A quantitative study of disruptive technology policy texts:An example of China’s artificial intelligence policy

Purpose:The transformative impact of disruptive technologies on the restructuring of the times has attracted widespread global attention.This study aims to analyze the characteristics and shortcomings of China’s artificial intelligence(AI)disruptive technology policy,and to put forward suggestions for optimizing China’s AI disruptive technology policy.Design/methodology/approach:Develop a three-dimensional analytical framework for“policy tools-policy actors-policy themes”and apply policy tools,social network analysis,and LDA topic model to conduct a comprehensive analysis of the utilization of policy tools,cooperative relationships among policy actors,and the trends in policy theme settings within China’s innovative AI technology policy.Findings:We find that the collaborative relationship among the policy actors of AI disruptive technology in China is insufficiently close.Marginal subjects exhibit low participation in the cooperation network and overly rely on central subjects,forming a“center-periphery”network structure.Policy tool usage is predominantly focused on supply and environmental types,with a severe inadequacy in demand-side policy tool utilization.Policy themes are diverse,encompassing topics such as“Intelligent Services”“Talent Cultivation”“Information Security”and“Technological Innovation”,which will remain focal points.Under the themes of“Intelligent Services”and“Intelligent Governance”,policy tool usage is relatively balanced,with close collaboration among policy entities.However,the theme of“AI Theoretical System”lacks a comprehensive understanding of tool usage and necessitates enhanced cooperation with other policy entities.Research limitations:The data sources and experimental scope are subject to certain limitations,potentially introducing biases and imperfections into the research results,necessitating further validation and refinement.Practical implications:The study introduces a three-dimensional analysis framework for disruptive technology policy texts,which is significant for formulating and enhancing disruptive technology policies.Originality/value:This study utilizes text mining and content analysis techniques to quantitatively analyze disruptive technology policy texts.It systematically evaluates China’s AI policies quantitatively,focusing on policy tools,policy actors,policy themes.The study uncovers the characteristics and deficiencies of current AI policies,offering recommendations for formulating and enhancing disruptive technology policies.

Exploration of Industrial Internet Security Technology and Application from the Perspective of Generative Artificial Intelligence

In recent years,artificial intelligence technology has developed rapidly around the world is widely used in various fields,and plays an important role.The integration of industrial Internet security with new technologies such as big models and generative artificial intelligence has become a hot research issue.In this regard,this paper briefly analyzes the industrial Internet security technology and application from the perspective of generative artificial intelligence,hoping to provide some valuable reference and reference for readers.

Ecological Restoration Technologies of Urban Artificial Landscape Lakes

Aiming at the problems of water pollution and ecological environment degradation in urban artificial landscape lakes,the ecological restoration technologies of artificial landscape lakes at home and abroad were studied to provide some reference for the ecological restoration of urban artificial landscape lakes in China.

A Review of Artificial Intelligence Applications in Contemporary Computer Network Technologies

Rapid advancement in science and technology has seen computer network technology being upgraded constantly, and computer technology, in particular, has been applied more and more extensively, which has brought convenience to people’s lives. The number of people using the internet around the globe has also increased significantly, exerting a profound influence on artificial intelligence. Further, the constant upgrading and development of artificial intelligence has led to the continuous innovation and improvement of computer technology. Countries around the world have also registered an increase in investment, paying more attention to artificial intelligence. Through an analysis of the current development situation and the existing applications of artificial intelligence, this paper explicates the role of artificial intelligence in the face of the unceasing expansion of computer network technology.

Acute pancreatitis:A review of diagnosis,severity prediction and prognosis assessment from imaging technology,scoring system and artificial intelligence

Acute pancreatitis(AP)is a potentially life-threatening inflammatory disease of the pancreas,with clinical management determined by the severity of the disease.Diagnosis,severity prediction,and prognosis assessment of AP typically involve the use of imaging technologies,such as computed tomography,magnetic resonance imaging,and ultrasound,and scoring systems,including Ranson,Acute Physiology and Chronic Health Evaluation II,and Bedside Index for Severity in AP scores.Computed tomography is considered the gold standard imaging modality for AP due to its high sensitivity and specificity,while magnetic resonance imaging and ultrasound can provide additional information on biliary obstruction and vascular complications.Scoring systems utilize clinical and laboratory parameters to classify AP patients into mild,moderate,or severe categories,guiding treatment decisions,such as intensive care unit admission,early enteral feeding,and antibiotic use.Despite the central role of imaging technologies and scoring systems in AP management,these methods have limitations in terms of accuracy,reproducibility,practicality and economics.Recent advancements of artificial intelligence(AI)provide new opportunities to enhance their performance by analyzing vast amounts of clinical and imaging data.AI algorithms can analyze large amounts of clinical and imaging data,identify scoring system patterns,and predict the clinical course of disease.AI-based models have shown promising results in predicting the severity and mortality of AP,but further validation and standardization are required before widespread clinical application.In addition,understanding the correlation between these three technologies will aid in developing new methods that can accurately,sensitively,and specifically be used in the diagnosis,severity prediction,and prognosis assessment of AP through complementary advantages.

Artificial intelligence technology and ultrasound-guided nerve block for analgesia in total knee arthroplasty

BACKGROUND Knee diseases are more common in middle-aged and elderly people,so artificial knee replacement is also more used in middle-aged and elderly people.Although the patient’s pain can be reduced through surgery,often accompanied by moderate pain after surgery and neutralization,which not only increases the psychological burden of the patient,but also greatly reduces the postoperative recovery effect,and may also lead to the occurrence of postoperative adverse events in severe cases.AIM To investigate the analgesic effect of artificial intelligence(AI)and ultrasoundguided nerve block in total knee arthroplasty(TKA).METHODS A total of 92 patients with TKA admitted to our hospital from January 2021 to January 2022 were opted and divided into two groups according to the treatment regimen.The control group received combined spinal-epidural anesthesia.The research group received AI technique combined with ultrasound-guided nerve block anesthesia.The sensory block time,motor block time,visual analogue scale(VAS)at different time points and complications were contrasted between the two groups.RESULTS The time of sensory block onset and sensory block perfection in the research group was shorter than those in the control group,but the results had no significant difference(P>0.05).Duration of sensory block in the research group was significantly longer than those in the control group(P<0.05).The time of motor block onset and motor block perfection in the research group was shorter than those in the control group,but the results had no significant difference(P>0.05).Duration of motor block in the research group was significantly longer than those in the control group.The VAS scales of the research group were significantly lower than that of the control group at different time points(P<0.05).The postoperative hip flexion and abduction range of motion in the research group were significantly better than those in the control group at different time points(P<0.05).The incidence of complications was significantly lower in the research group than in the control group(P=0.049).CONCLUSION In TKA,the combination of AI technology and ultrasound-guided nerve block has a significantly effect,with fewer postoperative complications and significantly analgesic effect,which is worthy of application.

Is the Genie of Artificial Intelligence Technology Out of the Bottle and Control?(A Short Review)

In recent years,AI(artificial intelligence)has made considerable strides,transforming a number of industries and facets of daily life.However,as AI develops more,worries about its potential dangers and unforeseen repercussions have surfaced.This article investigates the claim that AI technology has broken free from human control and is now unstoppable.We look at how AI is developing right now,what it means for society,and what steps are being taken to reduce the risks that come with it.We seek to highlight the need for responsible development and implementation of this game-changing technology by examining the opportunities and challenges that AI presents.

Harnessing the Power of Artificial Intelligence in Neuromuscular Disease Rehabilitation: A Comprehensive Review and Algorithmic Approach

Neuromuscular diseases present profound challenges to individuals and healthcare systems worldwide, profoundly impacting motor functions. This research provides a comprehensive exploration of how artificial intelligence (AI) technology is revolutionizing rehabilitation for individuals with neuromuscular disorders. Through an extensive review, this paper elucidates a wide array of AI-driven interventions spanning robotic-assisted therapy, virtual reality rehabilitation, and intricately tailored machine learning algorithms. The aim is to delve into the nuanced applications of AI, unlocking its transformative potential in optimizing personalized treatment plans for those grappling with the complexities of neuromuscular diseases. By examining the multifaceted intersection of AI and rehabilitation, this paper not only contributes to our understanding of cutting-edge advancements but also envisions a future where technological innovations play a pivotal role in alleviating the challenges posed by neuromuscular diseases. From employing neural-fuzzy adaptive controllers for precise trajectory tracking amidst uncertainties to utilizing machine learning algorithms for recognizing patient motor intentions and adapting training accordingly, this research encompasses a holistic approach towards harnessing AI for enhanced rehabilitation outcomes. By embracing the synergy between AI and rehabilitation, we pave the way for a future where individuals with neuromuscular disorders can access tailored, effective, and technologically-driven interventions to improve their quality of life and functional independence.

Artificial intelligence awareness and perceptions among pediatric orthopedic surgeons:A cross-sectional observational study

BACKGROUND Artificial intelligence(AI)is a branch of computer science that allows machines to analyze large datasets,learn from patterns,and perform tasks that would otherwise require human intelligence and supervision.It is an emerging tool in pediatric orthopedic surgery,with various promising applications.An evaluation of the current awareness and perceptions among pediatric orthopedic surgeons is necessary to facilitate AI utilization and highlight possible areas of concern.AIM To assess the awareness and perceptions of AI among pediatric orthopedic surgeons.METHODS This cross-sectional observational study was conducted using a structured questionnaire designed using QuestionPro online survey software to collect quantitative and qualitative data.One hundred and twenty-eight pediatric orthopedic surgeons affiliated with two groups:Pediatric Orthopedic Chapter of Saudi Orthopedics Association and Middle East Pediatric Orthopedic Society in Gulf Cooperation Council Countries were surveyed.RESULTS The pediatric orthopedic surgeons surveyed had a low level of familiarity with AI,with more than 60%of respondents rating themselves as being slightly familiar or not at all familiar.The most positively rated aspect of AI applications for pediatric orthopedic surgery was their ability to save time and enhance productivity,with 61.97%agreeing or strongly agreeing,and only 4.23%disagreeing or strongly disagreeing.Our participants also placed a high priority on patient privacy and data security,with over 90%rating them as quite important or highly important.Additional bivariate analyses suggested that physicians with a higher awareness of AI also have a more positive perception.CONCLUSION Our study highlights a lack of familiarity among pediatric orthopedic surgeons towards AI,and suggests a need for enhanced education and regulatory frameworks to ensure the safe adoption of AI.

Perspectives and Experiences of Education Stakeholders: A Quantitative Study on the Adoption of Artificial Intelligence in Executive Training Using Structural Equation Modeling

The recent increase in the use of artificial intelligence has led to fundamental changes in the development of training and teaching methods for executive education. However, the success of artificial intelligence in regional centers for teaching and training professions will depend on the acceptance of this technology by young executive trainees. This article discusses the potential benefits of adopting AI in executive training institutions in Morocco, specifically focusing on CRMEF Casablanca Settat. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003), this study proposes a model to identify the factors influencing the acceptance of artificial intelligence in regional centers for teaching professions and training in Morocco. To achieve this, a structural equation modeling approach was used to quantitatively describe the impact of each factor on AI adoption, utilizing data collected from 173 young executive trainees. The results indicate that perceived ease of use, perceived usefulness, trainer influence, and personal innovativeness influence the intention to use artificial intelligence. Our research provides managers of CRMEFs with a set of practical recommendations to enhance the implementation conditions of an artificial intelligence system. It aims to understand which factors should be considered in designing an artificial intelligence system within regional centers for teaching professions and training (CRMEFs).

Enhancing College English Teachers’Teaching and Practical Abilities in the New Era:The Role of Educational Technology Amid US-China AI Rivalry

In the 21st century,the rapid development of artificial intelligence(AI)and educational technology has revolutionized the global education landscape.As the United States and China engage in strategic competition in the AI field,the impact of this rivalry extends beyond technology and economics,permeating education and international relations.This paper explores how educational technology can be leveraged to enhance the teaching and practical abilities of college English teachers in China within the context of the US-China AI competition.The intersection of AI development,educational strategies,and international diplomacy provides a unique backdrop for examining the potential and challenges of integrating advanced technology in English language teaching(ELT).This paper aims to provide insights for policymakers,educators,and researchers on how to effectively utilize educational technology to enhance the teaching and practical abilities of college English teachers,emphasizing the importance of strategic planning and international cooperation in this rapidly evolving field.

The Impact of Seasonal Variation on Clinical Pregnancy and Live Birth Rates in Assisted Reproductive Technology: A Retrospective Cohort Study in Hainan

Objective:To investigate the influence of season on live birth and clinical pregnancy rates,as well as assisted reproductive technology(ART)outcomes,in the Hainan region.Methods:Patients were categorized into four groups based on the dates of artificial insemination and transplantation:spring,summer,autumn,or winter.The main outcome measures were clinical pregnancy rates and live birth rates.Secondary outcomes included body mass index(BMI),oocyte number,two pronuclei(2PN)cleavage rate,total gonadotropin(Gn)dosage and days,age,2PN fertilization rate,sperm concentration,sperm PR rate,anti-Müllerian hormone(AMH),and endometrial thickness.Outpatient semen quality indicators included sperm PR rate,total sperm count,sperm concentration,and total sperm motility.Results:This retrospective cohort study analyzed 2,016 artificial insemination cycles and 1,783 ovarian retrieval cycles from January 2017 to October 2022,and assessed the semen quality of 6,651 outpatients from May 2017 to October 2022.In artificial insemination cycles,sperm PR rate and clinical pregnancy rate were highest in winter,with a statistically significant difference between groups(P<0.05).Clinical pregnancy rate was influenced by both age and sperm PR rate(P<0.05).In ovarian retrieval cycles,the winter group had significantly higher clinical pregnancy,2PN fertilization,and 2PN cleavage rates than the other groups.The autumn group had higher live birth rates,though not significantly different.Additionally,winter months showed higher total sperm concentration and total sperm number compared to other seasons.Conclusion:Seasonality affected clinical pregnancy and live birth rates in artificial insemination cycles but not in ovarian retrieval cycles in the Hainan region.These findings suggest that while there is no need to choose a specific season for ovarian retrieval cycles,artificial insemination in winter may be preferable for patients.

Reform and Development of English Teaching in Colleges and Universities with the Integration of ChatGPT Technology

As an artificial intelligence-powered language generation model based on natural language processing,ChatGPT,like other artificial intelligence technologies,possesses super real-time dialogue capabilities and is considered an innovative and intelligent auxiliary teaching tool in the field of language learning.This article first analyzes the current state of development of artificial intelligence technologies such as ChatGPT.Secondly,it examines the challenges encountered in the reform and development of English teaching in colleges and universities in China.Lastly,it summarizes the applications and recommendations for using ChatGPT technology in college-level English teaching.

Research and Application of Artificial Intelligence in Electric Guitar Performance

The article explores the application of artificial intelligence technology in electric guitar playing.It delves into the advantages of artificial intelligence and its seamless integration into electric guitar performance.Additionally,it investigates the application of artificial intelligence technology through an intelligent playing robot.The research aims to offer substantial support for the advancement of artificial intelligence in electric guitar performance.

An Examination of Computer Science and Internet Technologies in Addressing Educational Inequities and Societal Psychological Concerns:A Literature Review from the Perspectives of 5G,Artificial Intelligence,and Augmented/Virtual Reality

This study comprehensively reviews the literature to deeply explore the role of computer science and internet technologies in addressing educational inequality and socio-psychological issues,with a particular focus on applications of 5G,artificial intelligence(AI),and augmented/virtual reality(AR/VR).By analyzing how these technologies are reshaping learning and their potential to ameliorate educational disparities,the study reveals challenges present in ensuring educational equity.The research methodology includes exhaustive reviews of applications of AI and machine learning,the Internet of Things and wearable technologies integration,big data analytics and data mining,and the effects of online platforms and social media on socio-psychological issues.Besides,the study discusses applications of these technologies in educational inequality and socio-psychological problem-solving through the lens of 5G,AI,and AR/VR,while also delineating challenges faced by these emerging technologies and future outlooks.The study finds that while computer science and internet technologies hold promise to bridge academic divides and address socio-psychological problems,the complexity of technology access and infrastructure,lack of digital literacy and skills,and critical ethical and privacy issues can impact widespread adoption and efficacy.Overall,the study provides a novel perspective to understand the potential of computer science and internet technologies in ameliorating educational inequality and socio-psychological issues,while pointing to new directions for future research.It also emphasizes the importance of cooperation among educational institutions,technology vendors,policymakers and researchers,and establishing comprehensive ethical guidelines and regulations to ensure the responsible use of these technologies.

Homo Faber Scapegoated, or Apocalyptic Artificial Intelligence: Rethinking the Technological Singularity Concept From the Synergetic Historicism Position

The article is focused on discussing a new methodological approach to the study on specifics of transferring human beings to the posthuman cyber society.The approach in question assists in rethinking interconnected problems both of human origins in the universe and mankind’s digital future.And,besides,such an approach allows to deal with self-organising interconversions between the poles of the cardinal dual opposition of the Global Noosphere Brain and the Artificial General Intelligence.Herewith such phenomena of digital social life as Global Digitalisation,Digital Immortality,Mindcloning,and Technological Zombification being the constituents of Technological Singularity Concept,are rethought as paving the way for oncoming Posthuman Digital Era.This concept is evidently exemplified by a bifurcation resulting in two alternatives to be chosen by human beings,to wit,either to be undergone Mindcloning and become digitally immortal or being destroyed by powerful intelligent machines.The investigation in question is based on such a progressive methodology as the Law of Self-Organizing Ideals,as well as on the Method of Dual Oppositions.Rethinking interrelationships between the problem of a sense of social history and the meaning-of-life of local societies members which any intelligent machine is devoid of permits to substantiate specific regularities of Self-Transforming Homo Faber into Homo Digitalis and Technological Zombies ready to be transferred to posthuman cyberspace.

The Optimization Study about Fault Self-Healing Restoration of Power Distribution Network Based on Multi-Agent Technology

In order to quickly and accurately locate the fault location of the distribution network and increase the stability of the distribution network,a fault recovery method based on multi-objective optimization algorithm is proposed.The optimization of the power distribution network fault system based on multiagent technology realizes fast recovery of multi-objective fault,solve the problem of network learning and parameter adjustment in the later stage of particle swarm optimization algorithm falling into the local extreme value dilemma,and realize the multi-dimensional nonlinear optimization of the main grid and the auxiliary grid.The system proposed in this study takes power distribution network as the goal,applies fuzzy probability algorithm,simplifies the calculation process,avoids local extreme value,and finally realizes the energy balance between each power grid.Simulation results show that the Multi-Agent Technology enjoys priority in restoring important load,shortening the recovery time of power grid balance,and reducing the overall line loss rate of power grid.Therefore,the power grid fault self-healing system can improve the safety and stability of the important power grid,and reduce the economic loss rate of the whole power grid.

Integration of Artificial Intelligence, Blockchain, and Wearable Technology for Chronic Disease Management: A New Paradigm in Smart Healthcare

Chronic diseases are a growing concern worldwide,with nearly 25% of adults suffering from one or more chronic health conditions,thus placing a heavy burden on individuals,families,and healthcare systems.With the advent of the“Smart Healthcare”era,a series of cutting-edge technologies has brought new experiences to the management of chronic diseases.Among them,smart wearable technology not only helps people pursue a healthier lifestyle but also provides a continuous flow of healthcare data for disease diagnosis and treatment by actively recording physiological parameters and tracking the metabolic state.However,how to organize and analyze the data to achieve the ultimate goal of improving chronic disease management,in terms of quality of life,patient outcomes,and privacy protection,is an urgent issue that needs to be addressed.Artificial intelligence(AI)can provide intelligent suggestions by analyzing a patient’s physiological data from wearable devices for the diagnosis and treatment of diseases.In addition,blockchain can improve healthcare services by authorizing decentralized data sharing,protecting the privacy of users,providing data empowerment,and ensuring the reliability of data management.Integrating AI,blockchain,and wearable technology could optimize the existing chronic disease management models,with a shift from a hospital-centered model to a patient-centered one.In this paper,we conceptually demonstrate a patient-centric technical framework based on AI,blockchain,and wearable technology and further explore the application of these integrated technologies in chronic disease management.Finally,the shortcomings of this new paradigm and future research directions are also discussed.

The role of artificial intelligence technology in the care of diabetic foot ulcers: the past, the present, and the future

Foot ulcers are common complications of diabetes mellitus and substantially increase the morbidity and mortality due to this disease.Wound care by regular monitoring of the progress of healing with clinical review of the ulcers,dressing changes,appropriate antibiotic therapy for infection and proper offloading of the ulcer are the cornerstones of the management of foot ulcers.Assessing the progress of foot ulcers can be a challenge for the clinician and patient due to logistic issues such as regular attendance in the clinic.Foot clinics are often busy and because of manpower issues,ulcer reviews can be delayed with detrimental effects on the healing as a result of a lack of appropriate and timely changes in management.Wound photographs have been historically useful to assess the progress of diabetic foot ulcers over the past few decades.Mobile phones with digital cameras have recently revolutionized the capture of foot ulcer images.Patients can send ulcer photographs to diabetes care professionals electronically for remote monitoring,largely avoiding the logistics of patient transport to clinics with a reduction on clinic pressures.Artificial intelligence-based technologies have been developed in recent years to improve this remote monitoring of diabetic foot ulcers with the use of mobile apps.This is expected to make a huge impact on diabetic foot ulcer care with further research and development of more accurate and scientific technologies in future.This clinical update review aims to compile evidence on this hot topic to empower clinicians with the latest developments in the field.

Application and Development of Computer Artificial Intelligence Technology

In the development of modern society,Internet technology has been popularized and applied.Artificial intelligence technology is not only found in science fiction movies,but has been widely used in industry,tertiary industry and people’s livelihood.Under the background of rapid advancement of science and technology,computer artificial intelligence technology will play an important role in the future.Due to a series of problems in the development of computer artificial intelligence technology,it is necessary for relevant personnel to strengthen research on the application and development of computer artificial intelligence technology.The paper mainly studies the application and development of computer artificial intelligence technology,and hopes to bring more convenience to the daily life of the people.