Study on the Application Fields and Development Prospects of Artificial Intelligence

2021 ◽  
Author(s):  
Li Xiaojun ◽  
Zhuo Xiande ◽  
Zhu Kexi ◽  
Deng Zhenli ◽  
Zhang Kai ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Application Fields ◽  
Development Prospects

scholarly journals Recent Advances in Self-Powered Piezoelectric and Triboelectric Sensors: From Material and Structure Design to Frontier Applications of Artificial Intelligence

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8422
Author(s):  
Zetian Yang ◽  
Zhongtai Zhu ◽  
Zixuan Chen ◽  
Mingjia Liu ◽  
Binbin Zhao ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Material Design ◽  
Structure Design ◽  
Flexible Sensors ◽  
Limited Life ◽  
Self Powered ◽  
Triboelectric Nanogenerators ◽  
Application Fields ◽  
The Internet Of Things ◽  
Development Prospects

The development of artificial intelligence and the Internet of things has motivated extensive research on self-powered flexible sensors. The conventional sensor must be powered by a battery device, while innovative self-powered sensors can provide power for the sensing device. Self-powered flexible sensors can have higher mobility, wider distribution, and even wireless operation, while solving the problem of the limited life of the battery so that it can be continuously operated and widely utilized. In recent years, the studies on piezoelectric nanogenerators (PENGs) and triboelectric nanogenerators (TENGs) have mainly concentrated on self-powered flexible sensors. Self-powered flexible sensors based on PENGs and TENGs have been reported as sensing devices in many application fields, such as human health monitoring, environmental monitoring, wearable devices, electronic skin, human–machine interfaces, robots, and intelligent transportation and cities. This review summarizes the development process of the sensor in terms of material design and structural optimization, as well as introduces its frontier applications in related fields. We also look forward to the development prospects and future of self-powered flexible sensors.

scholarly journals Container Multimodal Cooperative Transportation Management Information System Based on Artificial Intelligence Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Ling Wang ◽  
Shuai Fu
Keyword(s):  
Artificial Intelligence ◽  
Information System ◽  
Management Information System ◽  
Management Information ◽  
Efficient Operation ◽  
Multimodal Transportation ◽  
Multimodal Transport ◽  
Artificial Intelligence Technology ◽  
Application Fields ◽  
Transport Management

Artificial intelligence is a branch of computer science, which includes natural language, intelligent processing, and professional methods. Since the birth of artificial intelligence, the technology and application fields have continued to grow, and the application fields have also continued to expand. This article aims to study the application of artificial intelligence technology in the management information system of container multimodal transportation and to provide convenient and efficient operation methods for container multimodal transportation. This paper proposes the C-means clustering method. Through the research and development of the terminal management system, it has achieved great success in automation, intelligent planning, and integrated management. At the same time, the EDI system is adopted, which mainly uses the combination of GPS and GIS information platform Internet network technology. Therefore, when evaluating the operation of the multimodal transport virtual container under the control of coproduction, the DEA method is used to operate the multimodal virtual container. The situation is analyzed and evaluated, and the multimodal transport virtual container is determined through investment. The experimental results of this article show that the artificial intelligence system achieves the most efficient multimodal transport management with the most efficient system model, combined with the leading container multimodal transport virtual enterprise, to provide the best way of the management process for the development of the multimodal transport management information system. The intact rate of container cargo during transportation is as high as 99.7%.

scholarly journals Legal Regulation of the Use of Artificial Intelligence: Problems and Development Prospects

2021 ◽  
Vol 10 (1) ◽  
pp. 281
Author(s):  
Olena Yara ◽  
Anatoliy Brazheyev ◽  
Liudmyla Golovko ◽  
Viktoriia Bashkatova
Keyword(s):  
Artificial Intelligence ◽  
Human Rights ◽  
Human Activity ◽  
Code Of Ethics ◽  
Legal Regulation ◽  
Advantages And Disadvantages ◽  
Development Prospects

The article considers the advantages and disadvantages of using artificial intelligence (AI) in various areas of human activity. Particular attention was paid to the use of AI in the legal field. Prospects for the use of AI in the legal field were identified. The relevance of research on the legal regulation of the use of AI was proved. The use of AI raises an important problem of the compliance with general principles of ensuring human rights. Emphasis is placed on the need to develop and use a Code of ethics for artificial intelligence and legislation that would prevent its misapplication and minimize possible harmful consequences.

scholarly journals Budget Funding Priorities and Development Prospects of the US Artificial Intelligence

2021 ◽  
pp. 65-93
Author(s):  
Y. Selyanin
Keyword(s):  
Artificial Intelligence ◽  
National Security ◽  
Department Of Defense ◽  
Large Scale ◽  
Political Leadership ◽  
Intelligence Community ◽  
Existing Problems ◽  
The Us ◽  
Us Government ◽  
Development Prospects

The US Government has initiated a large-scale activity on artificial intelligence (AI) development and implementation. Numerous departments and agencies including the Pentagon, intelligence community and citizen agencies take part in these efforts. Some of them are responsible for technology, materials and standards development. Others are customers of AI. State AI efforts receive significant budget funding. Moreover, Department of Defense costs on AI are comparable with the whole non-defense funding. American world-leading IT companies support state departments and agencies in organizing AI technologies development and implementation. The USA's highest military and political leadership supports such efforts. Congress provides significant requested funding. However leading specialists criticize the state's approach to creating and implementing AI. Firstly, they consider authorized assignments as not sufficient. Secondly, even this funding is used ineffectively. Therefore Congress created National Security Commission on Artificial Intelligence (NSCAI) in 2018 for identifying problems in the AI area and developing solutions. This article looks at the stakeholders and participants of the state AI efforts, the budget funding authorization, the major existing problems and the NSCAI conclusions regarding the necessary AI funding in FYs 2021-2032.

USING EXPERT SYSTEMS FOR IMAGE UNDERSTANDING

1987 ◽  
Vol 01 (02) ◽  
pp. 237-250 ◽  
Author(s):  
P. SUETENS ◽  
A. OOSTERLINCK
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Expert Systems ◽  
Review Paper ◽  
Image Understanding ◽  
Interested Reader ◽  
Knowledge Based ◽  
Survey Papers ◽  
Application Fields

Expert systems and image understanding have traditionally been considered as two separate application fields of artificial intelligence (AI). In this paper it is shown, however, that the idea of building an expert system for image understanding may be fruitful. Although this paper may serve as a framework for situating existing works on knowledge-based vision, it is not a review paper. The interested reader will therefore be referred to some recommended survey papers in the literature.

scholarly journals CAREA: Cotraining Attribute and Relation Embeddings for Cross-Lingual Entity Alignment in Knowledge Graphs

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Baiyang Chen ◽  
Xiaoliang Chen ◽  
Peng Lu ◽  
Yajun Du
Keyword(s):  
Artificial Intelligence ◽  
Web Search ◽  
Threshold Value ◽  
Dynamic Threshold ◽  
Absolute Increase ◽  
Knowledge Graphs ◽  
Real World Datasets ◽  
Cross Lingual ◽  
Application Fields ◽  
Entity Relationships

Knowledge graphs (KGs) are one of the most widely used techniques of knowledge organizations and have been extensively used in many application fields related to artificial intelligence, for example, web search and recommendations. Entity alignment provides a useful tool for how to integrate multilingual KGs automatically. However, most of the existing studies evaluated ignore the abundant information of entity attributes except for entity relationships. This paper sets out to investigate cross-lingual entity alignment and proposes an iterative cotraining approach (CAREA) to train a pair of independent models. The two models can extract the attribute and the relation features of multilingual KGs, respectively. In each iteration, the two models alternate to predict a new set of potentially aligned entity pairs. Besides, this method further filters through the dynamic threshold value to enhance the two models’ supervision. Experimental results on three real-world datasets demonstrate the effectiveness and superiority of the proposed method. The CAREA model improves the performance with at least an absolute increase of 3.9 % across all experiment datasets. The code is available at https://github.com/ChenBaiyang/CAREA.

scholarly journals The Enlightening Role of Explainable Artificial Intelligence in Chronic Wound Classification

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1406
Author(s):  
Salih Sarp ◽  
Murat Kuzlu ◽  
Emmanuel Wilson ◽  
Umit Cali ◽  
Ozgur Guler
Keyword(s):  
Artificial Intelligence ◽  
Data Science ◽  
Chronic Wounds ◽  
Chronic Wound ◽  
Hybrid Approach ◽  
Black Box ◽  
Large Matrix ◽  
Explainable Artificial Intelligence ◽  
Wound Classification ◽  
Application Fields

Artificial Intelligence (AI) has been among the most emerging research and industrial application fields, especially in the healthcare domain, but operated as a black-box model with a limited understanding of its inner working over the past decades. AI algorithms are, in large part, built on weights calculated as a result of large matrix multiplications. It is typically hard to interpret and debug the computationally intensive processes. Explainable Artificial Intelligence (XAI) aims to solve black-box and hard-to-debug approaches through the use of various techniques and tools. In this study, XAI techniques are applied to chronic wound classification. The proposed model classifies chronic wounds through the use of transfer learning and fully connected layers. Classified chronic wound images serve as input to the XAI model for an explanation. Interpretable results can help shed new perspectives to clinicians during the diagnostic phase. The proposed method successfully provides chronic wound classification and its associated explanation to extract additional knowledge that can also be interpreted by non-data-science experts, such as medical scientists and physicians. This hybrid approach is shown to aid with the interpretation and understanding of AI decision-making processes.

scholarly journals Artificial Intelligence in Modern Journalism: History, Facts, Prospects for Development

2019 ◽  
Vol 8 (3) ◽  
pp. 555-568
Author(s):  
Olga Chertovskikh ◽  
Matvey Chertovskikh
Keyword(s):  
Artificial Intelligence ◽  
Mass Media ◽  
Technological Development ◽  
Human Society ◽  
Practical Application ◽  
Journalism History ◽  
History Of ◽  
Smart Machines ◽  
Further Development ◽  
Development Prospects

The article focuses on the issue of introduction of AI technology into the modern journalism. The topic proves to be of relevant importance as both mass media and press services reveal their direct dependence on the technological development level of the human society. It means that any new relevant technology can change the whole system. The objective of the article is to research the issue of Artificial Intelligence introduction into the modern journalism. The authors consider the history of the “smart machines” creation. Furthermore, they describe the current situation in the sphere of journalism, bring some specific examples of the existing and the projected systems and highlight the areas of possible practical application and the development prospects. They also obtain information on the main principles of the operation, the algorithms, the goals and the capabilities of the machines. In addition, the authors consider the advantages and the risks of this state-of-the-art technology, analyze the cultural and the psychological aspects of its mass introduction, make predictions concerning the prospects for the further development of this sphere, consider different scenarios of its development and identify the challenges and the advantages for the profession of a journalist. In conclusion, the authors state that despite the fact that AI in journalism is a mass phenomenon, all the projects of the introduction of Artificial Intelligence are not currently posing a direct threat to the profession. However, the fact that the mass media of different countries are starting to actively apply AI in journalism, emphasizes the relevance and the importance of further research in this sphere.

scholarly journals Research and Analysis of Machine Learning Algorithm in Artificial Intelligence

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Yang Li
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Research Status ◽  
Development Prospects

【Abstract】This article firstly explains the concepts of artificial intelligence and algorithm separately, then determines the research status of artificial intelligence and machine learning in the background of the increasing popularity of artificial intelligence, and finally briefly describes the machine learning algorithm in the field of artificial intelligence, as well as puts forward appropriate development prospects, in order to provide theoretical reference for industry insider.

scholarly journals THE INFLUENCE OF RAW MATERIALS ON THE PROPERTIES OF FOAM GLASS AND THE DEVELOPMENT PROSPECTS

2020 ◽  
Vol 3 (1) ◽  
pp. 44-48
Author(s):  
E. Latynceva ◽  
Ya. Podoynikova ◽  
T. Bezrukova ◽  
A. Murtazina
Keyword(s):  
Theoretical Analysis ◽  
Electromagnetic Radiation ◽  
Research Method ◽  
Raw Materials ◽  
Foam Glass ◽  
Industrial Wastes ◽  
Technical Literature ◽  
Main Components ◽  
Application Fields ◽  
Development Prospects

this paper considers the influence of raw components on the properties of foam glass and the development prospects of its use. The aim of the work is to identify the development prospects of foam glass appliance based on the study of the influence of raw materials on its properties. The task is to study the effect of initial materials on the properties of foam glass and the application fields of foam glass products in detail. To solve the problem a theoretical analysis of the scientific and technical literature and articles is used as a research method. As a result of the study, the main components used in the production of foam glass, their influence on the properties of the ready-made material and the application fields of foam glass products are considered. The authors draw a conclusion that the use of foam glass, which can reduce the effect of electromagnetic radiation, and foam glass made using industrial wastes is prospective

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