AI Engineering Research in Software Engineering Venues

Machine Tools’ Running State Monitoring in the Learning Factory—Based on Machine Learning Method and Vibration Data

The article is devoted to the study of the application of artificial intelligence technologies in law enforcement activities in Ukraine and the world. The purpose of the article is to analyze the international and domestic experience of using digital technologies in law enforcement activities, to identify the shortcomings of the legal regulation of the use of artificial intelligence in this area, to provide proposals for its improvement in Ukraine. It was found that one of the countries that is actively expanding the use of artificial intelligence and successfully introducing relevant technologies into public administration is China. The artificial intelligence system which is used in China called «Zero Trust». The purpose of using this system is to prevent the commission of corruption offenses. It is emphasized, that the disadvantage of the «Zero Trust» system is that artificial intelligence, identifying the cause of corruption, does not indicate the algorithms and principles of this process. At the same time, the experience of using artificial intelligence in the field of preventing and combating corruption in Ukraine is considered when carrying out automated verification of persons declarations of authorized to perform state and local government functions. Ways of improving legal regulation when conducting financial control of declarations using artificial intelligence technologies are proposed. It has been found that artificial intelligence is widely used in the USA to predict the prevalence and state of crime. It was emphasized that Ukraine also has experience in the application of artificial intelligence technologies in law enforcement activities. Artificial intelligence is used in the development and implementation of departmental specialized intelligent software, the implementation of operative and investigative actions (for the recognition of video objects observation by comparing images in social networks, etc). It was concluded that artificial intelligence and digital technologies help to quickly process large volumes of information in the investigation and prevention of criminal activity. Modern developments in the field of artificial intelligence and advanced digital technologies, which are implemented in foreign countries to prevent and fight crime, are of great importance for the improvement of legal regulation in this field in Ukraine.

In addition to creativity, modern landscape design also needs some auxiliary tools to predict the design effect, so as to ensure the design effect before the completion of the landscape. With the development of computer network and electronic information technology, human society has entered the information age, and artificial intelligence technology has been applied to all walks of life. With the continuous development of artificial intelligence, artificial intelligence has existed in all aspects of our lives and has a great impact on our lives. At the same time, through the achievements in recent years, artificial intelligence gradually affects other fields such as design. Therefore, combined with the current situation of landscape design auxiliary system in China, this paper introduces artificial intelligence and information technology into it, and makes the landscape design auxiliary system get further development with the help of artificial intelligence and information technology. This paper first introduces artificial intelligence, analyzes the advantages and development trend of automatic informatization of landscape design auxiliary system, and finally discusses the application of artificial intelligence technology in landscape design auxiliary system.

This study presents internet of things (IOT) and artificial intelligence technologies that are critical in reducing the harmful effects of this illness and assisting its recovery. It explores COVID-19’s economic impacts before learning about new technologies and potential solutions. The research objective was to propose a solution for self-diagnosis, self-monitoring, and self-management of COVID-19 with personal mobiles and personal data using cloud solutions and mobile applications with the help of an intelligent IoT system, artificial intelligence, machine learning, and 5G technologies. The proposed solution based on self-diagnosis without any security risk for users’ data with low cost of cloud-based data analytics by using handsets only is an innovative approach. Since the COVID-19 outbreak, the global social, economic, religious, and cultural frameworks and schedules have been affected adversely. The fear and panic associated with the new disease, which the world barely knew anything about, amplified the situation. Scientists and epidemiologists have traced the first outbreak of COVID-19 at Wuhan, China. A close examination of the genetic makeup of the virus showed that the virus is zoonotic, meaning that the virus changed hosts from animals to humans. The uncertainty associated with the above features and characteristics of the virus, as well as the high mortality rates witnessed in many parts of the globe, significantly contributed to the widespread global panic that brought the world to a standstill. Different authorities and agencies associated with securing the public have implemented different means and methods to try and mitigate the transmission of the infection as scientists and medical practitioners work on remedies to curb the spread of COVID-19. Owing to different demographics, different parts of the globe have attempted to effectively implement locally available resources to efficiently fight and mitigate the adverse effects of the COVID-19 pandemic. The general framework provided by the World Health Organization (WHO) has been implemented or enhanced in different parts of the globe by locally available resources and expertise to effectively mitigate the impact of COVID-19. There is currently no effective vaccine for COVID-19, but new technology can be available within weeks to reduce the spread of the disease; current approaches such as contact tracing and testing are not secure, and the cost of testing is high for end users. The proposed solution based on self-diagnosis without any security risk for users’ data with low cost of cloud-based data analytics functions by using an intelligent internet of things (IOT) system for collecting sensors data and processing them with artificial intelligence to improve efficiency and reduce the spread of COVID-19.

Art education has undergone significant transformation in the era of digitalization. With the advancement of Artificial Intelligence (AI) technology, there is tremendous potential to enhance the art learning experience. This research aims to elucidate how AI technology can be effectively utilized to improve art education in the context of digitalization. The study aims to introduce AI technology and explore its potential applications in enhancing the art learning experience. In the context of art learning experience, AI technology can provide broader access to digital art collections, online galleries, and virtual museums. Students can explore various artworks and cultures through digital platforms, thereby enriching their understanding and appreciation of art. The research findings reveal that AI technology can offer personalized guidance to students in developing their artistic skills. Intelligent AI systems can analyze students' artworks, provide tailored suggestions, and assist in enhancing their technical and creative abilities. In conclusion, the integration of AI technology in art education holds immense potential to elevate students' learning experiences. By expanding access, providing personalized guidance, and creating interactive experiences, AI technology enriches art learning in the era of digitalization. This is expected to provide greater insights and understanding of how AI technology can be harnessed to enhance the art learning experience in the context of digitalization. By optimizing the potential of AI, art education can become more inclusive, personalized, and engaging.

Routing protocols that support energy efficiency and Quality of Service (QoS) in wireless sensor networks (WSNs) are continuously evolving. In particular, many studies are being conducted on protocols that apply reinforcement learning algorithms in which agents learn the optimal path according to network conditions to maximize energy consumption and network lifetime, intelligent clustering protocols that automatically cluster sensor nodes and select cluster heads (CHs) to minimize energy consumption, and dynamically adjust routing paths based on real-time monitoring of traffic load, energy balance, and network failures. In addition, studies are being conducted to support multiple QoS requirements, such as delay, bandwidth, and reliability, by integrating AI technology with IoT communication protocols. In this paper, the current trends and future directions of routing protocols that support energy efficiency and QoS by utilizing artificial intelligence (AI), machine learning (ML), and other hybrid AI technologies in WSNs are described.

In an era where artificial intelligence (AI) technology is increasingly penetrating various aspects of life, including education, it is important to understand its impact on students' social relationships. These changes raise questions about how interactions between students and teachers are affected by AI Technology. This research aims to investigate the impact or artificial intelligence on students' social relationships in an educational environment. The focus is on understanding changes in interactions between students, student-teacher interaction, as well as broader implications for social dynamics inside the classroom and outside the classroom. The research method used is a literature review which uses data collections sources that are relevant to this research, which can be in books, megazines and other print media, or can be obtained from photos and videos. The research results show that artificial intelligence technology has a complex impact on students' social relationships. Although it can improve efficiency and learning outcomes, AI technology can also reduce social inequality, and create excessive dependence on technology. Educators and policymakers need to carefully consider the use of AI technology in education to ensure that positive impacts are maximized, while negative impacts are minimized.

The acceptance of technology at the higher educational level has been a significant discussion, with little attention on the gender dynamics on the acceptance of artificial intelligence (AI ) tools by senior lecturers. This study delved into a detailed analysis of the gender dynamics in the discussion of technology acceptance mainly AI tools, in foreign language (FL) education. Quantitative study approach was adopted in the process, and survey design was implemented. Data was collected using structured digital questionnaire, based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model. A total of ninety-five (95) male senior lecturers and one hundred and three (103) female senior lecturers participated in the study. Analysis was conducted using relevant statistical measures. The results showed disparities in the attitudes and views of senior lecturers towards artificial intelligence (AI) technologies in the context of FL education, greatly influenced by gender. In relation to usage, male senior lecturers have higher positive reactions (61.06%) in comparison to their female counterparts (46.6%). However, in relation to the assumption that AI technologies improve the performance of learners, 69% of male senior lecturers agree with this notion, but a substantially greater percentage of 72.81% of female senior lecturers hold the same perspective. Moreover, there exists a little disparity in the level of proficiency in using AI technologies across genders. Specifically, 56.84% of male senior lecturers see it as uncomplicated, while 61.16% of their female counterparts share the same sentiment. The gender discrepancy that is most notable pertains to the perceived level of ease in using artificial intelligence (AI) technologies during foreign language (FL) lessons. The data reveals that a majority of male senior lecturers, calculated as 69.48%, see the use of these tools very easy. In contrast, a much higher proportion of female senior lecturers, 86.41%, share the same perception. This discrepancy highlights a notable disparity in confidence levels between the two genders. These results together emphasise the changing gender dynamics in the acceptance of technology, interrogating conventional assumptions and underscoring the need for customised support systems to guarantee fair and efficient integration of artificial intelligence (AI) technologies in foreign language instruction among senior lecturers.

The purpose of this research is to investigate the nature of the relationship between artificial intelligence (AI) and machine learning (ML) technologies in service-based organizations on the one hand and organizational resilience on the other, as well as the potential impact of external market shocks on this relationship. A quantitative survey of 171 service-based groups was used to perform the research. The study's findings indicate that using AI and ML technologies in service delivery has a beneficial and substantial effect on organizational resilience. Furthermore, the research discovered that the degree to which external market shocks influence the efficacy of these technologies in improving an organization's resilience moderates the connection between the use of AI and ML technologies and organizational resilience. According to the results, service-based companies can improve their resilience by incorporating AI and ML technologies into their service delivery processes. They must, however, evaluate the possible influence of external market shocks on the efficacy of these technologies in increasing resilience. The research has ramifications for service-based organizations and adds to the body of knowledge on organizational resilience and the application of AI and ML technologies in service delivery.

Objectives: The objective of this scientific paper is to shed light on the challenges facing the legislative industry in the field of artificial intelligence (AI) technologies. Specifically, it aims to anticipate and predict the difficulties related to creating an independent legal personality for AI tools, enabling them to assume rights and obligations, as well as establishing criminal responsibility and punishment in cases where AI technologies commit crimes punishable by law. Methods: To achieve the stated objectives, this paper employs a theoretical and analytical approach. It involves a comprehensive review and analysis of existing literature, legal frameworks, and case studies related to the legal implications of AI technologies. Additionally, hypothetical scenarios and potential challenges are discussed to illustrate the complexities involved in creating legal frameworks that address the unique nature of AI tools and their impact on society. Results: The analysis reveals several key challenges facing the legislative industry in the field of AI technologies. These challenges include the conceptualization of an independent legal personality for AI tools, determining the rights and obligations associated with such personality, and establishing mechanisms for holding AI technologies accountable for their actions. Furthermore, the paper explores the difficulties in imposing criminal responsibility and punishment on AI technologies in cases where they commit crimes. Conclusion: In conclusion, this scientific paper highlights the complexities and challenges associated with creating legal frameworks for AI technologies. By anticipating and predicting these challenges, it provides valuable insights for legislators, policymakers, and legal professionals involved in shaping the regulatory landscape for AI. Moving forward, it is essential to address these challenges proactively and develop legal frameworks that strike a balance between promoting innovation and safeguarding societal interests in the era of artificial intelligence.

Artificial intelligence (AI) technology, as one of the most sophisticated science and technology in today's world, is increasingly being used to production and life, particularly in the manufacturing business. it demonstrates how artificial intelligence technology is used in mechanical manufacturing, namely in defect detection, quality inspection, enhancing workplace safety, and other areas. Artificial intelligence technology is becoming increasingly important in people's lives as it becomes more widely used in people's daily lives, such as the widespread use of smart dishwashers and smart sweepers, which are the products of the fusion of artificial intelligence and the mechanical manufacturing industry. Indeed, artificial intelligence technology has been widely utilized in the mechanical manufacturing business, which not only ensures production precision, but also enhances job productivity and workplace safety. The rise of artificial intelligence has caused significant changes in the manufacturing industry as a whole. Without exception, the manufacturing industry must rely on AI technology to accomplish automation and intelligent development, as well as to improve productivity. Using artificial intelligence to categorize mechanical components, we may propose parts from a based solely on an image or CAD model. To find a necessary component in a machines we must currently browse through a catalogue and be able to discern which part you want based on the available possibilities and your understanding of the catalogue. There are serial numbers to memorize since a single digit or character change might indicate a different sort of part. The algorithm will choose which sections are the best and will significantly facilitate our search.

PurposeThe introduction of artificial intelligence (AI) technology has had a substantial influence on the retail industry. However, AI adoption entails considerable responsibilities and risks for senior managers. In this study, the authors developed an evaluation and selection mechanism for successful AI technology adoption in the retail industry. The multifaceted measurement and identification of critical factors (CFs) can enable retailers to adopt AI technology effectively and maintain a sustainable competitive advantage.Design/methodology/approachThe evaluation and adoption of organisational AI technology involve multifaceted decision-making for management. Therefore, the authors used the analytic network process to develop an AI evaluation framework for calculating the weight and importance of each consideration. An expert questionnaire survey was distributed to senior retail managers and 17 valid responses were obtained. Finally, the Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) method was used to identify CFs for AI adoption.FindingsThe results revealed five CFs for AI adoption in the retail industry. The findings indicated that after AI adoption, top retail management is most concerned with factors pertaining to business performance and minor concerned about the internal system's functional efficiency. Retailers pay more attention to technology and organisation context, which are matters under the retailers' control, than to external uncontrollable environmental factors.Originality/valueThe authors developed an evaluation framework and identified CFs for AI technology adoption in the retail industry. In terms of practical application, the results of this study can help AI service providers understand the CFs of retailers when adopting AI. Moreover, retailers can use the proposed multifaceted evaluation framework to guide their adoption of AI technology.

With the rapid development of the financial industry and artificial intelligence (AI) technology, the application of AI robots in finance has become a widely discussed topic in the academia. As an important part of the financial market, the secondary trading market of virtual currencies is characterized by high volatility, risk and decentralization, which poses significant challenges for traditional trading methods. AI technologies, especially machine learning and deep learning algorithms, provides a new path to optimize trading strategies and reduce investment risks thanks to their powerful data processing, pattern recognition and real-time analysis capabilities. This paper focuses on the characteristics of AI technology and the secondary trading market of virtual currencies, as well as the practical application of artificial intelligence technology in the financial industry, and explores the potential of applying AI robots to virtual currency trading. The research shows that AI robots can provide more accurate decision support for investors through massive data analysis, automatic trading execution and real-time risk assessment, improving market response speed and investment return rate. If the combination of AI robots and virtual currency trading is successful, it is expected to create more long-term and stable returns for investors, providing important theoretical and practical value for the development of financial investment.

Artificial Intelligence (AI) technologies are becoming increasingly pervasive throughout the business industry. The rapid diffusion of this technology in organizations is due to the intrinsic benefits that can be realized by those who successfully adopt them into their business practices. Those organizations that fail to adopt AI technologies will be at a competitive disadvantage over those that do. As can be found throughout IS literature, successful adoption depends on users’ attitudes and behavioral intentions toward AI technology. Therefore, given the rapid diffusion of AI and the need for organizational success, it is important to research and understand the determinants of users’ attitudes and behavioral intentions toward adopting AI technologies.This current research proposed an extended Technology Acceptance Model (TAM) that includes variables identified within literature to be determinants of users’ attitudes and behavioral intentions toward adopting AI technologies. The proposed model (PM) was then tested by conducting a cross-sectional survey of students in a business college. The survey results were analyzed to determine which of the proposed variables increase TAM’s ability to explain attitudes and predict behavioral intentions toward adopting AI technologies. Further analysis also identified which of the proposed variables significantly influence business students’ attitudes and behavioral intentions to adopt AI technologies.The study found support that perceived usefulness was a significant determinant of students’ attitudes towards AI technologies. However, contrary to previous findings, the study found perceived ease of use negatively influenced attitudes towards AI technologies. From these findings, this study sought to provide insights that can inform educators and practitioners of curriculum and training design topics that will increase the likelihood of AI technology adoption. Specifically, the results suggested that educators and curriculum and instructional design practitioners should focus on usefulness and not on simplicity of use. The study also recommended that future research extend the current model with moderators and mediators such as innovation resistance and perceived risk.<br>

Professionals are implementing artificial intelligence (AI) technology in different fields owing to its diverse uses and benefits. Similarly, AI professionals are also beginning to implement AI technology in foreign-language education and second-language learning. Therefore, through a systematic literature review, this paper analyzes the role of AI in helping learners of a second language to master pronunciation. A detailed and in-depth search of different well-known databases was conducted, and of 116 articles, only 39 were selected for this paper. AI algorithms can advance language learning and acquisition in almost every dialect and could be significant for different parties in different ways. For example, organizations could utilize AI technology to develop their workers’ knowledge; individual learners could use AI technology to facilitate their studies anywhere and anytime; and traditional learning institutions could incorporate AI-powered methods of language learning to diversify learners’ opportunities. There are many benefits to employing AI in language learning, particularly in second-language learning.