Application Of AI Technology Research Articles

USING ARTIFICIAL INTELLIGENCE FOR RISK MANAGEMENT IN PROJECTS WITH THE SCRUM METHODOLOGY

In the rapidly evolving area of Information Technology projects, the integration of Artificial Intelligence into project risk management assessment processes represents an innovative approach that could pitch a risk evaluation process. The study investigates the standard risk management strategies and their limitations in the context of agile project environments by Scrum methodology. Standard methodologies for risk management often fall short in dynamically adapting to the rapidly changing schedule and evolving requirements characteristic of Agile projects. This gap in effectiveness becomes especially important when dealing with projects managed under the Scrum methodology, which prioritizes flexibility, rapid iteration, and stakeholder involvement. The study proposes an innovative solution to this problem through the application of AI technologies, which can significantly enhance both the precision and depth of risk assessments. The study explores several AI models, highlighting their potential to revolutionize risk management in IT projects. One of the key insights from the study is the ability of AI to process and analyze big amounts of data at a speed and efficiency that is impossible to achieve with a regular expert team. This capability allows for real-time risk assessment, enabling project teams to make informed decisions quickly and adapt their strategies to mitigate potential issues before they grow into significant problems. Moreover, AI's predictive analytics can forecast potential risks based on historical data, allowing for proactive risk management rather than reactive. The research further discusses the implementation challenges and considerations for incorporating AI into Scrum-based projects, including ethical considerations, data privacy concerns, and the need for interdisciplinary expertise to design, deploy, and manage AI-enhanced risk management systems.

Research on the Construction of English Intelligent Teaching Mode in Colleges and Universities Facilitated by Artificial Intelligence Technology

Abstract With the rapid development of artificial intelligence technology, its application in education has become increasingly widespread, especially in English teaching in colleges and universities. Using artificial intelligence technology to build an intelligent teaching mode can effectively improve the quality of teaching and students’ learning efficiency. The study adopts Bayesian algorithm and Bayesian-based learning tracking model (BKT and BF-BKT) as the main methods to optimize the teaching mode by analyzing learners’ mastery of knowledge points and behavioral performance. The results show that the maximum response time of the model is only 1038.59 milliseconds when the number of users is 120, proving the model’s efficiency in handling large-scale data. In addition, the intelligent teaching model positively impacted both teacher-student interaction and student learning ability. The teacher speech ratio decreased from 80.26% to 62.53%, and the students’ autonomy and participation increased significantly; the mean value of students’ learning ability in independent learning and critical thinking exceeded 4.00. The application of AI technology in teaching English in colleges and universities can significantly improve the quality of teaching and students’ learning effect.

Integration of Artificial Intelligence based on Electronic Information Engineering

Our analysis of the rapid development of core technologies in the new era of "Internet plus AI" is based on research into the applications of AI technology in the manufacturing sector in recent years. Next, we suggest novel approaches, methods, and configurations for intelligent manufacturing, as well as an architecture and technology system for intelligent manufacturing. In light of this, the purpose of this article is to examine artificial intelligence as it relates to Internet of Things technology in electronic information engineering. The goal is to increase people's material well-being and happiness by better optimizing artificial intelligence and IoT technology, mastering technical concepts, and applying them logically. To better simulate life and optimize information conditions, this paper analyses the experimental results through model construction. It also suggests ways to apply artificial intelligence and IoT technology to electronic information engineering. In conclusion, this research employs sixteen typical mechanics datasets to verify the correctness and generalizability of the method and concludes that it helps improve the usage of AI and IoT technologies.

Teaching Mathematics with the Assistance of an AI Chatbot to Enhance Mathematical Thinking Skills for High School Students

The paper introduces the concepts of thinking and mathematical thinking, emphasizing the significance of mathematical thinking in problem-solving and the development of mathematical skills. It elaborates on the process of mathematization, highlighting its role in fostering problem-solving abilities. Furthermore, the article discusses Teaching with the assistance of an AI Chatbot, the objectives of high school mathematics programs, and presents the Teaching Process in Mathematics with the assistance of an AI Chatbot to develop mathematical thinking skills for students. This process includes steps such as defining goals, logging into the AI Chatbot, identifying learning tasks, problem-solving, learning, application and experience, assessment, conclusion, analysis, inference, and mathematical problem-solving. The integration of the AI Chatbot is emphasized, creating a dynamic learning environment that supports students. The AI Chatbot not only provides knowledge but also stimulates curiosity and creativity, helping students understand and apply mathematics to real-world scenarios. The paper provides scientific insights into the application of AI technology in mathematics education, supporting the learning process and developing the mathematical thinking of high school students.

How does AI Technology Affect the Development of Physical Manufacturing Industry under the Background of Intelligent Economy

AI technology plays a positive role in promoting the development of physical manufacturing industry, which can improve production efficiency, reduce costs, improve product quality, innovate research and development capabilities, expand market opportunities and strengthen customer service. In the future, with the continuous development and application of AI technology, its potential will be further released, bringing more opportunities and challenges to the development of physical manufacturing.

Intelligent selection of healthcare supply chain mode - an applied research based on artificial intelligence.

Due to the inefficiency and high cost of the current healthcare supply chain mode, in order to adapt to the great changes in the global economy and public health, it is urgent to choose an effective mode for sustainable development of healthcare supply chain. The aim of this paper is to use artificial intelligence systems to make intelligent decisions for healthcare supply chain mode selection. Firstly, according to the economic benefits, social benefits and environmental benefits of healthcare supply chain, this paper identifies different healthcare supply chain modes in combination with artificial intelligence technology. Secondly, this paper presents the intelligent choice optimization method of healthcare supply chain mode based on deep reinforcement learning algorithm. Finally, the effect of artificial intelligence in healthcare supply chain mode selection is verified by simulation experiment. The experimental results show that healthcare supply chain mode selected by artificial intelligence is basically consistent with the target mode, while healthcare supply chain mode selected by the basic selection method, BP neural network method and big data method is different from the target mode, which indicates that AI has more advantages in the selection of medical supply chain mode. Therefore, we recommend the application of artificial intelligence to healthcare supply chain management. This study not only makes up for the ineffective problems of existing methods, but also makes up for the gaps in the application of AI technology in the field of healthcare supply chain. The scientific value of this paper is that the proposed framework and the artificial intelligence algorithm enrich the relevant theories of healthcare supply chain research and provide methodological guidance for intelligent decision-making of healthcare supply chain. At the same time, for medical enterprises, this research provides a new practical guideline for the application of artificial intelligence in the sustainable development and modern management of healthcare supply chain.

Effective and efficient content-based similarity retrieval of large lung CT images based on WSSLN model.

The in-depth combination and application of AI technology and medical imaging, especially high- definition CT imaging technology, make accurate diagnosis and treatment possible. Retrieving similar CT image(CI)s to an input one from the large-scale CI database of labeled diseases is helpful to realize a precise computer-aided diagnosis. In this paper, we take lung CI as an example and propose progressive content-based similarity retrieval(CBSR) method of the lung CIs based on a Weakly Supervised Similarity Learning Network (WSSLN) model. Two enabling techniques (i.e., the WSSLN model and the distance- based pruning scheme) are proposed to facilitate the CBSR processing of the large lung CIs. The main result of our paper is that, our approach is about 45% more effective than the state-of-the-art methods in terms of the mean average precision(mAP). Moreover, for the retrieval efficiency, the WSSLN-based CBSR method is about 150% more efficient than the sequential scan.

AI for Psychometrics: Validating Machine Learning Models in Measuring Emotional Intelligence with Eye-Tracking Techniques.

AI, or artificial intelligence, is a technology of creating algorithms and computer systems that mimic human cognitive abilities to perform tasks. Many industries are undergoing revolutions due to the advances and applications of AI technology. The current study explored a burgeoning field-Psychometric AI, which integrates AI methodologies and psychological measurement to not only improve measurement accuracy, efficiency, and effectiveness but also help reduce human bias and increase objectivity in measurement. Specifically, by leveraging unobtrusive eye-tracking sensing techniques and performing 1470 runs with seven different machine-learning classifiers, the current study systematically examined the efficacy of various (ML) models in measuring different facets and measures of the emotional intelligence (EI) construct. Our results revealed an average accuracy ranging from 50-90%, largely depending on the percentile to dichotomize the EI scores. More importantly, our study found that AI algorithms were powerful enough to achieve high accuracy with as little as 5 or 2 s of eye-tracking data. The research also explored the effects of EI facets/measures on ML measurement accuracy and identified many eye-tracking features most predictive of EI scores. Both theoretical and practical implications are discussed.

Retracted: The Application of AI Technology in GPU Scheduling Algorithm Optimization

Retracted: The Application of AI Technology in GPU Scheduling Algorithm Optimization

Effect of Adding Coconut Water (Cocus viridis) on Liquid Semen Quality of Kacang Goats (Capra aegagrus hircus) Stored at 4-5° C

The best semen quality is necessary for successful Artificial Insemination. Increasing population of Kacang goat, which is a native Indonesian goat breed can reach with the application of AI technology. It can support the suffice of national meat demand. The purpose of this study was to determine the effect of adding coconut water (CW) in the Skim Yolk Diluent (SYD) and storage time at a cold temperature of 4-5 C on the quality of liquid semen of Kacang goat. The research material was four Kacang goats aged 1 - 1.5 years, SYD, and coconut water. The research method was an experiment with a factorial randomized block design (RBD) consisting of two factors. The first factor is the addition of coconut water in SYD (D), namely D0 = 100% SYD + 0% CW; D1= 30% SYD + 70% CW; D2= 20% SYD + 80% CW; D3= 10% SYD + 90% CW. The second factor is the storage time of liquid cement at a temperature of 4-5°C (H), namely H0 = 0 days; H1= 1 day; H2 = 2 days, and H3 = 3 days. The treatment was repeated 10 times. Data were analyzed by Anova and further test using Duncan's multiple distance test. The results showed that the combination treatment showed a significantly different interaction effect (P<0.05) on the percentage of motility and abnormalities and the highly significant different interaction effect (P<0.01) on the percentage of spermatozoa viability. The best mean of motility, viability and abnormality was found in the D3H0 treatment. The conclusion is that the addition of coconut water in SYD can be done up to 90% with the time storage at 4-5ºC cold for 3 days because it is still able to maintain the quality of the Kacang goat liquid semen with a motility percentage more than 40%.

Application of ChatGPT in Improving Operational Efficiency in the Context of Entrepreneurship

In the ever-evolving digital era, the use of AI has become a major focus in various fields. One example is the application of AI technology in the context of entrepreneurship. Entrepreneurship is an activity that involves developing, launching, and managing new or innovative ventures. In this study, the main objective is to explore the application of ChatGPT in improving operational efficiency in the context of entrepreneurship. The focus of this study is primarily qualitative. Methods for gathering data include paying close attention to detail while viewing and recording data, and then using analytical techniques such as data reduction, visualisation, and inference to draw conclusions. The study results show that the application of ChatGPT in improving operational efficiency in an entrepreneurial context offers a range of significant benefits. In the areas of customer service, marketing and sales, and internal management, ChatGPT can help companies improve customer satisfaction, optimise business processes, save time and resources, and increase productivity and collaboration between teams.

Research on the Construction of Curriculum System of Asset Appraisal Major under AI Automatic Valuation Trend

With the application of AI technology in the asset appraisal industry, an asset appraisal platform based on online data collection, conversion and automatic valuation based on artificial intelligence has been established, which can greatly improve the evaluate efficiency of asset appraisal professionals. Due to the late start of asset appraisal major in universities in China, the problem of imperfect curriculum system of asset appraisal major is gradually exposed. Colleges and universities need to reform the current curriculum system, add more courses related to AI automatic valuation technology, and add more practical content, to help students master more evaluation methods, and cultivate new compound asset evaluation talents.

AI technology application and employee responsibility

Employees are important stakeholders of firms, and employee responsibility is a crucial dimension of corporate social responsibility. This study employed a multivariable linear regression model to analyze the impact of AI technology on the variation in employee responsibility. We also utilized multiple methods, such as propensity score matching and alternative indicator analysis, to ensure the robustness of the research results. We theorized and found that the application of AI technology has a negative effect on employee responsibility, with supervision cost partially mediating the relationship between AI technology application and employee responsibility. Moreover, the negative relationship between AI technology application and employee responsibility decreases as the level of product market competition in which the firm operates increases, and it is stronger in government-controlled firms than in privately controlled firms. We also found that AI technology application and employee responsibility can improve firm productivity, and employee responsibility has a significant positive impact on innovation output and innovation efficiency, while the application of AI technology does not significantly impact innovation output and innovation efficiency. Our study contributes to research on the impact of AI technology in the workplace and has important implications for organizational practices regarding the application of AI technology and employee responsibility.

Design and Implementation of Enterprise Financial Decision Support System Based on Business Intelligence

Purpose: Business intelligence and decision support systems are now recognized as critical enterprise infrastructure. Data is increasingly being used by business enterprises to react to key operational and strategic operations of their customers, markets, and stakeholders. Theoretical framework: Business intelligence has advanced as the volume of data generated by smart technologies and the Internet has increased exponentially. Design/Methodology/Approach: When using AI in the business world, privacy concerns arise when sensitive data is transmitted to a third-party vendor who has no connection to the company. Financial decision support data is managed by these AI service providers. Even while it may seem like a drawback, artificial intelligence technology actually has several advantages. Findings: The results of this research show that a network can improve the financial management of a corporation. Using many applications of AI technology helps bring down the overall cost of operations. When it comes to financial services, both the number of IT workers needed and the number of necessary pieces of hardware (servers) can be reduced, resulting in a marginal drop in capital expenditures. Research, Practical & Social implications: When it comes to financial services, both the number of IT workers needed and the number of necessary pieces of hardware (servers) can be reduced, resulting in a marginal drop in capital expenditures. It is now simpler and quicker to get your hands on relevant financial information, which should lead to greater efficiency. Originality/value: With our proposed approach, the accuracy of financial decision support in company increases to 99.84% from 88.94%, while the implementation time and cost are reduced.

Application of AI Technology in Modern Digital Marketing

Application of AI Technology in Modern Digital Marketing

AI revolution in healthcare and medicine and the (re-)emergence of inequalities and disadvantages for ageing population.

AI systems in medicine and healthcare are being extensively explored in prevention, diagnosis, novel drug designs and after-care. The application of AI technology in healthcare systems promises impressive outcomes such as equalising healthcare, reducing mortality rate and human error, reducing medical costs, as well as reducing reliance on social services. In the light of the WHO "Decade of Healthy Ageing", AI applications are designed as digital innovations to support the quality of life for older persons. However, the emergence of evidence of different types of algorithmic bias in AI applications, ageism in the use of digital devices and platforms, as well as age bias in digital data suggests that the use of AI might have discriminatory effects on older population or even cause harm. This paper addresses the issue of age biases and age discrimination in AI applications in medicine and healthcare systems and try to identify main challenges in this area. It will reflect on the potential of AI applications to amplify the already existing health inequalities by discussing two levels where potential negative impact of AI on age inequalities might be observed. Firstly, we will address the technical level of age bias in algorithms and digital datasets (especially health data). Secondly, we will discuss the potential disparate outcomes of automatic decision-making systems (ADMs) used in healthcare on the older population. These examples will demonstrate, although only partially, how AI systems may create new structures of age inequalities and novel dimensions of exclusion in healthcare and medicine.

The Application of AI Technologies in English Education in Industry 4.0

The Application of AI Technologies in English Education in Industry 4.0

РОЛЬ ТЕХНОЛОГИЙ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА В ЦИФРОВОЙ ТРАНСФОРМАЦИИ ТРАНСПОРТНОЙ ОТРАСЛИ

Artificial Intelligence is becoming an increasingly common technology in various fields of endeavour. One of the areas where its use is finding increasing application is in the transport industry. The development of AI in the transport industry should improve the safety, efficiency and comfort of journeys. The article presents the results of the research on the application of AI technology in the transport and logistics industry. The advantages, attractiveness and significance of the implementation of this technology for the competitiveness of transport companies are considered. The authors’ attention is focused on the problems of using artificial intelligence for effective management of transport infrastructure objects.

What is Missing in XAI So Far?

With the perspective on applications of AI-technology, especially data intensive deep learning approaches, the need for methods to control and understand such models has been recognized and gave rise to a new research domain labeled explainable artificial intelligence (XAI). In this overview paper we give an interim appraisal of what has been achieved so far and where there are still gaps in the research. We take an interdisciplinary perspective to identify challenges on XAI research and point to open questions with respect to the quality of the explanations regarding faithfulness and consistency of explanations. On the other hand we see a need regarding the interaction between XAI and user to allow for adaptability to specific information needs and explanatory dialog for informed decision making as well as the possibility to correct models and explanations by interaction. This endeavor requires an integrated interdisciplinary perspective and rigorous approaches to empirical evaluation based on psychological, linguistic and even sociological theories.

ARTIFICIAL INTELLIGENCE IN HEALTH CARE AND THE OVIEDO CONVENTION

Applications of AI technology are being developed in healthcare. The prospects for the deployment of targeted AI applications in medical treatment, clinical trials, drug research, and public health are promising and groundbreaking.
 But the deployment of these new technologies in healthcare also raises legal questions, especially from a human rights perspective. This contribution therefore focuses on the human rights analysis of AI applications in healthcare and how these applications relate to the Oviedo Convention.