Application Of Artificial Intelligence Technology Research Articles

THE AI REVOLUTION IN IT EDUCATION

Artificial intelligence (AI) is rapidly transforming the IT landscape, demanding a paradigm shift in IT education. This paper explores the impact of AI on the educational process for aspiring IT specialists. The goals of transformation. Shifting focus of the curriculum is transitioning from a purely technical focus to preparing students for human-AI collaboration. Develop essential skills in data science, machine learning, and understanding the ethical implications of AI become central to the IT education framework. Orientation on lifelong learning for create adaptability and continuous learning skills to navigate the evolving field. Forming soft skills in communication, collaboration, and creativity gain prominence alongside technical expertise. The benefits are job market preparedness with graduates equipped by AI skills professionals become more competitive in the workforce. Enhanced problem-solving with understanding and applying AI tools improves students’ ability to analyze problems and develop innovative solutions. Increased Efficiency by leverage AI to automate tasks, optimize workflows, and achieve greater productivity. Fostering innovation with Integrating AI into the curriculum encourages students to explore new applications of AI technology. AI revolution create some challenges. Educational institutions need to adapt their curriculum and train faculty to effectively deliver AI-related content. Ensuring all students have equal access to the resources required for learning AI is crucial. Integrating discussions about AI ethics prepares students to use AI responsibly. The results are the integration of artificial intelligence (AI) in IT education is transforming the landscape of learning and teaching. This revolution is reshaping how students engage with content, how educators deliver instruction, and how institutions operate. Here are the key areas where AI is making a significant impact in IT education.

Application of Artificial Intelligence Technology in Vulnerability Analysis of Intelligent Ship Network

The improvement in transportation efficiency, security, safety, and environmental effects may be possible due to the impending advent of autonomous ships. Automatic situational awareness, risk detection, and intelligent decision-making are the key features of the intelligent ship network, differentiating it from conventional ships. There is an immediate need to implement a system for marine information management and network security due to the growing importance of this field, which poses a risk to national and societal stability due to factors, such as the diversity and complexity of marine information types, the challenges associated with data collection, and other similar factors. By recognizing different vulnerabilities and through research cases of the ship systems and Artificial Intelligence (AI) technologies, this paper presents Adaptive Fuzzy Logic-assisted Vulnerability Analysis of Intelligent Ship Networks (AFL-VA-ISN) in various cyberattack scenarios for autonomous ship intrusion detection and information management. Fuzzy logic has been combined with AI, providing a framework for handling uncertainty and imprecision in intelligent ship networks and effective decision-making. This work presents a method for detecting anomalies in risk data based on the collaborative control structure of the Ship Information System. Maintaining the network security of intelligent ships is the primary focus of this research, which mainly employed multi-sensor nodes to evaluate data containing information about malicious attacks and placed self-execution protection organize generating nodes into place to intercept and protect against attacks. The experimental outcomes demonstrate that the suggested AFL-VA-ISN model increases the data transmission rate by 99.2%, attack detection rate by 98.5%, risk assessment rate by 97.5%, and access control rate of 96.3%, and reduces the network latency rate of 11.4% compared to other existing models.

The application of artificial intelligence technology in assembly techniques within the industrial sector

The application of artificial intelligence technology in assembly techniques within the industrial sector

Research on entertainment robots based on artificial intelligence interaction for human posture recognition and sports activity monitoring

With the application of artificial intelligence technology in sports activity monitoring, new technologies such as interactive robots and the Internet of Things are being more widely used, which can provide entertainment and interactive guidance for sports training. This article analyzes the research on human pose recognition and sports activity monitoring of entertainment robots based on artificial intelligence interaction. This paper designs and develops an entertainment robot system that can recognize human posture and monitor physical activities. Users can interact with the robot and get real-time feedback about their posture and activities, thereby improving motor skills and physical fitness. After in-depth analysis of the theory of dynamic Bayesian network, we used EM algorithm to build a dynamic Bayesian network model, carried out detailed research on the random variables represented by the nodes of the dynamic model, and used the Internet of Things human posture recognition technology to extract the features of human behavior according to the characteristics of human behavior. The results show that the attitude recognition accuracy can be improved by adding the dynamic Bayesian network based on the random forest algorithm. The entertainment robot can accurately identify human posture and monitor sports activities, and has good real-time and stability. Through interaction with the robot, users can get personalized suggestions for individual postures and activities, improving the training effect and enjoyment of physical activities. Therefore, through the in-depth research and analysis of the dynamic Bayesian network and the human posture recognition of the Internet of Things, it is found that the sports activity monitoring system proposed in this paper can comprehensively monitor students’ sports activities, so as to achieve the goal of comprehensively improving students’ physical fitness.

Analysis and prediction of research hotspots and trends in heart failure research.

Comprehensive data analyses in heart failure research can provide academics with information and help policymakers formulate relevant policies. We collected data from reports published between 1945 and 2021 to identify research topics, trends, and cross-domains in the heart failure disease literature. Text fragments were extracted and clustered from the titles and abstracts in 270617 publications using artificial intelligence techniques. Two algorithms were used to corroborate the results and ensure that they were reliable. Experts named themes and document clusters based on the results of these semiautomated methods. Using consistent methods, we identified and flagged 107 heart failure topics and 16 large document clusters (divided into two groups by time). The annual vocabularies of research hotspots were calculated to draw attention to niche research fields. Clinical research is an expanding field, followed by basic research and population research. The most frequently raised issues were intensive care treatment for heart failure, applications of artificial intelligence technologies, cardiac assist devices, stem cells, genetics, and regional distribution and use of heart failure-related health care. Risk scoring and classification, care for patients, readmission, health economics of treatment and care, and cell regeneration and signaling pathways were among the fastest-growing themes. Drugs, signaling pathways, and biomarkers were all crucial issues for clinical and basic research in the entire population. Studies on intelligent medicine and telemedicine, interventional therapy for valvular disease, and novel coronavirus have emerged recently. Clinical and population research is increasingly focusing on the customization of intelligent treatments, improving the quality of patients' life, and developing novel treatments. Basic research is increasingly focusing on regenerative medicine, translational medicine, and signaling pathways. Additionally, each research field exhibits mutual fusion characteristics. Medical demands, new technologies, and social support are all potential drivers for these changes.

Application of Artificial Intelligence Technologies in Visual Communication Design

In recent years, the artificial intelligence technologies have developed rapidly, gradually infiltrated various fields, empowered all walks of life, and promoted the transformation and upgrading of technologies in various fields. Among them, the field of visual communication design, which mainly transmits visual symbol information, is developing in a more intelligent and diversified direction with the support of artificial intelligence technologies. This paper mainly discusses the application status and practical impact of artificial intelligence technologies in the field of visual communication design, so as to help people better understand and grasp the relationship and development between the two, promote the full and in-depth integration of the two, and improve the innovation and optimization development of visual communication design, which can bring people more beautiful design works.

Methodological and practical aspects of the application of artificial intelligence technologies in the system of state financial control

The article analyzes the use of artificial intelligence technologies in the system of state financial control. The authors present the main directions for the development of artificial intelligence, in particular its application in the system of government control. Also, the possibilities of expanding the areas of application of artificial intelligence in state financial control are being considered in order to increase the efficiency of the country’s economic security. The authors believe that the use of artificial intelligence will speed up inspections, and in the future there will be an intensification of the activities of state financial control bodies. The scientific novelty of the article lies in the fact that it examines the need to use artificial intelligence technology in the system of state financial control, and also analyzes the trend in the development of artificial intelligence in order to effectively ensure the economic security of the Russian Federation through state control bodies.

Exploring artificial intelligence and urban pollution emissions: "Speed bump" or "accelerator" for sustainable development?

Within the framework of the overarching green development objective guiding the transformation and progress of urban green and low-carbon initiatives, the technological advancements stemming from artificial intelligence have introduced fresh paradigms for reducing urban pollution and enhancing environmental governance. A comprehensive exploration into the influence of artificial intelligence on urban pollution emissions has emerged as a pivotal current concern. The findings that the progression of artificial intelligence has effectively curbed urban pollution emissions, assuming the role of a significant "speed bump". Robustness testing corroborated this conclusion. Mechanism testing unveiled that the evolution of artificial intelligence mitigates urban pollution emissions by enhancing production efficiency, minimizing energy consumption, boosting green technology innovation, optimizing industrial structure, and increasing public participation. Heterogeneity analysis underscored substantial variances in the impact of artificial intelligence on urban pollution emissions, influenced by pollutant types, regional disparities, and urban scale differentials. Further scrutiny exposed that while the application of artificial intelligence technology does not entirely mitigate the "local-neighborhood" effect, it does ameliorate the "boundary effect", subsequently reducing pollution emission intensity in cities straddling provincial administrative boundaries.

On the Question of the Concept of Artificial Intelligence Technologies

Despite the existing legal definition, the concept of artificial intelligence, which has penetrated various spheres of human life, requires a more precise definition. However, in most cases, artificial intelligence is opposed to human intelligence, the so-called natural intelligence, which looks natural, but it is difficult to recognize as true. The article substantiates that the ways of understanding human intelligence and artificial intelligence (or machine intelligence) they are completely different because their nature is different. Based on the analysis of various approaches of scientists, both lawyers and engineers, as well as legislators to the definition of artificial intelligence, the author concludes that the most appropriate really understanding of artificial intelligence as a field of scientific knowledge of a complex nature. The author makes a conclusion about the ways of further application of artificial intelligence technologies in forensic activities, considering the spread of artificial intelligence technologies. The result of the study is the formulation of the definition of artificial intelligence technology.

Exploring the Innovative Development of the Media Industry in the Digital Economy Era

With the acceleration of the informatization process, the digital economy has gradually become a new engine driving economic growth. The media industry, serving as a bridge between information producers and consumers, faces new development opportunities. The widespread use of the internet has accelerated the digital innovation of the media industry, making content creation and dissemination more convenient. The application of artificial intelligence technology has endowed the media industry with new capabilities, further enhancing its competitiveness. At the same time, industry integration can expand the convenience of the media industry and, through cooperation with other industries, bring new growth points to the media sector. However, the media industry also faces a series of challenges in its development process. Continuously relying on traditional profit models will inevitably constrain the development of the media industry, making it difficult to meet the profit needs of media enterprises. Additionally, the increasing amount of user data poses challenges to ensuring data security. To address these issues adequately, it is essential to deepen technological innovation, strengthen copyright protection, innovate profit models, and gradually enhance the capacity for independent innovation, addressing market competition and technological change, and making a greater contribution to the cultural prosperity and economic development of society.

EDUCATION IN THE ERA OF ARTIFICIAL INTELLIGENCE: AXIOLOGICAL STUDY

Education in the era of Artificial Intelligence (AI) presents new challenges in the axiological aspect, namely the moral and ethical values related to the use of AI technology in the learning process. This article aims to conduct an axiological study of education in the era of artificial intelligence with a focus on understanding the values that emerge along with the development of AI technology and their implications in the educational context. The research approach used is literature analysis to explore understanding of the use of AI in education and its implications for moral and ethical values. The results of the study show that the use of AI technology can provide significant benefits in increasing the effectiveness and efficiency of learning, but also raises several axiological problems. This research is qualitative research involving literature analysis, the data obtained will be processed thematically. In its conclusion, this article emphasizes the need to develop axiological awareness in education in the era of artificial intelligence. By paying attention to moral and ethical values, education can be an effective forum for developing a generation that is technologically intelligent and has a strong axiological awareness. This effort needs to be supported by critical thinking, reflection, and collaboration between educators, stakeholders and related parties to ensure that the application of AI technology in education runs ethically and responsibly.

Towards Promoting the Efficiency of Enterprise Investment Management with Artificial Intelligence

With the continuous development and optimization of artificial intelligence, enterprises have begun to pay attention to the use of artificial intelligence for the optimization of work and the improvement of efficiency, and in the management of enterprise investment, a number of companies have begun to use a large number of artificial intelligence technologies in the integration and analysis of data, information processing and analysis, risk management, efficiency improvement, and so on. Enterprises encounter problems in analyzing data and information in investment management, and problems in risk management, all of which affect the improvement of their investment returns. Enterprises face a huge amount of data in the process of investment management, it is difficult to calculate a large number of data models in a relatively short period of time, and it is impossible to analyze and extract more information. In the face of investment risk, the control of risk in the past investment process is more based on experience to judge, there is a great deal of subjective assumptions in risk avoidance. And in the investment process companies also want to increase returns, improve efficiency, avoid risk, and achieve a more automated and intelligent trading process. Enterprises need to use artificial intelligence to technically solve the problems of data aggregation, arithmetic, and analysis; use artificial intelligence to optimize the problem of processing large amounts of information; use artificial intelligence technology to enhance risk management and predictive analysis, strengthen intelligent decision-making and portfolio optimization, and provide insights into big data analysis and market trends. The wide application of artificial intelligence technology in enterprises also has a certain impact on the development of enterprises, and it has a certain impact on the planning, feasibility, whole-process control, investment evaluation, investment report, and investment efficiency of investment in the investment link, which makes it widely concerned in the society and in enterprises.

Practical applications of advanced cloud services and generative AI systems in medical image analysis

The medical field is one of the important fields in the application of artificial intelligence technology. With the explosive growth and diversification of medical data, as well as the continuous improvement of medical needs and challenges, artificial intelligence technology is playing an increasingly important role in the medical field. Artificial intelligence technologies represented by computer vision, natural language processing, and machine learning have been widely penetrated into diverse scenarios such as medical imaging, health management, medical information, and drug research and development, and have become an important driving force for improving the level and quality of medical services. The article explores the transformative potential of generative AI in medical imaging, emphasizing its ability to generate synthetic data, enhance images, aid in anomaly detection, and facilitate image-to-image translation. Despite challenges like model complexity, the applications of generative models in healthcare, including Med-PaLM 2 technology, show promising results. By addressing limitations in dataset size and diversity, these models contribute to more accurate diagnoses and improved patient outcomes. However, ethical considerations and collaboration among stakeholders are essential for responsible implementation. Through experiments leveraging GANs to augment brain tumor MRI datasets, the study demonstrates how generative AI can enhance image quality and diversity, ultimately advancing medical diagnostics and patient care.

Classification of Brain Image Tumor using EfficientNet B1-B2 Deep Learning

In this study, a new neural network model (EfficientNet B1-B2) was sought for the detection of brain tumors in magnetic resonance imaging (MRI) images. The primary objective was to achieve high accuracy rates so as to classify the images. The deep learning techniques meticulously processed and increased the data augmentation as much as possible for the EfficientNet B1-B2 models. Our experimental results show an accuracy of 98% in the B1 version in Table II. This provides a potentially optimistic view of the application of artificial intelligence technology to disease diagnosis based on medical image analysis. Nonetheless, we must remind ourselves that the dataset we used has limitations in terms of the challenges it can pose. Although the number of potential variations of actual medical images constitutes a major challenge, it is not the only one. Most medical datasets are unbalanced, contain highly variable noise, have a slow internal structure, and are often small in size. Hence, our end goal is to help stimulate not only the field of brain tumor detection and treatment but also the development of more sophisticated classification models in the health context.

Application of artificial intelligence in mine ventilation: a brief review.

In recent years, there has been a notable integration of artificial intelligence (AI) technologies into mine ventilation systems. A mine ventilation network presents a complex system with numerous interconnected processes, some of which pose challenges for deterministic simulation methods. The utilization of machine learning techniques and evolutionary algorithms offers a promising avenue to address these complexities, resulting in enhanced monitoring and control of air parameter distribution within the ventilation network. These methods facilitate the timely identification of resistance faults and enable prompt calculation of ventilation parameters during emergency scenarios, such as underground explosions and fires. Furthermore, evolutionary algorithms play a crucial role in the advancement of methods for visual analysis of ventilation systems. However, it is essential to acknowledge that the current utilization of AI technologies in mine ventilation is limited and does not encompass the full spectrum of challenging-to-formalize problems. Promising areas for AI application include analyzing changes in air distribution caused by unaccounted thermal draft and gas pressure, as well as developing novel approaches for calculating shock losses. Moreover, the application of AI technologies in optimizing large-scale mine ventilation networks remains an unresolved issue. Addressing these challenges holds significant potential for enhancing safety and efficiency in mine ventilation systems.

Application and Prospects of Artificial Intelligence Technology in Early Screening of Chronic Obstructive Pulmonary Disease at Primary Healthcare Institutions in China.

Chronic Obstructive Pulmonary Disease (COPD), as one of the major global health threat diseases, particularly in China, presents a high prevalence and mortality rate. Early diagnosis is crucial for controlling disease progression and improving patient prognosis. However, due to the lack of significant early symptoms, the awareness and diagnosis rates of COPD remain low. Against this background, primary healthcare institutions play a key role in identifying high-risk groups and early diagnosis. With the development of Artificial Intelligence (AI) technology, its potential in enhancing the efficiency and accuracy of COPD screening is evident. This paper discusses the characteristics of high-risk groups for COPD, current screening methods, and the application of AI technology in various aspects of screening. It also highlights challenges in AI application, such as data privacy, algorithm accuracy, and interpretability. Suggestions for improvement, such as enhancing AI technology dissemination, improving data quality, promoting interdisciplinary cooperation, and strengthening policy and financial support, aim to further enhance the effectiveness and prospects of AI technology in COPD screening at primary healthcare institutions in China.

人工智能技术在网络信息安全中的应用研究

With the continuous iterative development of computer technology, computer technology has been widely applied in various fields of real society, and artificial intelligence technology is also developing synchronously with computer technology. In the computer network environment, supporting artificial intelligence technology through programming techniques can mimic human neural networks and achieve various intelligent operation functions. However, in today’s society, the network environment is becoming increasingly complex, and the security of network information transmission is gradually being affected. Therefore, it is necessary to ensure the security of the network information environment through the improvement and application of artificial intelligence technology, in order to conduct deeper research on artificial intelligence technology and create a favorable objective environment for its application.

The Application of Artificial Intelligence for English Teachers

The birth and development of science and technology is to better serve mankind. The development of artificial intelligence technology is becoming more and more mature, especially in the application of English teaching, which promotes the reform, development and modernization of English teaching. This paper analyzes the connotation of AI technology and the application of artificial intelligence technology in English listening, writing, translation and oral teaching.

Cite space-based research on the use of artificial intelligence in the field of literature and museums

In recent years, with the rapid development and application of artificial intelligence technology, image technology based on artificial intelligence has gradually become a research hotspot in the field of cultural relic restoration. This article will explore the application of artificial intelligence based image technology in the field of cultural relic and museum restoration. Firstly, the importance of restoring cultural relics and artifacts was introduced, as well as the limitations and shortcomings of traditional restoration methods. Secondly, elaborate on the development and application of artificial intelligence technology, as well as its potential and advantages in the field of cultural relic restoration. Next, we will introduce the application of artificial intelligence based image technology in cultural relic restoration, including image enhancement, segmentation, recognition, and reconstruction. Finally, the application prospects and challenges of artificial intelligence based image technology in the field of cultural relic restoration were summarized, and future research directions and suggestions were proposed.

Metamorphosis of Islamic Religious Education Learning Method: Classic Approach Converted by Artificial Intelligence (AI)

The transformation of Islamic religious education learning methods through the conversion of classical approaches using artificial intelligence (AI) represents a significant phenomenon that has reshaped paradigms in the field of religious education. This literature review qualitatively explores profound changes in the approach to Islamic religious education brought about by the application of artificial intelligence technology. It focuses on aspects such as personalized learning, real-time monitoring of student progress, adaptation to individual learning styles, automatic feedback, and online collaboration. Qualitative analysis reveals how artificial intelligence enhances students' learning experiences. Through this transformation, the learning approach becomes more responsive and tailored to the individual needs of students, fostering a more inclusive learning environment. In the context of ethics and humanity, the literature review highlights the importance of humane guidance, ethical algorithm design, ethics training for developers and users, and privacy protection as crucial elements. This research underscores the significance of upholding ethical and humane values ​​when integrating artificial intelligence into Islamic religious education. By synthesizing findings from various literature sources, this abstract concludes that the metamorphosis of Islamic religious education learning methods through artificial intelligence plays an integral role in enhancing adaptability, responsiveness, and effectiveness in religious education. Consequently, this study provides profound insights into the positive implications and ethical challenges that need to be addressed in navigating the ever-evolving digital era.