scholarly journals A Study on the Deduction and Diffusion of Promising Artificial Intelligence Technology for Sustainable Industrial Development

2020 ◽  
Vol 12 (14) ◽  
pp. 5609
Author(s):  
Hong Joo Lee ◽  
Hoyeon Oh
Keyword(s):  
Artificial Intelligence ◽  
Regression Analysis ◽  
Topic Modeling ◽  
Business Models ◽  
The United States ◽  
Growth Cycle ◽  
Bass Model ◽  
Artificial Intelligence Technology ◽  
Detailed Technique ◽  
And Diffusion

Based on the rapid development of Information and Communication Technology (ICT), all industries are preparing for a paradigm shift as a result of the Fourth Industrial Revolution. Therefore, it is necessary to study the importance and diffusion of technology and, through this, the development and direction of core technologies. Leading countries such as the United States and China are focusing on artificial intelligence (AI)’s great potential and are working to establish a strategy to preempt the continued superiority of national competitiveness through AI technology. This is because artificial intelligence technology can be applied to all industries, and it is expected to change the industrial structure and create various business models. This study analyzed the leading artificial intelligence technology to strengthen the market’s environment and industry competitiveness. We then analyzed the lifecycle of the technology and evaluated the direction of sustainable development in industry. This study collected and studied patents in the field of artificial intelligence from the US Patent Office, where technology-related patents are concentrated. All patents registered as artificial intelligence technology were analyzed by text mining, using the abstracts of each patent. The topic was extracted through topic modeling and defined as a detailed technique. Promising/mature skills were analyzed through a regression analysis of the extracted topics. In addition, the Bass model was applied to the promising technologies, and each technology was studied in terms of the technology lifecycle. Eleven topics were extracted via topic modeling. A regression analysis was conducted to identify the most promising/mature technology, and the results were analyzed with three promising technologies and five mature technologies. Promising technologies include Augmented Reality (AR)/Virtual Reality (VR), Image Recognition and Identification Technology. Mature technologies include pattern recognition, machine learning platforms, natural language processing, knowledge representation, optimization, and solving. This study conducts a quantitative analysis using patent data to derive promising technologies and then presents the objective results. In addition, this work then applies the Bass model to the promising artificial intelligence technology to evaluate the development potential and technology diffusion of each technology in terms of its growth cycle. Through this, the growth cycle of AI technology is analyzed in a complex manner, and this study then predicts the replacement timing between competing technologies.

scholarly journals Application of Artificial Intelligence Technology in Oncology: Towards the Establishment of Precision Medicine

Cancers ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3532 ◽  
Author(s):  
Ryuji Hamamoto ◽  
Kruthi Suvarna ◽  
Masayoshi Yamada ◽  
Kazuma Kobayashi ◽  
Norio Shinkai ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Precision Medicine ◽  
Medical Devices ◽  
The United States ◽  
Medical Data ◽  
Clinical Implementation ◽  
Medical Field ◽  
Core Technology ◽  
Artificial Intelligence Technology ◽  
History Of

In recent years, advances in artificial intelligence (AI) technology have led to the rapid clinical implementation of devices with AI technology in the medical field. More than 60 AI-equipped medical devices have already been approved by the Food and Drug Administration (FDA) in the United States, and the active introduction of AI technology is considered to be an inevitable trend in the future of medicine. In the field of oncology, clinical applications of medical devices using AI technology are already underway, mainly in radiology, and AI technology is expected to be positioned as an important core technology. In particular, “precision medicine,” a medical treatment that selects the most appropriate treatment for each patient based on a vast amount of medical data such as genome information, has become a worldwide trend; AI technology is expected to be utilized in the process of extracting truly useful information from a large amount of medical data and applying it to diagnosis and treatment. In this review, we would like to introduce the history of AI technology and the current state of medical AI, especially in the oncology field, as well as discuss the possibilities and challenges of AI technology in the medical field.

scholarly journals Research on Integrated Development Technology of Artificial Intelligence, Big Data and Cloud Computing

2021 ◽  
pp. 349-356
Author(s):  
Yu Qing
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Big Data ◽  
Development Strategy ◽  
Reference Value ◽  
The United States ◽  
Two Dimensions ◽  
Integrated Development ◽  
Development Technology ◽  
Artificial Intelligence Technology

Big data is profoundly changing our society and our way of production, life and thinking. At the same time, the development of big data continues to promote the innovation and breakthrough of artificial intelligence. Artificial intelligence is the focus of current research. All countries also raise artificial intelligence to the national strategic level and seize the commanding height of artificial intelligence. This paper analyzes the strategic characteristics of the development of artificial intelligence in the United States, Britain and Japan from the two dimensions of technology deployment and system guarantee. This paper studies the artificial intelligence technology based on big data and the development strategy of artificial intelligence, so as to provide a strategic idea for the development of artificial intelligence in China. The idea has a certain reference value for the research on the integrated development technology of artificial intelligence, big data and cloud computing.

scholarly journals Application of Artificial Intelligence Techniques in Operating Mode of Professors’ Academic Governance in American Research Universities

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Ruishu Wang ◽  
Jiannan Li ◽  
Wanbing Shi ◽  
Xin Li
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Research Universities ◽  
Operating Mode ◽  
The United States ◽  
Academic Governance ◽  
Artificial Intelligence Techniques ◽  
School Teaching ◽  
Artificial Intelligence Technology ◽  
American Research

Artificial intelligence technology is an important transformative force for teaching innovation in the intelligent era. It is being widely used in American school teaching, including the design of intelligent tutoring systems to achieve precise problem solving, the machine learning technology to ensure personalized activity design, the creation of intelligent virtual reality to promote classroom teaching contextualization, and the development of intelligent evaluation systems to ensure the scientific evaluation of capabilities. In the process of advancing the teaching and application of artificial intelligence technology, the United States has built a linkage mechanism of federal leadership, university follow-up, and social collaboration and implemented the smart technology in school teaching and professors’ academic governance. This paper is aimed at studying the professors’ academic governance of American research universities by Internet data mining, historical analysis method, documentary method, survey method, and other methods. Professors’ academic governance is a vital part of the modern university system that causes the institutional reform of the internal governance structure of modern universities. The United States is a powerful country in higher education, and professors in American research universities have always participated in university academic governance for centuries. By studying the definition, history, and development and mode of operation of professors’ academic governance in American research universities, the results indicate a clear division of power and responsibility between the professors and administrators based on an artificial intelligence decision system in American research universities. Also, there is a good communication platform based on artificial intelligence environment for professors to discuss their opinions on academic affairs. Third, professors exercise academic power under the guarantee of diversified guaranteed systems based on the artificial intelligence evaluation system and the ideology of mutual respect based on the artificial intelligence management and service system. Studying the application of artificial intelligence techniques in operating mode and enlightenment of professors’ academic governance in an American research university is of great significance to promote the construction of other modern universities’ professors’ academic governance system.

scholarly journals Impact of Social Network and Business Model on Innovation Diffusion of Electric Vehicles in China

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
D. Y. Kong ◽  
X. H. Bi
Keyword(s):  
Social Network ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicle ◽  
Business Models ◽  
Technological Development ◽  
The United States ◽  
Network Control ◽  
Local Market ◽  
Bass Model ◽  
Purchasing Model

The diffusion of electric vehicles (EVs) involves not only the technological development but also the construction of complex social networks. This paper uses the theory of network control to analyze the influence of network forms on EV diffusion in China, especially focusing on the building of EV business models (BMs) and the resulting effects and control on the diffusion of EVs. The Bass model is adopted to forecast the diffusion process of EVs and genetic algorithm is used to estimate the parameters based on the diffusion data of Hybrid Electric Vehicle (HEV) in the United States and Japan. Two different social network forms and BMs are selected, that is, battery leasing model and vehicle purchasing model, to analyze how different network forms may influence the innovation coefficient and imitation coefficient in the Bass model, which will in turn result in different diffusion results. Thereby, we can find the appropriate network forms and BMs for EVs which is suitable to the local market conditions.

Power, Conflict, and Effectiveness

2000 ◽  
Vol 5 (1) ◽  
pp. 28-33 ◽  
Author(s):  
M. Afzalur Rahim ◽  
David Antonioni ◽  
Krum Krumov ◽  
Snejana Ilieva
Keyword(s):  
United States ◽  
Regression Analysis ◽  
Interpersonal Conflict ◽  
The United States ◽  
Hierarchical Regression ◽  
Hierarchical Regression Analysis ◽  
Referent Power ◽  
Legitimate Power ◽  
Power Base ◽  
Effectiveness Data

This study investigated the relationships of bases of leader power (coercive, reward, legitimate, expert, and referent) and styles of handling interpersonal conflict (integrating, obliging, dominating, avoiding, and compromising) to subordinates' effectiveness. Data for this study were collected with questionnaires from the United States and Bulgaria and analyzed with hierarchical regression analysis for each country. Results indicated that in the United States referent power base of supervisors and integrating style of handling conflict of subordinates were positively associated with effectiveness. In Bulgaria, legitimate power base of supervisors was positively associated with effectiveness, but the subordinates' conflict styles were not associated with effectiveness.

Top 100 most-cited articles on medical imaging applications of artificial intelligence: a bibliometric analysis (Preprint)

2020 ◽  
Author(s):  
Ying Liu ◽  
Ziyan Yu ◽  
Shuolan Jing ◽  
Honghu Jiang ◽  
Chunxia Wang
Keyword(s):  
Artificial Intelligence ◽  
Medical Imaging ◽  
Bibliometric Analysis ◽  
Clinical Medicine ◽  
Medical Physics ◽  
Medical Image Analysis ◽  
The United States ◽  
Independent Learning ◽  
Learning Ability ◽  
Core Technology

BACKGROUND Artificial intelligence (AI) has penetrated into almost every aspect of our lives and is rapidly changing our way of life. Recently, the new generation of AI taking machine learning and particularly deep convolutional neural network theories as the core technology, has stronger learning ability and independent learning evolution ability, combined with a large amount of learning data, breaks through the bottleneck limit of model accuracy, and makes the model efficient use. OBJECTIVE To identify the 100 most cited papers in artificial intelligence in medical imaging, we performed a comprehensive bibliometric analysis basing on the literature search on Web of Science Core Collection (WoSCC). METHODS The 100 top-cited articles published in “AI, Medical imaging” journals were identified using the Science Citation Index Database. The articles were further reviewed, and basic information was collected, including the number of citations, journals, authors, publication year, and field of study. RESULTS The highly cited articles in AI were cited between 72 and 1,554 times. The majority of them were published in three major journals: IEEE Transactions on Medical Imaging, Medical Image Analysis and Medical Physics. The publication year ranged from 2002 to 2019, with 66% published in a three-year period (2016 to 2018). Publications from the United States (56%) were the most heavily cited, followed by those from China (15%) and Netherlands (10%). Radboud University Nijmegen from Netherlands, Harvard Medical School in USA, and The Chinese University of Hong Kong in China produced the highest number of publications (n=6). Computer science (42%), clinical medicine (35%), and engineering (8%) were the most common fields of study. CONCLUSIONS Citation analysis in the field of artificial intelligence in medical imaging reveals interesting information about the topics and trends negotiated by researchers and elucidates which characteristics are required for a paper to attain a “classic” status. Clinical science articles published in highimpact specialized journals are most likely to be cited in the field of artificial intelligence in medical imaging.

Accidental Sustainability

2017 ◽  
Author(s):  
Geoffrey Jones
Keyword(s):  
Large Scale ◽  
Negative Impact ◽  
Positive Impact ◽  
Organic Food ◽  
The United States ◽  
Air Travel ◽  
Business Leaders ◽  
Natural Beauty ◽  
And Diffusion ◽  
Whole Foods

This chapter examines the scaling and diffusion of green entrepreneurship between 1980 and the present. It explores how entrepreneurs and business leaders promoted the idea that business and sustainability were compatible. It then examines the rapid growth of organic foods, natural beauty, ecological architecture, and eco-tourism. Green firms sometimes grew to a large scale, such as the retailer Whole Foods Market in the United States. The chapter explores how greater mainstreaming of these businesses resulted in a new set of challenges arising from scaling. Organic food was now transported across large distances causing a negative impact on carbon emissions. More eco-tourism resulted in more air travel and bigger airports. In other industries scaling had a more positive impact. Towns were major polluters, so more ecological buildings had a positive impact.

scholarly journals A Study of Automatic Judgment of Food Color and Cooking Conditions with Artificial Intelligence Technology

Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1128
Author(s):  
Chern-Sheng Lin ◽  
Yu-Ching Pan ◽  
Yu-Xin Kuo ◽  
Ching-Kun Chen ◽  
Chuen-Lin Tien
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Color Space ◽  
Color Difference ◽  
Color Space Conversion ◽  
Before And After ◽  
Artificial Intelligence Technology ◽  
Artificial Intelligence Algorithm ◽  
Time Image ◽  
Cooking Conditions

In this study, the machine vision and artificial intelligence algorithms were used to rapidly check the degree of cooking of foods and avoid the over-cooking of foods. Using a smart induction cooker for heating, the image processing program automatically recognizes the color of the food before and after cooking. The new cooking parameters were used to identify the cooking conditions of the food when it is undercooked, cooked, and overcooked. In the research, the camera was used in combination with the software for development, and the real-time image processing technology was used to obtain the information of the color of the food, and through calculation parameters, the cooking status of the food was monitored. In the second year, using the color space conversion, a novel algorithm, and artificial intelligence, the foreground segmentation was used to separate the vegetables from the background, and the cooking ripeness, cooking unevenness, oil glossiness, and sauce absorption were calculated. The image color difference and the distribution were used to judge the cooking conditions of the food, so that the cooking system can identify whether or not to adopt partial tumbling, or to end a cooking operation. A novel artificial intelligence algorithm is used in the relative field, and the error rate can be reduced to 3%. This work will significantly help researchers working in the advanced cooking devices.

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