Intelligent Technology Research Articles

Research on Financial Investment Risk Assessment Techniques and Applications

In recent years, the financial markets have undergone rapid development and significant volatility, leading to a pronounced urgency and complexity in investment risk assessment. This study explores the technologies and applications of financial investment risk evaluation, offering an in-depth analysis of the theoretical foundations and practical operations of quantitative, qualitative, and hybrid assessment methodologies. Traditional quantitative techniques, such as the Value at Risk (VaR) model, provide crucial objective data support, while qualitative approaches enrich the breadth of risk identification through expert opinions and seasoned experience. Hybrid methods synergistically combine the strengths of both, adapting to the intricacies of the market environment. The integration of big data and artificial intelligence technologies injects innovative momentum into risk assessment, enabling more precise and timely risk monitoring. Case applications span multi-layered risk management strategies within banks, insurance companies, and hedge funds, offering valuable insights for diverse financial institutions. The study posits that efficient risk assessment relies not only on technological advancements but also necessitates consideration of market dynamics and regulatory environment fluctuations. Continual innovation and practical optimization are pivotal in addressing future challenges.

Navigating English Learning with AI: A Qualitative Study of University Students Experiences

The accelerated development of Artificial Intelligence (AI) technologies has had a substantial impact on educational practices, particularly in the field of English education. This study investigateshe experiences of university students at a UIN Fatmawati Sukarno Bengkulu in the process of navigating English learning through AI. The study examines the challenges and benefits those students experience when utilizing the most frequently used AI tools, as well as their perceptions of these technologies. Interviews with nine students in the fifth semester of the English program at UIN Fatmawati Sukarno Bengkulu are conducted using a qualitative methodology. The results indicate that students have a positive attitude toward AI in the context of English learning and employ a variety of AI tools to resolve various aspects of language acquisition. This study is a unique exploration of the manner in which university students simultaneously incorporate multiple AI tools in their English learning, providing new insights into the role of AI in promoting self-directed learning and practical language application. The study offers new insights into the transformative potential of AI in supporting students’ autonomous learning journeys while learning English by providing a comprehensive view of AI’s role in English education.

Revolutionizing Sports Education using AI & ML

In the realm of sports education and performance analysis, there exists a pressing need to overcome barriers such as geographical limitations, cost constraints, and time constraints inherent in traditional teaching methodologies. In response to these challenges, this paper presents a novel sports education system leveraging artificial intelligence (AI) technologies. This allinclusive system allows for easy access to sports academies and training facilities based on geographic proximity by introducing an innovative teaching platform driven by AI and GPS integration. Moreover, it offers an extensive library of sports laws, sophisticated strategies, and professional advice, encouraging ongoing skill development. Setting goals and closely observing performance are made easier by the system's integration of AI-driven forecasts, such as victory probabilities. The central aim of this initiative is to redefine the landscape of sports education by offering a convenient, cost-effective, and highly efficient solution accessible to individuals at all proficiency levels. In addition to its educational advantages, the system is poised to make significant contributions to sports analytics, supplying extensive data and insights for both researchers and practitioners. This proposal advocates a progressive approach that moves beyond traditional methods, heralding a new era in sports education and performance analytics

Teaching and AI in the postdigital age: Learning from teachers’ perspectives

This interview-based study aimed to understand how teachers make sense of their work and themselves in relation to artificial intelligence (AI) and other digital technologies, and was conceived as a means of learning with and from teachers. Navigating recent AI developments raised questions about thinking, creativity, production, and the meaning and value of humanity, along with more practical concerns regarding instruction and assessment. Creating policy and ongoing teacher education opportunities that recognize teachers’ capacities for professional judgement while also providing support would encourage thoughtful and creative uses of AI, and avoid pressuring teachers to thoughtlessly rush forward with AI implementation.

Digital Technologies in the National Cadastre System of Uzbekistan: Issues of Legal Regulation

Objective: to critically analyze the state of national legislation of Uzbekistan in terms of legal regulation of digitalization and the use of artificial intelligence in the cadastral sphere.Methods: the research is based on such methods of scientific cognition as formal-legal and comparative-legal analysis, induction and deduction.Results: the provisions that regulate digitalization and the use of artificial intelligence in the cadastral sphere were analyzed, legal gaps were identified. It was determined that the practical application of artificial intelligence technologies outpaces its legal regulation. The shortcomings of legal regulation in this sphere were noted (lacking legal definition of the legal status of artificial intelligence in the national legislation; regulation of business entities’ participation in the management of artificial intelligence, etc.). The said shortcomings hinder its full application and harmonization with traditional sources of cadastral information. The author substantiated the need for universal digitization of the national cadastre and predicts the possibility of wider application of artificial intelligence in the natural-resource cadastral system. It is argued that the existing system in its current state may lead to wrong decisions and cadastral errors, hence, it is necessary to improve the legal regulation of cadastre.Scientific novelty: for the first time the results of the national cadastre digitization were assessed. Forecasts were given about the possibility of using artificial intelligence in this area, subject to further improvement of legal regulation. The latter is fundamentally important for reforming the cadastral system, since the technological basis of this system does not fully meet the needs of the digital economy.Practical significance: it is due to the lack of legal regulation of the artificial intelligence concept and legal status in the national legislation, as well as a unified approach to the cadastral system digitalization. Modern technologies are actively used in practice, but lack a sufficient legal basis. The main conclusions, proposals and recommendations of the study can be a basis for further improvement of the legal framework of Uzbekistan in terms of the application of artificial intelligence technologies.

Implementation of Artificial Intelligence Technology-Based Learning Media at SD Negeri Kotagede 1 Yogyakarta

In the digital era, the field of education is witnessing the transformation that occurs through the integration of artificial intelligence (AI). With artificial intelligence's (AI) potential to revolutionize various sectors, it presents itself as a material or tool that can enhance the teaching and learning experience. Its features align with our thinking, enabling us to progress according to our desired content. Artificial intelligence (AI) is today's most important tool in education. Artificial intelligence (AI) plays a crucial role in enabling the use of AI-based learning media, thereby facilitating the learning process in education. Artificial intelligence (AI)--based learning media in education will aid teachers and students in learning. This study aims to provide insight to all of us regarding the implementation of learning media based on artificial intelligence (AI) technology at SD Negeri Kotagede 1 Yogyakarta. This study employs a descriptive-qualitative approach. In the current educational landscape, particularly at SD Negeri Kotagede 1 Yogyakarta, artificial intelligence (AI) plays a crucial role. Artificial intelligence (AI) can facilitate the learning process flow by using learning media based on artificial intelligence technology. Teachers can utilize artificial intelligence to design programs and learning processes, while students can enhance their comprehension of the material and cultivate their critical thinking skills. Implementing learning media based on artificial intelligence (AI) technology can benefit educational institutions in a more interesting, innovative, effective, and creative learning process.

Advances and Prospects of PID Controller in Mechanical Field: From Traditional Tuning to Intelligent Optimization

Abstract. The extensive use of PID controllers in the mechanical fieldparticularly in robots and other mechanical systemsis covered in this study. In these sectors, PID controllers have become the most popular control technology due to their straightforward design and simplicity of use. PID controller performance in nonlinear complex systems is explored, along with stability and adaptive adjustment, by comparing the conventional and intelligent PID tuning methods. According to the research, control performance can be greatly enhanced by merging PID controller with intelligent technologies like fuzzy logic and genetic algorithms. These results point to the possible use of PID-based control in numerical control systems in the future. PID controllers' automatic tuning capabilities have garnered significant attention in the industrial sector. Future research will focus on the automatic tuning of PID controller to further optimize its performance and broaden its application range.

Leveraging artificial intelligence in Regulatory Technology (RegTech) for financial compliance

Abstract. The rapid development of Regulatory Technology (RegTech) has introduced new methods to handle and simplify the compliance and regulatory issues surrounding financial services and products. Combining artificial intelligence (AI) with this trend is an effective way of strengthening financial services, making them safer and more convenient. The current AI technologies incorporated within RegTech applications improve the efficiency of compliance with rules and regulations, and contribute to the development and implementation of smart technology, including automated regulatory reporting, proven and trustworthy KYC processes, and reduced compliance costs. This paper presents the application of intelligent technology, such as machine learning, deep learning, natural language processing, and smart regulatory frameworks, to build modern, intelligent workflows, dynamically control policies, and instantaneously monitor transactions. We employ empirical economic data, evidenced by realistic case studies, to demonstrate the benefits brought on by intelligent technology to financial institutions, including quicker compliance with regulatory regimes, decreased operational risk, and increased transparency and accountability. Through analysing figures offered in various cases, we show the transformed compliance landscape created by RegTech, how it becomes a solution for the diverse challenges affecting financial sectors on a global scale, and how is it going to impact the whole field of financial services in the future..

S-RAF: A Simulation-Based Robustness Assessment Framework for Responsible Autonomous Driving

As artificial intelligence (AI) technology advances, ensuring the robustness and safety of AI-driven systems has become paramount. However, varying perceptions of robustness among AI developers create misaligned evaluation metrics, complicating the assessment and certification of safety-critical and complex AI systems such as autonomous driving (AD) agents. To address this challenge, we introduce Simulation-Based Robustness Assessment Framework (S-RAF) for autonomous driving. S-RAF leverages the CARLA Driving simulator to rigorously assess AD agents across diverse conditions, including faulty sensors, environmental changes, and complex traffic situations. By quantifying robustness and its relationship with other safety-critical factors, such as carbon emissions, S-RAF aids developers and stakeholders in building safe and responsible driving agents, and streamlining safety certification processes. Furthermore, S-RAF offers significant advantages, such as reduced testing costs, and the ability to explore edge cases that may be unsafe to test in the real world.

MeDi‐TODER: Medical Domain‐Incremental Task‐Oriented Dialogue Generator Using Experience Replay

ABSTRACTArtificial intelligence (AI) technology has brought groundbreaking changes to the healthcare domain. Specifically, the integration of a medical dialogue system (MDS) has facilitated interactions with patients, identifying meaningful information such as symptoms and medications from their dialogue history to generate appropriate responses. However, shortcomings arise when MDS lacks access to the patient's cumulative history or prior domain knowledge, resulting in the generation of inaccurate responses. To address this challenge, we propose a medical domain‐incremental task‐oriented dialogue generator using experience replay (MeDi‐TODER) that applies the continual learning technique to the medical task‐oriented dialogue generator. By strategically sampling and storing exemplars from previous domains and rehearsing it as it learns, the model effectively retains knowledge and can respond to the novel domains. Extensive experiments demonstrated that MeDi‐TODER significantly outperforms other models that lack continual learning in both natural language generation and natural language understanding. Notably, our proposed method achieves the highest scores, surpassing the upper‐class benchmarks.

The Frontier Exploration and Application Prospect of Data Science

Abstract. In the era of information explosion, data floods in like a relentless tide, shaping peoples world every minute and second. Data science, the most prominent discipline of our time, wields unprecedented power to propel the development of industries across the board, serving as a bridge that connects the past with the future, granting insights into the present, and predicting trends. This article delves into the allure of data science, unveiling how it has become the key to unlocking the future world. Furthermore, this review explores in detail the core concepts, key technologies, and broad applications of data science. Through in-depth research on data acquisition, processing, analysis, and visualization, it reveals the innovative applications and significant impacts of data science in multiple fields such as business intelligence, healthcare, and financial technology. At the same time, the future trends and challenges of data science are prospectively analyzed, which provides a valuable reference for further promoting the research and practice in this field.

Occupational therapy in the space of artificial intelligence: Ethical considerations and human-centered efforts

Background Artificial intelligence (AI) technology is constantly and rapidly evolving and has the potential to benefit occupational therapy (OT) and OT clients. However, AI developments also pose risks and challenges, for example in relation to the ethical principles of OT. One way to support future AI technology aligned with OT ethical principles may be through human-centered AI (HCAI), an emerging branch within AI research and developments with a notable overlap of OT values and beliefs. Objective To explore the risks and challenges of AI technology, and how the combined expertise, skills, and knowledge of OT and HCAI can contribute to harnessing its potential and shaping its future, from the perspective of OT’s ethical values and beliefs. Results Opportunities for OT and HCAI collaboration related to future AI technology include ensuring a focus on 1) occupational performance and participation, while taking client-centeredness into account; 2) occupational justice and respect for diversity, and 3) transparency and respect for the privacy of occupational performance and participation data. Conclusion and Significance There is need for OTs to engage and ensure that AI is applied in a way that serves OT and OT clients in a meaningful and ethical way through the use of HCAI.

Impacts of interacting with an AI chatbot on preservice teachers' responsive teaching skills in math education

AbstractBackgroundArtificial Intelligence (AI) technologies offer unique capabilities for preservice teachers (PSTs) to engage in authentic and real‐time interactions using natural language. However, the impact of AI technology on PSTs' responsive teaching skills remains uncertain.ObjectivesThe primary objective of this study is to examine whether interaction with a responsive AI‐based chatbot that acts as a virtual student improves pre‐service teachers' noticing abilities. The second objective is to compare how the presence or absence of chatbot responses affects changes in PSTs' questioning practices. Finally, the third objective is to investigate how the experience of interacting with the responsive virtual student affects PSTs' perceptions of the effectiveness of their questioning, their satisfaction with the interactions, and their confidence about interacting with a real student compared to the non‐responsive chatbot.MethodsA randomised controlled pre‐ and post‐test design was used with 50 PSTs. PSTs' noticing, interaction with the chatbot, and post‐survey data were collected, and a t‐test was conducted to examine significant differences by group.Results and ConclusionIn the experimental group, the virtual student responded to PSTs' questions, while in the control group, she did not. Notable differences were observed in their questioning practices.TakeawaysOverall, AI‐based chatbots hold promise for enhancing PSTs' responsive teaching skills. Future research is needed to examine the long‐term impact of responsive chatbot use on PSTs' noticing skills.

Advances in flight control systems for modern commercial aircraft

Abstract. In consequence of the accelerated evolution of aviation technology, the flight control systems of commercial aircraft have undergone substantial technological advancement and system optimization. This paper presents a comprehensive analysis of the recent advancements and future trends in flight control systems for commercial aircraft. The fundamental concepts and historical evolution of flight control systems are delineated, with a particular emphasis on the evolution of autopilot systems and the technological advancements of flight control systems (FCS). Furthermore, it examines innovations in flight control algorithms, including adaptive control and intelligent algorithms, and investigates the impact of fault-tolerant design on flight safety. In terms of system integration, the integration of flight control systems with navigation and communication systems, as well as performance enhancements resulting from system optimization, is explored. In addition, it examines the potential impact of intelligence and networking on future flight control systems, with a particular focus on the prospects for the application of artificial intelligence, quantum computing, and new material technologies. The synthesis of these areas provides a systematic understanding of the technological evolution and future development of flight control systems for commercial aircraft.

A Review of Data-Driven Intelligent Monitoring for Geological Drilling Processes

The exploration and development of resources and energy are fundamental to human survival and development, and geological drilling is a key method for deep resource and energy exploration. Intelligent monitoring technology can achieve anomaly detection, fault diagnosis, and fault prediction in the drilling process, which is crucial for ensuring production safety and improving drilling efficiency. The drilling process is characterized by complex geological conditions, variable working conditions, and low information value density, which pose a series of difficulties and challenges for intelligent monitoring. This paper reviews the research progress of the data-driven intelligent monitoring of geological drilling processes, focusing on the above difficulties and challenges. It mainly includes multivariate statistics, machine learning, and multi-model fusion. Multivariate statistical methods can effectively handle and analyze complex geological drilling data, while machine learning methods can efficiently extract key patterns and trends from a large amount of geological drilling data. Multi-model fusion methods, by combining the advantages of the first two methods, enhance the ability to handle complex multivariable and nonlinear problems. This review shows that existing research still faces problems such as limited data processing capabilities and insufficient model generalization capabilities. Improving the efficiency of data processing and the generalization capability of models may be the main research directions in the future.

Teledentistry Integration: Revolutionizing Dental Insurance Through Technological Innovation

This article examines the transformative impact of teledentistry on the dental insurance industry, exploring how telecommunications technology is revolutionizing dental care delivery, access, and insurance. It discusses the expansion of dental care accessibility, streamlining of insurance processes, enhancement of preventive care, and the generation of data-driven insights through teledentistry. The article also addresses privacy and security considerations, presents case studies of successful implementations, and explores future prospects and innovations in the field. By analyzing the integration of teledentistry with artificial intelligence and wearable technology, the article highlights the potential for more proactive, personalized, and accessible dental care, while emphasizing the need for continued research and development to fully realize these benefits.

Implementation of Committee Partnerships on AI-Based School Policies at Public Junior High School

In the increasingly sophisticated digital era, artificial intelligence (AI) technology has significantly changed various fields, including education. In Indonesia, secondary schools have begun implementing AI technology to improve the quality of teaching and school management. Implementing this technology includes using AI-based systems for personalized learning, student data analysis, and more efficient school administration management. Implementing AI-based policies requires a strong partnership between the school committee and the school. This includes monitoring technology implementation, providing teacher training, and involving parents in the technology-based learning process. This study aims to identify and analyze the role of partnerships between school committees and schools in implementing AI-based policies at SMP Negeri 3 Tanjungsari. To ensure effective policy implementation, various stakeholders, including school committees, must support advancing AI technology in education. This study employs a qualitative approach, incorporating a case study method. It obtained the collected data through in-depth interviews, participant observation, and document analysis. The study results indicate that strong partnerships between school committees and schools play a significant role in supporting the implementation of AI policies. However, some challenges are still faced, such as the committee's lack of understanding of AI technology. This study also offers strategies to improve the effectiveness of these partnerships, including training and enhancing communication between the committee and the school. These findings significantly contribute to developing educational policies that are more adaptive to technological advances.

Research on autonomous driving technology in intelligent transportation systems

Abstract. The convergence of scientific and technological advancement with the acceleration of urbanization has resulted in a notable intensification of the issue of traffic congestion. In this context, the development of autonomous driving technology has emerged as a pivotal area of focus for future transportation systems. Therefore, this paper presents a review of the current status of automatic driving technology in intelligent transportation systems, based on methods such as literature, data analysis and case studies. Furthermore, it delves into the evolution, applications, challenges and solutions of automated driving technologies in intelligent transport systems, and presents forward-thinking insights into the future development of intelligent transportation. As autonomous driving technology continues to evolve, the integration of deep reinforcement learning and other advanced technologies will facilitate the advancement of intelligent vehicle human-machine collaborative decision-making technology. It is imperative that the construction technology of safety-critical scenarios be reinforced in order to enhance the interpretability of algorithmic models and the real-time nature of scenario generation. All parties need to collaborate to promote the innovation and improvement of autonomous driving technology, achieve widespread application and sustainable development, and create a better travelling environment.

Development of Intelligent Construction Robots for In-situ Lunar Resource Utilization

Abstract: With the development of technologies such as 3D printing and artificial intelligence, robotic lunar construction has gradually become a reality. In recent years, many countries have conducted research on lunar construction, among which lunar in-situ resource utilization construction is the most promising option for lunar construction, and intelligent robot construction is the main method of in-situ resource utilization construction. This paper analyzes the trend of intelligent construction and the necessity of lunar construction, and concludes that lunar construction robots have great development prospects and value. Using "ISRU, intelligent construction robot, 3D printing" as keywords, using the method of literature analysis, literature retrieval is conducted on China National Knowledge Infrastructure and Google Scholar databases, and the types of lunar bases, the acquisition of lunar resources, the classification of intelligent construction robots, and the 3D printing technology and Fully adaptable robot assembly and construction technology in lunar in-situ resource utilization are analyzed. The concept, classification, function, auxiliary 3D printing technology and materials required for 3D printing are analyzed in detail. The assembled mortise and tenon structure, fully adaptable assembly robot technology and underground construction technology are described in detail. The intelligent construction technology involved in lunar in-situ resource utilization construction (ISRU) and how to adapt to the lunar environment for construction are systematically analyzed, and the challenges faced in realizing robotic lunar construction are briefly outlined. It provides ideas for scholars studying intelligent construction robots.

Artificial intelligence in physical education: comprehensive review and future teacher training strategies

Artificial intelligence (AI) technology is deeply changing our lives and provides impetus for improving production and living efficiency as an important emerging tool. Digitalization and intelligent development have also become the development direction of the sports industry, bringing new requirements to the transformation of physical education (PE) and the improvement of the quality of PE teachers. PE is an important part of the public health system, and AI can deeply participate in the formulation of teaching strategies, the tracking of teaching processes and the evaluation of teaching results, effectively improving the quality of teaching. Research on the application of AI technology in PE has been carried out. This paper comprehensively reviews the existing research and conducts a comprehensive analysis of the research progress and status. The potential application areas of AI in PE are discussed to better promote the intelligent and digital upgrading of PE. We found that the research on the application of AI in PE is still in its early stages, and the research content needs to be strengthened in terms of breadth and depth. Furthermore, this paper analyzes the challenges faced by PE teacher development and training in the context of educational transformation in the era of AI, and explores the necessary skills and knowledge related to AI technology that future PE teachers should master in order to effectively achieve the improvement of teaching level and the sustainable development of public health system. The review of this paper provides valuable guidance for educators and policymakers to formulate high-quality teacher development and training mechanisms, and provides a new reference for the application and development of AI in sports.