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.

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.

Innovation and Practice of Training Mode for Professional Postgraduates of Acupuncture and Tuina Based on Artificial Intelligence

In view of the common problems of integrating artificial intelligence into the training of postgraduates in Acupuncture and Tuina major,this paper reviews the related research progress both at home and abroad.It puts forward the innovative reform paths for integrating artificial intelligence into postgraduate training mode of Acupuncture and Tuina major:construct the teaching staff of artificial intelligence graduate students;innovating artificial intelligence to promote the integration of classics and scientific research;constructing the ideological and political case base of artificial intelligence courses;implementing artificial intelligence platform blended teaching;building a domestic and foreign exchange platform for artificial intelligence.Through practical research in teaching,it has achieved good teaching results and played a good demonstration,leading and radiation role in similar majors in China.

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).

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.

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.

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.

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.

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.

Call for Papers Journal of Electronic Science and Technology Announcing a Special Issue on Artificial Intelligence with Rough Sets

Submission Deadline： 10 December 2010Since the introduction of rough sets in 1982 by Professor Zdzislaw Pawlak, we have witnessed great advances in both theory and applications. In order to promote development of rough sets, we are preparing a special issue on ＂Artificial Intelligence with Rough Sets＂ published by JEST （International）, Journal of Electronic Science and Technology, which is a refereed international journal focusing on IT area. The aim of this special issue is to present the current state of the research in this area, oriented towards both theoretical and applications aspects of rough sets.

Research on the application of artificial intelligence in the computer network technology

As the product of the mutual infiltration of the various disciplines such as the control theory, information theory, system theory, computer science, physiology, psychology, mathematics, philosophy and so on, the research field of the theory and application of artificial intelligence technology covers almost all the areas of human activity. In recent years, the rapid development of computer network technology produces and drives a batch of new scientific research fields. Among them, the application of artificial intelligence in the computer network technology is a hot topic which is academically and technically strong and can bring obvious economic benefit.

Study on Cognitive Optical Network Structure and Self-optimization with the Application of Artificial Intelligence Technology

Cognitive optical network is the intermediate to combine artificial intelligence technology with network,and also the important network technology to promote network intelligence level constantly.In the paper,it analyzes the cognitive optical network structure with the application of artificial intelligence technology by starting from the basic conditions of cognitive network and cognitive optional network on the basis of fully understanding the connotation of cognitive network and cognitive optical network,and explores its self-governance functions,so as to better realize the self-optimization and self-configuration of network.

Research on the Application of Big Data and Artificial Intelligence Technology in Computer Network

With the continuous development of social economy,science and technology are also in continuous progress,relying on the Internet technology of big data era has come in an all-round way.On the basis of the development of cloud computing and Internet technology,artificial intelligence technology has emerged as the times require.It also has more advantages.Applying it to computer network technology can effectively improve the data processing efficiency and quality of computer network technology,and improve the convenience for people’s life and production.This paper studies and analyzes the practical application requirements of computer network,and discusses the application characteristics and timeliness of artificial intelligence technology.

Beyond p-y method:A review of artificial intelligence approaches for predicting lateral capacity of drilled shafts in clayey soils

In 2023,pivotal advancements in artificial intelligence(AI)have significantly experienced.With that in mind,traditional methodologies,notably the p-y approach,have struggled to accurately model the complex,nonlinear soil-structure interactions of laterally loaded large-diameter drilled shafts.This study undertakes a rigorous evaluation of machine learning(ML)and deep learning(DL)techniques,offering a comprehensive review of their application in addressing this geotechnical challenge.A thorough review and comparative analysis have been carried out to investigate various AI models such as artificial neural networks(ANNs),relevance vector machines(RVMs),and least squares support vector machines(LSSVMs).It was found that despite ML approaches outperforming classic methods in predicting the lateral behavior of piles,their‘black box'nature and reliance only on a data-driven approach made their results showcase statistical robustness rather than clear geotechnical insights,a fact underscored by the mathematical equations derived from these studies.Furthermore,the research identified a gap in the availability of drilled shaft datasets,limiting the extendibility of current findings to large-diameter piles.An extensive dataset,compiled from a series of lateral loading tests on free-head drilled shaft with varying properties and geometries,was introduced to bridge this gap.The paper concluded with a direction for future research,proposes the integration of physics-informed neural networks(PINNs),combining data-driven models with fundamental geotechnical principles to improve both the interpretability and predictive accuracy of AI applications in geotechnical engineering,marking a novel contribution to the field.

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.

Real-Time Prediction of Urban Traffic Problems Based on Artificial Intelligence-Enhanced Mobile Ad Hoc Networks(MANETS)

Traffic in today’s cities is a serious problem that increases travel times,negatively affects the environment,and drains financial resources.This study presents an Artificial Intelligence(AI)augmentedMobile Ad Hoc Networks(MANETs)based real-time prediction paradigm for urban traffic challenges.MANETs are wireless networks that are based on mobile devices and may self-organize.The distributed nature of MANETs and the power of AI approaches are leveraged in this framework to provide reliable and timely traffic congestion forecasts.This study suggests a unique Chaotic Spatial Fuzzy Polynomial Neural Network(CSFPNN)technique to assess real-time data acquired from various sources within theMANETs.The framework uses the proposed approach to learn from the data and create predictionmodels to detect possible traffic problems and their severity in real time.Real-time traffic prediction allows for proactive actions like resource allocation,dynamic route advice,and traffic signal optimization to reduce congestion.The framework supports effective decision-making,decreases travel time,lowers fuel use,and enhances overall urban mobility by giving timely information to pedestrians,drivers,and urban planners.Extensive simulations and real-world datasets are used to test the proposed framework’s prediction accuracy,responsiveness,and scalability.Experimental results show that the suggested framework successfully anticipates urban traffic issues in real-time,enables proactive traffic management,and aids in creating smarter,more sustainable cities.

The enlightenment of artificial intelligence large-scale model on the research of intelligent eye diagnosis in traditional Chinese medicine

Eye diagnosis is a method for inspecting systemic diseases and syndromes by observing the eyes.With the development of intelligent diagnosis in traditional Chinese medicine(TCM);artificial intelligence(AI)can improve the accuracy and efficiency of eye diagnosis.However;the research on intelligent eye diagnosis still faces many challenges;including the lack of standardized and precisely labeled data;multi-modal information analysis;and artificial in-telligence models for syndrome differentiation.The widespread application of AI models in medicine provides new insights and opportunities for the research of eye diagnosis intelli-gence.This study elaborates on the three key technologies of AI models in the intelligent ap-plication of TCM eye diagnosis;and explores the implications for the research of eye diagno-sis intelligence.First;a database concerning eye diagnosis was established based on self-su-pervised learning so as to solve the issues related to the lack of standardized and precisely la-beled data.Next;the cross-modal understanding and generation of deep neural network models to address the problem of lacking multi-modal information analysis.Last;the build-ing of data-driven models for eye diagnosis to tackle the issue of the absence of syndrome dif-ferentiation models.In summary;research on intelligent eye diagnosis has great potential to be applied the surge of AI model applications.

China, France and the Netherlands to Deepen Cooperation on Information Technology and Artificial Intelligence

On July 11,2017,an agreement was signed in Beijing to renew and strengthen the collaboration between the CAS Institute of Automation(CASIA,China),Institut National de Recherche en Informatique et en Automatique(Inria,France),and Centrum Wiskunde&Informatica(CWI,the Netherlands),which are the founding members of the Sino-European Laboratory in Computer Science,