Future directions of chemical theory and computation

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Yuyuan Lu ◽  
Geng Deng ◽  
Zhigang Shuai
Keyword(s):  
Artificial Intelligence ◽  
Statistical Mechanics ◽  
Computational Chemistry ◽  
High Performance ◽  
Rapid Development ◽  
Structural Theory ◽  
Dynamic Simulations ◽  
Future Directions ◽  
New Era ◽  
Chemical Theory

Abstract Theoretical and computational chemistry aims to develop chemical theory and to apply numerical computation and simulation to reveal the mechanism behind complex chemical phenomena via quantum theory and statistical mechanics. Computation is the third pillar of scientific research together with theory and experiment. Computation enables scientists to test, discover, and build models/theories of the corresponding chemical phenomena. Theoretical and computational chemistry has been advanced to a new era due to the development of high-performance computational facilities and artificial intelligence approaches. The tendency to merge electronic structural theory with quantum chemical dynamics and statistical mechanics is of increasing interest because of the rapid development of on-the-fly dynamic simulations for complex systems plus low-scaling electronic structural theory. Another challenging issue lies in the transition from order to disorder, from thermodynamics to dynamics, and from equilibrium to non-equilibrium. Despite an increasingly rapid emergence of advances in computational power, detailed criteria for databases, effective data sharing strategies, and deep learning workflows have yet to be developed. Here, we outline some challenges and limitations of the current artificial intelligence approaches with an outlook on the potential future directions for chemistry in the big data era.

scholarly journals Application of digital technology innovation in campus cultural and creative design——Take Jiangxi University of Finance and Economics as an example

2021 ◽  
Vol 236 ◽  
pp. 05041
Author(s):  
Song Pan ◽  
Wen Qiang ◽  
Zhang Xiangsen
Keyword(s):  
Artificial Intelligence ◽  
Digital Technology ◽  
Technology Innovation ◽  
Brand Image ◽  
Rapid Development ◽  
Creative Design ◽  
New Era ◽  
University Culture ◽  
Advanced Technologies ◽  
Creative Products

With the rapid development of information technology and the continuous emergence of artificial intelligence, big data, cloud computing and other advanced technologies, design ushers in a new era of digital technology. The innovative application of digital technology in contemporary design in China promotes the rapid development of cultural and creative design. As an important carrier of university culture, cultural and creative products have become an important part of the construction of university culture, which plays an important role in publicizing the school cultural characteristics and promoting the school brand image. Based on the analysis of excellent campus cultural and creative cases at home and abroad, taking Jiangxi University of Finance and economics as an example, this paper explores the new application of digital technology in contemporary cultural and creative design.

The Aviation Engine

1950 ◽  
Vol 162 (1) ◽  
pp. 433-445 ◽  
Author(s):  
F. R. Banks
Keyword(s):  
Gas Turbine ◽  
Automobile Industry ◽  
High Performance ◽  
Rapid Development ◽  
Great Part ◽  
Piston Engine ◽  
Royal Air Force ◽  
New Era ◽  
Large Numbers ◽  
Aviation Engines

This lecture is an attempt to give a cross-section of aviation engine development and progress during the last two decades. Such a lecture is now opportune, since great progress has been made during the last ten years—mainly due to the 1939–45 war and the advent of the aviation gas turbine. The rapid development of this prime-mover has started a new era in aviation and the well-tried piston engine is already being relegated to second place and even eliminated in the more important aircraft applications. The lecture is divided into two parts. The first deals with the piston engine and the second with the gas turbine. In the first part, the development of the piston engine is discussed; with emphasis upon those factors, such as supercharging and improved fuel, which have particularly contributed to its present high performance. Cooling developments of both the air- and the liquid-cooled engine are discussed, and also the influence of such detail refinements as the sodium-cooled valve and sparking plugs having sintered aluminium oxide insulators. The second part of the lecture describes the present forms of aviation gas turbine, with some details of its specific performance and the author's views concerning the future development and application of this new engine. At the request of the Council, and where relevant, the author has shown how the development of the aviation engine has influenced that of the automobile engine and he has also given—in Appendix I—a summary of his views on the application of the gas turbine to road-vehicle propulsion. This lecture would not be complete without reference to the great part played, in the 1939–45 war, by the aviation engine and automobile industries of Britain, in combining to produce large numbers of aviation engines for the Royal Air Force. In this particular connexion, the author is of the opinion that the experience and the production methods of the automobile industry, as a whole, contributed largely to the uniform excellence and economical production of the aviation engine, and fully vindicated the faith of those who originated the “Shadow” scheme in the rearmament period before the war.

scholarly journals Research on the Social Impact of Artificial Intelligence and Government’s Coping Strategies

2020 ◽  
pp. 114-123
Author(s):  
Weili Tian
Keyword(s):  
Artificial Intelligence ◽  
Social Life ◽  
Social Impact ◽  
Rapid Development ◽  
Human Society ◽  
Chinese Media ◽  
New Era ◽  
The World ◽  
The Face ◽  
Intelligence Development

“Artificial intelligence” is one of the most popular buzzwords in the society at present, and was selected as the “Top Ten Chinese Media Popularity in 2017”. Human society is gradually entering a new era of artificial intelligence. Artificial intelligence is not just a scientific and technological innovation, but will bring about a big change in social life. As the State Council’s “New Generation Artificial Intelligence Development Plan” pointed out: “The rapid development of artificial intelligence will profoundly change human social life and change the world.” In the face of the new situation in the new era, governments at all levels must take the initiative to seek change and change, firmly grasp the major historical opportunities for the development of artificial intelligence, keep abreast of development, research and judge the general trend, actively plan, grasp the direction, seize the opportunities, and lead the world in the development of artificial intelligence. The trend, serving economic and social development and supporting national security, drives the overall leap and leapfrog development of national competitiveness.

scholarly journals Joint Channel Pruning and Quantization-Based CNN Network Learning with Mobile Computing-Based Image Recognition

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Huanyu Liu ◽  
Qing Luo ◽  
Mingmei Shao ◽  
Jeng-Shyang Pan ◽  
Junbao Li
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Rapid Development ◽  
Computational Cost ◽  
The Internet ◽  
New Era ◽  
Practical Applications ◽  
Model Compression ◽  
Smart Healthcare ◽  
Artificial Intelligence Technology

The development of the Internet and communication technology has ushered in a new era of the Internet of Things (IoT). Moreover, with the rapid development of artificial intelligence, objects are endowed with intelligence, such as home automation and smart healthcare, which are typical applications of artificial intelligence technology in IoT. With the rise of convolutional neural network (CNN) in the field of computer vision, more and more practical applications need to deploy CNN on mobile devices. However, due to the large amount of CNN computing operations and the large number of parameters, it is difficult to deploy on ordinary edge devices. The neural network model compression method has become a popular technology to reduce the computational cost and has attracted more and more attention. We specifically design a small target detection network for hardware platforms with limited computing resources, use pruning and quantization methods to compress, and demonstrate in VOC dataset and RSOD dataset on the actual hardware platform. Experiments show that the proposed method can maintain a fairly accurate rate while greatly speeding up the inference speed.

Surface/interface nanoengineering for rechargeable Zn–air batteries

2020 ◽  
Vol 13 (4) ◽  
pp. 1132-1153 ◽  
Author(s):  
Tianpei Zhou ◽  
Nan Zhang ◽  
Changzheng Wu ◽  
Yi Xie
Keyword(s):  
High Performance ◽  
Rapid Development

Surface/interface nanoengineering of electrocatalysts and air electrodes will promote the rapid development of high-performance rechargeable Zn–air batteries.

High Performance Thin Layer Chromatography (HPTLC) for the Investigation of Medicinal Plants

2020 ◽  
Vol 16 ◽  
Author(s):  
Alper Gökbulut
Keyword(s):  
Medicinal Plants ◽  
High Performance ◽  
Separation Efficiency ◽  
Rapid Development ◽  
Herbal Remedies ◽  
Qualitative And Quantitative ◽  
Powerful Analytical Tool ◽  
Quantitative Examination ◽  
Data Acquisition And Processing ◽  
Layer Chromatography

Background: Chromatographic techniques such as TLC basically and, HPLC, GC, HPTLC equipped with various detectors are most frequently used for the qualitative and quantitative examination of herbals. Method: An overview of the recent literature concerning the usage of HPTLC for the analysis of medicinal plants has been reviewed. Results: During the last decade/s, HPTLC, a modern, sophisticated and automatized TLC technique with better and advanced separation efficiency, detection limit, data acquisition and processing, has been used for the analysis of herbal materials and preparations since the rapid development of technology in chromatography world. HPTLC with various detectors is a powerful analytical tool especially for the phytochemical applications such as herbal drug quantification and fingerprint analysis. Conclusion: In this review, a latest perspective has been established and some of the previous studies were summarized for the usage of HPTLC in the analysis of herbal remedies, dietary supplements and nutraceuticals.

МЕТОДЫ ДОСТИЖЕНИЯ МАКСИМАЛЬНОЙ ЭФФЕКТИВНОСТИ ПЛАТФОРМЫ ПРОТОТИПИРОВАНИЯ ВЫСОКОПРОИЗВОДИТЕЛЬНЫХ СИСТЕМ НА КРИСТАЛЛЕ НА ЗАДАЧАХ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА

2020 ◽  
Vol 96 (3s) ◽  
pp. 585-588
Author(s):  
С.Е. Фролова ◽  
Е.С. Янакова
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Computer Vision ◽  
High Performance ◽  
Systems On Chip ◽  
High Performance Systems ◽  
On Chip ◽  
Network Technologies ◽  
Neural Network Technologies

Предлагаются методы построения платформ прототипирования высокопроизводительных систем на кристалле для задач искусственного интеллекта. Изложены требования к платформам подобного класса и принципы изменения проекта СнК для имплементации в прототип. Рассматриваются методы отладки проектов на платформе прототипирования. Приведены результаты работ алгоритмов компьютерного зрения с использованием нейросетевых технологий на FPGA-прототипе семантических ядер ELcore. Methods have been proposed for building prototyping platforms for high-performance systems-on-chip for artificial intelligence tasks. The requirements for platforms of this class and the principles for changing the design of the SoC for implementation in the prototype have been described as well as methods of debugging projects on the prototyping platform. The results of the work of computer vision algorithms using neural network technologies on the FPGA prototype of the ELcore semantic cores have been presented.

The Oxford Handbook of Ethics of AI

2020 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Ethical Issues ◽  
Rapid Development ◽  
Data Driven ◽  
International Human Rights Law ◽  
Human Knowledge ◽  
Human Rights Law ◽  
Ai Ethics ◽  
And Behavior ◽  
Control Complex

This book explores the intertwining domains of artificial intelligence (AI) and ethics—two highly divergent fields which at first seem to have nothing to do with one another. AI is a collection of computational methods for studying human knowledge, learning, and behavior, including by building agents able to know, learn, and behave. Ethics is a body of human knowledge—far from completely understood—that helps agents (humans today, but perhaps eventually robots and other AIs) decide how they and others should behave. Despite these differences, however, the rapid development in AI technology today has led to a growing number of ethical issues in a multitude of fields, ranging from disciplines as far-reaching as international human rights law to issues as intimate as personal identity and sexuality. In fact, the number and variety of topics in this volume illustrate the width, diversity of content, and at times exasperating vagueness of the boundaries of “AI Ethics” as a domain of inquiry. Within this discourse, the book points to the capacity of sociotechnical systems that utilize data-driven algorithms to classify, to make decisions, and to control complex systems. Given the wide-reaching and often intimate impact these AI systems have on daily human lives, this volume attempts to address the increasingly complicated relations between humanity and artificial intelligence. It considers not only how humanity must conduct themselves toward AI but also how AI must behave toward humanity.

scholarly journals How Do Machines Learn? Artificial Intelligence as a New Era in Medicine

2021 ◽  
Vol 11 (1) ◽  
pp. 32
Author(s):  
Oliwia Koteluk ◽  
Adrian Wartecki ◽  
Sylwia Mazurek ◽  
Iga Kołodziejczak ◽  
Andrzej Mackiewicz
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Health Care ◽  
Medical Data ◽  
General Process ◽  
New Era ◽  
Automated Evaluation ◽  
Machine Learning Applications ◽  
And Training ◽  
Current Standards

With an increased number of medical data generated every day, there is a strong need for reliable, automated evaluation tools. With high hopes and expectations, machine learning has the potential to revolutionize many fields of medicine, helping to make faster and more correct decisions and improving current standards of treatment. Today, machines can analyze, learn, communicate, and understand processed data and are used in health care increasingly. This review explains different models and the general process of machine learning and training the algorithms. Furthermore, it summarizes the most useful machine learning applications and tools in different branches of medicine and health care (radiology, pathology, pharmacology, infectious diseases, personalized decision making, and many others). The review also addresses the futuristic prospects and threats of applying artificial intelligence as an advanced, automated medicine tool.

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