, governance, policy formulation and implementation, technology, resource management, innovation, etc. Artificial intelligence holds the potential to make human lives better in thousands of ways. Today, if we look around, we are already using AI in our daily lives in some way or another. Artificial intelligence technology in smartphones has grown rapidly in recent years. Google Assistant, Siri, and Alexa are a few examples of AI personal assistants that make our daily tasks easier. Not only do these solution-driven technologies follow commands, but they also learn from experience to provide better services. Today, artificial intelligence is reshaping and redefining industries. It is bringing about a revolution in technology and impacting the global economy. Artificial intelligence can solve complex problems in a limited amount of time and with enhanced accuracy.

Artificial intelligence in cardiovascular medicine: An updated review of the literature.

Screening and early detection of cardiovascular disease (CVD) are crucial for managing progress and preventing related morbidity. In recent years, several studies have reported the important role of Artificial intelligence (AI) technology and its integration into various medical sectors. AI applications are able to deal with the massive amounts of data (medical records, ultrasounds, medications, and experimental results) generated in medicine and identify novel details that would otherwise be forgotten in the mass of healthcare data sets. Nowadays, AI algorithms are currently used to improve diagnosis of some CVDs including heart failure, atrial fibrillation, hypertrophic cardiomyopathy and pulmonary hypertension. This review summarized some AI concepts, critical execution requirements, obstacles, and new applications for CVDs.

Concepts and Definitions of Artificial and Natural Intelligence: A Methodological Analysis

The article delves into the conceptual frameworks surrounding artificial intelligence (AI) by juxtaposing it with natural intelligence and delineating the correlated notions. It enumerates the issues propelling the discourse on the explored topics. The author proposes a bifurcation between two polar concepts of artificial intelligence. The first is dubbed “imitative,” where AI is perceived in relation to natural intelligence as its technical recreation, capable of not only emulating but significantly outstripping its natural counterpart. A prerequisite for embodying this concept is understanding natural intelligence; three approaches are examined: (a) acknowledging the lack of a precise understanding of natural intelligence, (b) exploring it from a biological perspective, and (c) analyzing it from a psychological perspective. The author articulates their own interpretation of natural intelligence, portraying it as a multifaceted amalgam of cultural, historical, social, and anthropological elements. From this vantage point, natural intelligence emerges not merely as a natural formation (thereby, discussions about the laws governing its function and evolution are warranted), but also as an “extra-natural” formation, its existence dictated by randomness and uniqueness, meaning natural intelligence evolves in a “singular” manner. In the context of comparing natural and artificial intelligence, the discussion encompasses several issues: the feasibility of the control of natural intelligence processes, the structure of neural networks, the superiority of computer programs in chess, the use of neural networks to write academic papers, and so forth. The conclusion posits that given artificial intelligence, despite its complexity, remains a technical invention orchestrated and brought to fruition by humans as a tool; society, if inclined to bestow AI with autonomy for tackling specific tasks, ought to do so prudently to prevent self-detriment and retain the ability to curtail or utterly revoke such autonomy.

William Gibson’s Sprawl Trilogy: Connection between Humans and Artificial Intelligence

Artificial intelligence as it is envisioned in literature, reflects moral and social standards, sculpts societal hopes and fears, spurs scientific progress, and perhaps even foretells the future. Artificial intelligence (AI) is being developed by humans, including programmers through their code and authors and readers through millennia of discourse, starting with ancient automatons and continuing with contemporary concepts of AI. The question of what we are producing as AI becomes more human—and possibly superhuman—and what literature can teach us about these AI imaginaries are also topics covered in this paper. The researcher seeks to explain the connections between artificial intelligence and literature in this work by highlighting the numerous ways that machine intelligence helps the production and comprehension of narrative. This study will also look at the connection between humans and artificial intelligence in William Gibson’s Sprawl trilogy and how his cyberpunk trilogy allows readers to think about how the lines between humans and technology are blurring and how technology can both liberate and enslave people.

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.