Intelligent Applications Research Articles

Effect of Educational Guidelines on Maternity Nurses' Knowledge and Attitude regarding Artificial Intelligence Application

Effect of Educational Guidelines on Maternity Nurses' Knowledge and Attitude regarding Artificial Intelligence Application

AI-Powered Obstacle Detection for Safer Human-Machine Collaboration

Abstract This article deals with ensuring and increasing the safety of mobile robotic systems in human-machine collaboration. The goal of the research was to design and implement an artificial intelligence application that recognizes obstacles, including humans, and increases safety. The resulting mobile Android application uses a MiDaS model to generate a depth map of the environment from the drone’s camera to approximate the distance from all obstacles to avoid the drone’s collision. Besides, this work introduced us to DJI Mobile SDK and neural network optimizations for their use on smartphones.

Mapping the Way: Teaching Music Information Literacy in the Contemporary Information Landscape

abstract: Information literacy instruction in the twenty-first century stands at a crossroads of multiple socio-cultural trends, recent technological advances (specifically, artificial intelligence applications and large language models), shifting professional standards, and new developments in local educational settings. It is now necessary for instructors to act as explorers of the information environments in which they live and work, observing and staying cognizant of these developments while utilizing the principles of information ethics as a compass for guiding their work. In this article, the author explains how developments in local settings, combined with the above factors, can serve as an impetus for reinventing information literacy instruction. The author presents a variety of strategies for teaching information literacy in music in both credit-bearing courses and "one shot" instructional sessions that incorporate existing information literacy standards and values in information ethics. Curriculum mapping is highlighted as a strategy for planning and codifying pedagogical strategies while keeping lesson planning adaptable and responsive to specific learning needs. Recommendations for other instructors acknowledge that the process of delivering effective information literacy instruction in music is ongoing; success will depend upon how instructors choose to respond to contemporary societal developments and the educational needs of students and colleagues at their respective institutions.

Artificial Intelligence Models and Association of Air Pollutants and Novel Coronavirus: A Survey for Asia and Oceania

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic has led to approximately 704 million confirmed cases of coronavirus disease (COVID-19) and resulted in approximately 7.01 million fatalities worldwide. The present review examines the applications of Artificial Intelligence (AI) models concerning the COVID-19 pandemic and its correlation with air pollutants. The objective of this review is to identify, assess, and synthesize pertinent findings regarding the relationship between air pollution and COVID-19. Initially, a comprehensive set of 549 articles was screened, resulting in the selection of 38 articles from the study region through two stringent rounds of inclusion and exclusion. Given the limited availability of published literature originating from countries in Asia and Oceania, the authors endeavoured to focus specifically on studies from this geographical area. The analysis primarily centred on contextual keywords, methodologies employed, algorithms utilized, and, notably, the specific air pollutants examined, such as particulate matter (PM) including PM2.5 and PM10, as well as associated meteorological parameters. Our findings indicate that a significant portion of the research is concentrated in China, recognized as the initial epicentre of the COVID-19 outbreak. Additionally, most researchers from Asia and Oceania primarily concentrated on PM2.5, followed by studies on meteorological factors and PM10. This review delineates five prospective research avenues for future exploration. Consequently, this article enriches the existing literature by providing researchers with insights into current studies, thereby enhancing the accessibility of available evidence for decision-makers and proposing a potential research agenda for forthcoming investigations.

Unlocking the potential: Responsibly embracing artificial intelligence to advance the use of health data and analytics at the Canadian Institute for Health Information.

Canadian Institute for Health Information (CIHI) is looking to modernize and adopt new ways of working. This incudes the use of new technology, including the application of Artificial Intelligence (AI). To begin in a purposeful manner, the organization developed an AI strategy which was informed through feedback from key stakeholders and partners, from its staff and from a review of international research. The research informed several ways AI could add value to CIHI's internal operations and to the external role CIHI could play in advancing responsible AI adoption in health systems across Canada. This article describes the strategy development process and the areas of focus within the strategy.

Educational Application of Artificial Intelligence for Diagnosing the State of Railway Tracks

The aim of the work is to present an innovative solution based on artificial intelligence for examining the condition of railway tracks in real time. The system, based on fuzzy logic and metaheuristics such as Fuzzy Logic, Neural Networks and Bee Behavior Optimization, combines hardware and software to provide reliable data on the technical characteristics of the railway. Installed in rail vehicles, hardware collects this data, while software uses artificial intelligence to improve operational reliability and safety. The aforementioned technology is not only useful for infrastructure diagnostics, but also for urban railways such as trams and metros, ensuring a high level of passenger safety. The introduction of artificial intelligence in the railway sector is a key step towards modernisation, improving efficiency, resource optimization and safety. Although still in its infancy, artificial intelligence already shows great potential in transforming the railway sector towards a more efficient, reliable and sustainable future.

Detection and Analysis of Anomalous Behavior in On-Orbit Satellites Using AI Algorithms

The increasing deployment of satellites for essential applications necessitates robust anomaly detection to maintain their operational integrity. Traditional methods, which depend on manual monitoring and predefined thresholds, often prove inadequate in the complex space environment. This paper investigates the application of Artificial Intelligence (AI) algorithms to improve the detection and analysis of anomalous behavior in on-orbit satellites. AI, especially through machine learning (ML) and deep learning (DL), provides advanced capabilities for processing extensive telemetry data and identifying intricate patterns. By leveraging historical data, AI systems can establish normal operational parameters and detect deviations indicating potential anomalies. Techniques such as supervised and unsupervised learning are employed to develop models with high predictive accuracy. Furthermore, AI facilitates root cause analysis by correlating anomalies with operational conditions or external factors, enabling effective corrective measures. The integration of AI also promotes autonomous satellite operations, which are crucial for deep-space missions. This advancement enhances satellite reliability and safety, supporting sustainable and progressive space exploration. In this research, machine learning algorithms were employed to develop the proposed anomaly detection system. The system aims to detect subtle failures in the spacecraft’s attitude dynamics system, particularly in the reaction wheel subsystem, by learning solely from the spacecraft's nominal behavioral data. The system was developed from a small satellite's attitude dynamics control system, which may exhibit bearing failures in the reaction wheels. Two types of anomaly detection systems were introduced: a two-sided learning anomaly detection system and a one-sided learning anomaly detection system. For this study, a two-sided learning anomaly detection system was developed using the Logistic Regression (LR) method. This provided a foundation for the training process using a machine learning approach. By learning from both nominal and failure behaviors of the satellite, the system was designed to detect small reaction wheel friction failures effectively.

A Chinese perspective on artificial intelligence generated content and copyright

In recent years, the application of artificial intelligence (AI) in the field of content generation has become more and more widespread, and the concept of artificial intelligence generated content (AIGC) has gradually entered the public consciousness. Can pieces of AIGC be considered works? Can AI be the author of AIGC? This paper seeks to provide a comprehensive and systematic analysis of the literature of Chinese scholars so as to sort out the different perspectives of Chinese scholars on the relevant issues. This paper uses the China National Knowledge Infrastructure (CNKI) as the data source database and uses Citespace to carry out text-mining work in the retrieved literature. This literature presents twelve main doctrines on the copyrightability of AIGC and three doctrines on its attribution.

The Application of Artificial Intelligence in Education – The Current State and Trends

The aim of this paper is to discuss the application of contemporary AI tools and technologies in education. The paper will mainly focus on a close examination of relevant academic literature as well as the current situation and methods of AI implementation in different sectors, finally, in education. Particularly, it was crucial that there were identified the major directions of applying AI in learning with an emphasis on learners and educators being the basic aspects of AI use within modern educational approaches. Secondly, some benefits and drawbacks concerning AI implementations in education supported by experiences from industry leaders and specific satisfaction measures among existing users, are analyzed. The most significant part covers integrating findings that show facts about artificial intelligence being used in education for 2024 like top online learning statistics for 2024, top AI statistics for 2024, and best AI plagiarism checkers for teachers in 2024 respectively. This includes evaluating teacher or instructor preparation skills to employ artificial intelligence (AI) tools and technology as well as ways students can learn how to use them without misuse towards quality education improvement.

A Review of the Applications of Artificial Intelligence in Histopathology

A Review of the Applications of Artificial Intelligence in Histopathology

The Application of Artificial Intelligence on Business operations and Accounting Practices and its Impact on Overall Organizational Efficiencies: A Review Work

This Paper shows the relationship between Artificial Intelligence and Accounting practices and practitioners by creating a crucial analysis of previous literature related to the study. This paper emphasizes on the impacts of AI on different accounting determination and to the different methods of accounting. As the introduction of AI different companies reshaping their financial decision-making process significantly. This specific study explores the different new ideas through which the business firm can also develop their position now and then. The study reviews the different articles, case studies, Annual Reports of the company. The findings significantly enhance the speed and accuracy of the company to all round’s activities and also enhances the activities of Business 4.0 and 5.0. The stakeholders of the company also be benefited significantly to take quick and accurate decisions by reviewing AI driven financial reports. However, it comprises of some amount of barrier in this process where the study mainly emphasizes on all those areas for efficient operation of business firm through the adoption of AI.

The Impact of Artificial Intelligence in Educational System

The way we teach and learn could be completely transformed by artificial intelligence (AI), which could make the process more efficient, personalized, and interesting. Artificial intelligence (AI) in education is the application of AI technologies, like natural language processing and machine learning, to improve the educational process. Through the use of algorithms, teachers are able to customize learning for each student by analyzing data, finding trends, and making predictions. Artificial intelligence (AI) and its potential impact on education have gained widespread attention because of ChatGPT's impressive performance on standardized academic assessments. For the development and implementation of AI-driven technologies in schools, colleges, and universities to be sustainable, a thorough knowledge of their effects on the current educational system is needed. The application of AI in education has a lot of potential advantages. One of the biggest benefits of AI in education is personalized learning, which allows students to learn at their own pace and in a fashion that best fits their learning preferences. This can improve student results. Chatbots, automated grading and evaluation, and intelligent tutoring systems can boost productivity, free up teachers' time, and deliver more precise and consistent feedback. Some of the challenges that need to be resolved are potential bias, cost, lack of confidence, and privacy and security concerns. AI can improve data analysis, empowering teachers to make facts-based decisions. There are some impacts of artificial intelligence in educational system that are covered in this review. These are the applications of artificial intelligence in automated assessment, intelligent tutoring systems, personalized learning, and collaborative teacher-student learning.

Harnessing the potential of AI applications in Education: Opportunities, challenges, and future directions

The potential of artificial intelligence (AI) applications in education to revolutionize teaching and learning has attracted a lot of interest in recent years. This research paper presents an in-depth review of the many AI uses in education, such as virtual reality simulations, automated grading systems, intelligent tutoring systems, and personalized learning platforms. This article explores the potential that AI technologies offer to improve educational practices, including individualized instruction, better learning outcomes, and increased student engagement. It does this by drawing on current literature and empirical data. It also discusses the challenges and ethical encounters that come with incorporating AI into the classroom, like algorithmic bias, data privacy issues, and the digital divide. This paper delves deeper into a several possibilities for future research and development in artificial intelligence (AI) applications in education, highlighting the significance of interdisciplinary collaboration, building robust frameworks for assessment, and promoting equity and inclusivity in AI-powered learning environments.

Application of Artificial Intelligence in Cone-Beam Computed Tomography for Airway Analysis: A Narrative Review.

Cone-beam computed tomography (CBCT) has emerged as a promising tool for the analysis of the upper airway, leveraging on its ability to provide three-dimensional information, minimal radiation exposure, affordability, and widespread accessibility. The integration of artificial intelligence (AI) in CBCT for airway analysis has shown improvements in the accuracy and efficiency of diagnosing and managing airway-related conditions. This review aims to explore the current applications of AI in CBCT for airway analysis, highlighting its components and processes, applications, benefits, challenges, and potential future directions. A comprehensive literature review was conducted, focusing on studies published in the last decade that discuss AI applications in CBCT airway analysis. Many studies reported the significant improvement in segmentation and measurement of airway volumes from CBCT using AI, thereby facilitating accurate diagnosis of airway-related conditions. In addition, these AI models demonstrated high accuracy and consistency in their application for airway analysis through automated segmentation tasks, volume measurement, and 3D reconstruction, which enhanced the diagnostic accuracy and allowed predictive treatment outcomes. Despite these advancements, challenges remain in the integration of AI into clinical workflows. Furthermore, variability in AI performance across different populations and imaging settings necessitates further validation studies. Continued research and development are essential to overcome current challenges and fully realize the potential of AI in airway analysis.

Application of Artificial Intelligence to Improve Production Process Efficiency in Manufacturing Industry

The rapid advancement of Artificial Intelligence (AI) has profoundly impacted the manufacturing industry, offering transformative potential to enhance production process efficiency. This paper presents a systematic literature review of AI applications in the manufacturing sector, focusing on key AI technologies such as machine learning, robotics, predictive analytics, and natural language processing. The review highlights how these technologies have improved quality control, resource management, and overall operational performance. However, the adoption of AI also presents challenges, including significant investment costs, the need for a skilled workforce, and concerns over data security and privacy. Despite these challenges, the integration of AI in manufacturing presents numerous opportunities for future research and innovation, particularly in the areas of sustainable manufacturing and the convergence of AI with other emerging technologies. This study concludes that while AI offers substantial benefits for production efficiency, its successful implementation requires careful strategic planning and investment in both technology and human resources.

Graphic association learning: Multimodal feature extraction and fusion of image and text using artificial intelligence techniques

With the advancement of technology in recent years, the application of artificial intelligence in real life has become more extensive. Graphic recognition is a hot spot in the current research of related technologies. It involves machines extracting key information from pictures and combining it with natural language processing for in-depth understanding. Existing methods still have obvious deficiencies in fine-grained recognition and deep understanding of contextual context. Addressing these issues to achieve high-quality image-text recognition is crucial for various application scenarios, such as accessibility technologies, content creation, and virtual assistants. To tackle this challenge, a novel approach is proposed that combines the Mask R-CNN, DCGAN, and ALBERT models. Specifically, the Mask R-CNN specializes in high-precision image recognition and segmentation, the DCGAN captures and generates nuanced features from images, and the ALBERT model is responsible for deep natural language processing and semantic understanding of this visual information. Experimental results clearly validate the superiority of this method. Compared to traditional image-text recognition techniques, the recognition accuracy is improved from 85.3% to 92.5%, and performance in contextual and situational understanding is enhanced. The advancement of this technology has far-reaching implications for research in machine vision and natural language processing and open new possibilities for practical applications.

Can the Pioneering Impact of Artificial Intelligence in Anaesthetic Practice Uphold Good Medical Practice?

The potential applications of Artificial Intelligence (AI) in anaesthesia are expansive.~However, like any technological advancement, the integration of AI in anaesthetic practice comes with both benefits and potential risks. This article seeks to set out some of the advantages and disadvantages of the use of AI technologies within the field of anaesthesia. Benefits of the application of AI in anaesthesia include an improvement in perioperative risk stratification, personalisation of anaesthetic plans, improvement in efficiency and ultimately reduce healthcare costs. However, reliance on technology may reduce clinical acumen but furthermore there are issues surrounding data quality, privacy as well as legal and ethical concerns, which require further evaluation. Whilst AI within anaesthetic practice holds immense promise, there are substantial challenges which require careful consideration and ongoing evaluation. A collaborative approach will be required from healthcare staff, developers and regulators to promote the safe, responsible, and effective application of AI in anaesthesia practice.

АНАЛИЗ УГОЛОВНОГО ПРАВОСУДИЯ И КИБЕРПРЕСТУПНОСТИ В КОНТЕКСТЕ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА ЧЕРЕЗ ПРИЗМУ МЕЖДУНАРОДНЫХ ОРГАНИЗАЦИЙ

The scientific article is aimed at analyzing issues related to the use of existing international instruments in the fight against cybercrime in the context of the use of artificial intelligence technologies. Within its framework, an assessment is made of the current position of international organizations and their potential impact on legislation and processes in the field of combating cybercrime in the near future. The focus is on analyzing the implications of artificial intelligence developments for the effective management of the criminal justice system, particularly in the context of combating cybercrime. The study also examines current trends and practices in the use of artificial intelligence systems and applications to carry out harmful and illegal activities, including phenomena such as deepfakes. The final part of the article proposes alternative approaches to developing effective measures to combat cybercrime carried out using artificial intelligence systems.

Preventing postoperative moderate- and high-risk pressure injuries with artificial intelligence-powered smart decompression mattress on in middle-aged and elderly patients: a retrospective cohort analysis.

Aims/Background Artificial intelligence technology has attained rapid development in recent years. The integration of artificial intelligence applications into pressure reduction mattresses, giving rise to artificial intelligence-powered pressure reduction mattresses, is expected to provide personalised intelligent pressure reduction solutions, through automatic user's data-based adjustment of the patient's local pressure condition to prevent pressure injury. The purpose of this study was to investigate the effectiveness of artificial intelligence-powered smart decompression in the prevention of postoperative medium- and high-risk pressure injury in middle-aged and elderly patients. Methods A total of 400 middle-aged and elderly patients admitted to our hospital from June 2021 to December 2023 were selected as study subjects. Patients were categorised into observation and control groups according to the medical record system. General demographic data of the patients were collected. The propensity score matching method was used to balance the baseline data of the two groups of patients. The incidence, severity, complications and sleep quality in the matched study subjects were also compared. Results After matching, there were 96 patients in the two groups, and the differences in baseline data between the two groups were not statistically significant. Pressure injury and the total incidence of complications in the observation group were significantly lower than those in the control group (p < 0.05). Before treatment, there was no difference in the scores of all aspects of the Richards Campbell Sleep Questionnaire between the two groups (p > 0.05). After treatment, the scores of all aspects of Richards Campbell Sleep Questionnaire in the observation group were significantly lower than those in the control group (p < 0.05). Conclusion The artificial intelligence-powered smart decompression mattress can significantly prevent moderate- and high-risk pressure injury, effectively reducing the incidence of pressure injury and complications in postoperative long-term bedridden patients, alleviating the severity of pressure injury, relieving the pressure on various parts, and improving the sleep quality of patients.

Research on Music Teaching Systems Assisted by Artificial Intelligence

In music teaching, the application of artificial intelligence has brought revolutionary changes to teaching and greatly improved the teaching quality and learning effect. The purpose of this study is to explore the application and effectiveness of artificial intelligence in auxiliary music teaching system. With the rapid development of information technology, the application of artificial intelligence in the field of education is more and more extensive, especially in the field of music teaching, and its potential and value are gradually emerging. In this study, by constructing a music teaching system based on artificial intelligence, the influence of learners on music cognition, skill mastery and innovation ability was deeply studied. In terms of research methods, this study uses empirical research methods, combined with questionnaires, teaching experiments, data analysis and other means to comprehensively evaluate the effectiveness of artificial intelligence-assisted music teaching system.