World Industrial Revolutions and the Development of Artificial Intelligence System

The objective-scientific conclusions obtained from the researches conducted in various fields of science prove that era and worldview are in unity and are phenomena that determine one another,and era and worldview are the most important phenomena in the understanding of geniuses,historical events,including personalities who have left a mark on the history of politics,and every individual as a whole.And it is appropriate to briefly consider the problem in the context of human and personality factors.It is known that man has tried to understand natural phenomena since the beginning of time.Contact with the material world naturally affects his consciousness and even his subconscious as he solves problems that are important or useful for human life.During this understanding,the worldview changes and is formed.Thus,depending on the material and moral development of all spheres of life,the content and essence of the progress events,as the civilizations replaced each other in different periods,the event of periodization took place and became a system.If we take Europe,the people of the Ice Age of 300,000 years ago,who engaged in hunting to solve their hunger needs,in other words,the age of dinosaurs,have spread to many parts of the world from Africa,where they lived in order to survive and meet more of their daily needs.The extensive integration of agricultural Ice Age People into the Earth included farming,fishing,animal husbandry,hunting,as well as handicrafts,etc.,and has led to the revolutionary development of the fields.As economic activities led these first inhabitants of the planet from caves to less comfortable shelters,then to good houses,then to palaces,labor activities in various occupations,including crafts,developed rapidly.Thus,the fads of the era who differed from the crowd(later this class will be called personalities,geniuses...-Kh.G.)began to appear.If we approach the issue from the point of view of history,we witness that the world view determines the development in different periods.This idea can be expressed in such a way that each period can be considered to have developed or experienced a crisis according to the level of worldview.In this direction of our thoughts,the question arises:So,what is the phenomenon of worldview of this era-XXI century?Based on the general content of the current events,characterized as the globalization stage of the modern world,we can say that the outlook of the historical stage we live in is based on the achievements of the last stage of the industrial revolution.In this article,by analyzing the history of the artificial intelligence system during the world industrial revolutions,we will study both the concept of progress of the industrial revolutions and the progressive and at the same time regressive development of the artificial intelligence system.

Research on the Path to High-Quality Development of Grassroots Libraries in the Era of Artificial Intelligence in Henan

Since the age of digital intelligence,the government has introduced policies to actively promote the intelligent transformation of grassroots public cultural services.Based on the investigation and analysis of the development status quo of grassroots libraries in Henan Province,we put forward the path of high-quality development of grassroots libraries in Henan,namely,improving the mechanism and system,leading with digital intelligence technology,empowering by Yellow River culture(the heritage and values rooted in the history and traditions of the Yellow River region),and driven by users’demand.

Leveraging Robust Artificial Intelligence for Mechatronic Product Development—A Literature Review

Mechatronic product development is a complex and multidisciplinary field that encompasses various domains, including, among others, mechanical engineering, electrical engineering, control theory and software engineering. The integration of artificial intelligence technologies is revolutionizing this domain, offering opportunities to enhance design processes, optimize performance, and leverage vast amounts of knowledge. However, human expertise remains essential in contextualizing information, considering trade-offs, and ensuring ethical and societal implications are taken into account. This paper therefore explores the existing literature regarding the application of artificial intelligence as a comprehensive database, decision support system, and modeling tool in mechatronic product development. It analyzes the benefits of artificial intelligence in enabling domain linking, replacing human expert knowledge, improving prediction quality, and enhancing intelligent control systems. For this purpose, a consideration of the V-cycle takes place, a standard in mechatronic product development. Along this, an initial assessment of the AI potential is shown and important categories of AI support are formed. This is followed by an examination of the literature with regard to these aspects. As a result, the integration of artificial intelligence in mechatronic product development opens new possibilities and transforms the way innovative mechatronic systems are conceived, designed, and deployed. However, the approaches are only taking place selectively, and a holistic view of the development processes and the potential for robust and context-sensitive artificial intelligence along them is still needed.

Artificial intelligence as a tool in drug discovery and development

The rapidly advancing field of artificial intelligence(AI)has garnered substantial attention for its potential application in drug discovery and development.This opinion review critically examined the feasibility and prospects of integrating AI as a transformative tool in the pharmaceutical industry.AI,encompassing machine learning algorithms,deep learning,and data analytics,offers unprecedented opportunities to streamline and enhance various stages of drug development.This opinion review delved into the current landscape of AI-driven approaches,discussing their utilization in target identification,lead optimization,and predictive modeling of pharmacokinetics and toxicity.We aimed to scrutinize the integration of large-scale omics data,electronic health records,and chemical informatics,highlighting the power of AI in uncovering novel therapeutic targets and accelerating drug repurposing strategies.Despite the considerable potential of AI,the review also addressed inherent challenges,including data privacy concerns,interpretability of AI models,and the need for robust validation in realworld clinical settings.Additionally,we explored ethical considerations surrounding AI-driven decision-making in drug development.This opinion review provided a nuanced perspective on the transformative role of AI in drug discovery by discussing the existing literature and emerging trends,presenting critical insights and addressing potential hurdles.In conclusion,this study aimed to stimulate discourse within the scientific community and guide future endeavors to harness the full potential of AI in drug development.

A Discussion of Artificial Intelligence in Visual Art Education

Since ChatGPT emerged on November 30, 2022, Artificial Intelligence (AI) has been increasingly discussed as a radical force that will change our world. People have become used to AI in which such ubiquitous technologies as Siri, Google, and Netflix deploy AI algorithms to answer questions, impart information, and provide recommendations. However, many individuals including originators and backers of AI have recently expressed grave concerns. In this paper, the authors will assess what is occurring with AI in Visual Arts Education, outline positives and negatives, and provide recommendations addressed specifically for teachers working in the field regarding emerging AI usage from kindergarten to grade twelve levels as well as in higher education.

The Role and Place of Artificial Neural Network Architectures Structural Redundancy in the Input Data Prototypes and Generalization Development

Neural Networks (NN) are the functional unit of Deep Learning and are known to mimic the behavior of the human brain to solve complex data-driven problems. Whenever we train our own neural networks, we need to take care of something called the generalization of the neural network. The performance of Artificial Neural Networks (ANN) mostly depends upon its generalization capability. In this paper, we propose an innovative approach to enhance the generalization capability of artificial neural networks (ANN) using structural redundancy. A novel perspective on handling input data prototypes and their impact on the development of generalization, which could improve to ANN architectures accuracy and reliability is described.

Artificial Intelligence and the Sustainable Development Goals: An Exploratory Study in the Context of the Society Domain

Artificial Intelligence (AI) experienced significant advancements in recent years, and its potential power is already recognized across various industries. Yet, the rise of AI has led to a growing concern about its impact on meeting the Sustainable Development Goals (SDGs). The aim of this paper was to evaluate contributions and the potential influence of AI to sustainable development in the society domain. Furthermore, the study analyzed GPT-3 responses, as one of the largest language models developed by OpenAI, descriptively. We conducted a set of queries on the SDGs to gather information on GPT-3’s perceptions of AI impact on sustainable development. Analysis of GPT-3’s contribution potential towards the SDGs showcased its broad range of capabilities for contributing to the SDGs in areas such as education, health, and communication. The study findings provide valuable insights into the contributions of AI to sustainable development in the society domain and highlight the importance of proper regulations to promote the responsible use of AI for sustainable development. We highlighted the potential for improvement in neural language processing skills of GPT-3 by avoiding imitating weak human writing styles with more mistakes in longer texts.

Application of machine learning and deep learning in geothermal resource development: Trends and perspectives

This study delves into the latest advancements in machine learning and deep learning applications in geothermal resource development,extending the analysis up to 2024.It focuses on artificial intelligence's transformative role in the geothermal industry,analyzing recent literature from Scopus and Google Scholar to identify emerging trends,challenges,and future opportunities.The results reveal a marked increase in artificial intelligence(AI)applications,particularly in reservoir engineering,with significant advancements observed post‐2019.This study highlights AI's potential in enhancing drilling and exploration,emphasizing the integration of detailed case studies and practical applications.It also underscores the importance of ongoing research and tailored AI applications,in light of the rapid technological advancements and future trends in the field.

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.

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.

Enhancing Quality of Patients Care and Improving Patient Experience in China with Assistance of Artificial Intelligence

Improving health of Chinese people has become national strategy according to the Healthy China 2030.Patient experience evaluation examines health care service from perspective of patients;it is important for improving health care quality.Applying artificial intelligence(AI)in patient experience is an innovative approach to assist continuous improvement of care quality of patient service.A nursing quality platform based on patient experience data which is empowered by AI technologies has been established in China for the purpose of surveillance and analysis of the quality of patient care.It contains data from nearly 1300 healthcare facilities,based on which portraits of nursing service qualities can be drawn.The patient experience big data platform has shown potentials for healthcare facilities to improve patient care quality.More efforts are needed to achieve the goal of enhancing people’s sense of health gain.

Present Status of Clinical Decision Support System （CDSS） and Proposal of Ethical Guideline for Artificial Intelligence Development in Medical Field

This paper is looking at the trends of future medicine focusing on IBM Watson, Microsoft Intelligent Network for Eye care （MINE）, and Google’s AI Eye Doctor. Microsoft’s Mine, an artificial intelligence assistant program, and Google’s Eye Doctor, were created because of the two characteristics of eye disease. The disease of the eye significantly reduces the quality of human life, but it can be prevented if the illness is discovered in advance. Therefore, prevention of these diseases is important. Through the development of the Google eye Doctor Program shown in the article of “Retinopathy Algorithm”, we obtained the implications for the ethical guidelines that can be applied to other artificial intelligence development programs. At the heart of these guidelines is the efficient and safe treatment of patient illnesses for medical purposes.

Standards Expected to Boost Development of Artificial Intelligence

The State Council,China's Cabinet issued the Development Plan for the New Generation of Artificial Intelligence(Plan for short)on July 20,2017.The Plan vows to reach the advanced world level in overall technology and application of AI and initially build AI technical standards and service system by 2020.

International Papers Contribution on Artificial Intelligence Promotes the Application and Development of Big Data in the Petroleum Industry

Artificial intelligence is a new technological science that researches and develops theories,methods,technologies and application systems for simulating,extending and expanding human intelligence.It simulates certain human thought processes and intelligent behaviors(such as learning,reasoning,thinking,planning,etc.),and produces a new type of intelligent machine that can respond in a similar way to human intelligence.In the past 30 years,it has achieved rapid development in various industries and related disciplines such as manufacturing,medical care,finance,and transportation.

Impact of Artificial Intelligence on Economic Development

The economic growth pattern in China is changing from high-speed development to high-quality development.In order to promote high-quality economic development,it is necessary to promote the transformation and upgrading of all aspects of social reproduction.Artificial intelligence has promoted high-quality economic development in China from the aspects of innovation effect,technology spillover effect,factor improvement effect,and technology optimization effect.However,there are still several problems in China's Al development,such as the lack of core technologies,privacy and security,as well as the lack of high-tech talents.To this end,China should advance basic theoretical research and key generic technology development to improve the self-reliance of science and technology,as well as optimize the development environment of the industry and improve the relevant laws and regulations as well as the ethical norms system.A system to train high-quality personnel and a mechanism that allows personnel flow should be established to promote high-quality economic development.

Current Situation and Development of Intelligence Robots

Industrial intelligent robots are treated as a measure of na- tional scientific level and technology innovation, and also the important symbol of high-level manufacturing, while service intelligent robots can directly affect people＇ s daily lives. The development of artificial robots in different areas is at- tracting much attention around the world. This article re- views the current situation and development of Chinese and international intelligent robot markets including industrial ro- bots and service robots. The intelligent robot technology and the classification of robots are also discussed. Finally, appli- cations of intelligent robots in various fields are concluded and the development trends and outlook of intelligent robots are explored.

Artificial intelligence and the future of medicine: a multidimensional analysis

This multidimensional analysis of the impact of artificial intelligence on the future of medicine aims to give some clues on foreseen categories of applications as well as their societal implications in terms of risks/benefits.Artificial intelligence encompasses technologies recapitulating four dimensions of human intelligence,i.e.sensing,thinking,acting and learning.Intelligent machines are converging with advancing biotechnologies to shape the future of medicine,in synergy with continuous progress in our understanding of system biology,brain physiology,biology of aging,computational sciences and decision-making theories.Data-driven predictive models of health-related problems can be generated to inform decisions and actions,allowing to enhance productivity in new drug development,increase the cost-effectiveness of fully integrated health care systems and empower patients and healthy individuals to better manage their disease or their health,respectively.Consequently,the future will likely take the form of a computational precision medicine continuously informed by data capture and modeling to propose preventive measures or therapies precisely tailored to characteristics of each individual.

New Year's greeting and overview of Artificial Intelligence in Medical Imaging in 2021

As editors of Artificial Intelligence in Medical Imaging(AIMI),it is our great pleasure to take this opportunity to wish all of our authors,subscribers,readers,Editorial Board members,independent expert referees,and staff of the Editorial Office a Very Happy New Year.On behalf of the Editorial Team,we would like to express our gratitude to all of the authors who have contributed their valuable manuscripts,our independent referees,and our subscribers and readers for their continuous support,dedication,and encouragement.Together with an excellent of team effort by our Editorial Board members and staff of the Editorial Office,AIMI advanced in 2020 and we look forward to greater achievements in 2021.

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,

Deep learning-based subseasonal to seasonal precipitation prediction in southwest China:Algorithm comparison and sensitivity to input features

The prediction of precipitation at subseasonal to seasonal(S2S)timescales remains an enormous challenge because of the gap between weather and climate predictions.This study compares three deep learning algorithms,namely,the long short-term memory recurrent(LSTM),gated recurrent unit(GRU),and recurrent neural network(RNN),and selects the optimal algorithm to establish an S2S precipitation prediction model.The models were evaluated in four subregions of the Sichuan Province:the Plateau,Valley,eastern Basin,and western Basin.The results showed that the RNN model had better performance than the LSTM and GRU models.This could be because the RNN model had an advantage over the LSTM model in the transformation of climate indices with positive and negative variations.In the validation of test datasets,the RNN model successfully predicted the precipitation trend in most years during the wet season(May-October).The RNN model had a lower prediction bias(within±10%),higher sign accuracy of the precipitation trend(~88.95%),and greater accuracy of the maximum precipitation month(>0.85).For the prediction of different lead times,the RNN model was able to provide a stable trend prediction for summer precipitation,and the time correlation coefficient score was higher than that of the National Climate Center of China.Furthermore,this study proposed a method to measure the sensitivity of the RNN model to different input features,which may provide unprecedented insights into the nonlinear relationship and complicated feedback process among climate systems.The results of the sensitivity distribution are as follows.First,the Niño 4 and Niño 3.4 indices were equally important for the prediction of wet season precipitation.Second,the sensitivity of the snow cover on the Tibetan Plateau was higher than that in the Northern Hemisphere.Third,an opposite sensitivity appeared in two different patterns of the Indian Ocean and sea ice concentrations in the Arctic and the Barents Sea.