Role of AI for application of marketing teaching –A research perspective1

2020 ◽  
pp. 1-9
Author(s):  
Jiheng Hu ◽  
Boya Liu ◽  
Hao Peng
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Probabilistic Neural Network ◽  
Rapid Development ◽  
Development Trend ◽  
Colleges And Universities ◽  
System Reform ◽  
Good Convergence ◽  
Learning Platform ◽  
Modern Media

With the arrival of the era of artificial intelligence, based on the problems existing in the teaching process of marketing specialty, combined with the future business development trend and the core needs of enterprise operation, this paper analyzes the system reform of the practical courses of artificial intelligence and marketing specialty. With the rapid development of computer technology, intelligence has gradually become an important means to solve problems in various industries. In this paper, the modern media as a means, marketing teaching in Colleges and universities as the research background, through the establishment of the depth of marketing in Colleges and Universities Based on artificial intelligence network research learning platform, build a post-modern media communication perspective system. Based on probabilistic neural network and from the perspective of modern media marketing application system construction, the paper proves that the artificial intelligence prediction based on probabilistic neural network has good convergence, fault tolerance and data processing ability through MATLAB. Finally, this paper takes the pricing strategy in marketing as an example, and focuses on the application of artificial intelligence technology in marketing teaching from four aspects: preparation before class, implementation in class, consolidation after class and marketing teaching examination. According to the function and application of the theory of artificial intelligences in marketing teaching, we can find out that teachers must deeply understand the situation of each student’s artificial intelligences, so as to use the theory of artificial intelligences to change the traditional view of students and talents, and teach students according to their aptitude, so as to achieve better teaching effect.

scholarly journals Research Progress and Application of Computer Artificial Intelligence Technology

2018 ◽  
Vol 176 ◽  
pp. 01043 ◽  
Author(s):  
Jin Wei
Keyword(s):  
Artificial Intelligence ◽  
Rapid Development ◽  
Science And Technology ◽  
Development Trend ◽  
Concept Development ◽  
Research Progress ◽  
Huge Amount ◽  
Development History ◽  
Artificial Intelligence Technology ◽  
Major Application

With the development of science and technology, artificial intelligence technology has received more and more attention and attention. Under the background of the rapid development of big data and cloud computing, the artificial intelligence industry broke out. There is a huge amount of research on artificial intelligence and the artificial intelligence industry is huge. As far as the artificial intelligence industry in China is concerned, even the start is relatively late, but the industry scale, industrial layout, and technology research are all in a continuous improvement stage. Especially after the deepening of the layout of science and technology and manufacturing industries, the scale of artificial intelligence industry is further developed. More artificial intelligence products will appear at the same time. From the perspective of the concept, development history and new progress of artificial intelligence, this paper combines China’s artificial intelligence market and the development of artificial intelligence companies to analyze the current major application areas, and then further explore the future development trend of artificial intelligence.

The effectiveness of physical education teaching in college based on Artificial intelligence methods

2020 ◽  
pp. 1-11
Author(s):  
Zihao Li ◽  
Hejin Wang
Keyword(s):  
Artificial Intelligence ◽  
Physical Education ◽  
Rapid Development ◽  
Participation Rate ◽  
Colleges And Universities ◽  
The Body ◽  
Current Status ◽  
Innovative Teaching ◽  
Artificial Intelligence Technology ◽  
Low Activity

Traditional physical education in colleges and universities is difficult to arouse students’ interest in sports, resulting in low activity participation rate and inability to exercise the body. How to effectively improve the effectiveness of physical education in colleges and universities has become one of the hot topics of most concern from all walks of life. In physical education, innovative teaching concepts and methods, teaching methods and processes, and teaching evaluation methods are all conducive to improving the classroom atmosphere of physical education and successfully improve the effectiveness of physical education. This article focuses on analyzing the current status of physical education in colleges and universities. Based on the rapid development of artificial intelligence technology, how to improve the effectiveness of physical education is studied, and an experimental method is used to compare and analyze physical education in a college. The analysis results show that artificial intelligence-based physical education can obviously improve students’ strength quality, speed quality, endurance quality, and agility quality, which provides a more important reference and reference for improving the effectiveness of college physical education.

scholarly journals Design, Implementation, and Evaluation of Online English Learning Platforms

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Jie Li
Keyword(s):  
Neural Network ◽  
Online Learning ◽  
Performance Test ◽  
Rapid Development ◽  
Internet Technology ◽  
English Learning ◽  
Learning Platform ◽  
Learning Platforms ◽  
Questionnaire Surveys ◽  
And Performance

With the rapid development of internet technology, various online learning platforms have emerged. The combination of the internet and education is an inevitable trend, and smart online learning platforms based on neural network become popular. This paper introduces how to design online English learning platforms through a neural network. It proposes the construction of a universally designed online English learning platform and the design of an online English learning platform server development architecture. Then, the implementation of online English learning platforms is discussed. Evaluation of the platforms is also very important, which is conducted through two questionnaire surveys. The first survey is general and the second one is more specific. Results of both surveys show that the learners’ demand for online English learning platforms is still growing, especially among the young learners. In addition, this paper reports the results of the feasibility analysis and performance test of online English learning platforms: (1) The well-designed online English learning platform has relatively complete functions and meets the needs of both students and teachers. It includes a series of functional modules such as students’ registration, analysis of students’ profile, courseware and learning resources management, test management, test score analysis, interactive discussion, online monitor and feedback. (2) There are no major defects in the implementation of the online English learning platform in this experiment. (3) The reliability and security of the online English learning platform are relatively high.

scholarly journals Application of Computer Image Recognition Technology in Power Informationization

2021 ◽  
Vol 2074 (1) ◽  
pp. 012022
Author(s):  
Jiaxuan Li ◽  
Xin Wen
Keyword(s):  
Artificial Intelligence ◽  
Power System ◽  
Image Recognition ◽  
Reference Model ◽  
Rapid Development ◽  
Electric Energy ◽  
System Reform ◽  
Power Equipment ◽  
Practical Application ◽  
China’S Economy

Abstract With the rapid development of informationization, image recognition has been applied more and more deeply in various industries, and has become an important technical means in production and life, especially for the development of artificial intelligence. With the continuous development and progress of China’s economy and society, the demand for electricity is increasing. How to provide sufficient electric energy safely and efficiently for social development has become the key goal of power system reform. Power equipment detection is one of the earliest links to realize information in China’s power system. Because of its highly intelligent advantages, this technology can play an important role in the detection of power equipment, Which further improve the automation and intelligence level of power equipment detection. Starting from the practical application of this technology in power information, this paper analyzes some advantages that this technology can bring in power system, and provides a reference model for the popularization of this technology.

Automatic soil identification from penetrometric signal by using artificial intelligence techniques

2020 ◽  
Author(s):  
Carlos Sastre Jurado ◽  
P. Breul ◽  
Miguel Benz Navarette ◽  
C. Bacconnet
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Probabilistic Neural Network ◽  
Classification Models ◽  
Good Efficiency ◽  
Artificial Neuron ◽  
Neuron Networks ◽  
Geotechnical Characteristics ◽  
Geotechnical Tests

Conventional geotechnical soil classifications aim to classify soils into families with geotechnical characteristics and therefore similar behaviour, however, they require core samples and laboratory identification testing. Several empirical systems for estimating the nature of the soils have been developed on the basis of several in situ geotechnical tests. However, at present these systems remain empirical and they are often only used on an indicative basis. The objective of this article is, based on the analysis of dynamic penetrometric signals, to develop a methodology able to provide an estimate of the nature of the soil crossed. The methodology developed provide an automatic classification based on Artificial Neuron Networks (ANN) tools. Two types of ANN architectures were considered: Multilayer Feedforward Perceptron (MFP) and Probabilistic Neural Network (PNN). The learning of these two tools was achieved through a base carried out in the laboratory and in situ. The both classification models were then tested in blind conditions and showed a good efficiency for calibrated soils and promising results for in situ soils.

scholarly journals Research on the Collaborative Cultivation Mode of Logistics Specialty Talents under the Background of “New Business”

2021 ◽  
Vol 292 ◽  
pp. 02019
Author(s):  
Zhao Lei ◽  
Zhang Yanhua
Keyword(s):  
Research Collaboration ◽  
Rapid Development ◽  
Development Trend ◽  
Colleges And Universities ◽  
Theory And Practice ◽  
University Research ◽  
Market Demand ◽  
Logistics Industry ◽  
Cultivation Mode ◽  
New Business

With the development of the Internet and E-Commerce, logistics has maintained a sustained and rapid development trend since the 1980s. Its industry scale and service capacity have been significantly improved. It has become a new economic growth point in China, and logistics has become a pillar industry in the development of the national economy. With the vigorous development of logistics industry, more logistics talents are needed, and universities are the cradle of training talents. The logistics personnel training is far behind the logistics market demand, and those practice is weak during the process of the logistics professional teaching with the theory. Therefore, if there is chance to make a breakthrough, must rely on practical teaching to strengthen logistics theory and practice combination, with the help of practice process to improve the students’ practical ability, related handling problems and straining capacity, including effectively improvement the comprehensive ability of students, for achievement the effective docking of school education and enterprises. Production-University-Research Collaboration training is an important way to cultivate students’ practical ability and innovation ability, and it is also a new highlight of application-oriented universities, colleges and universities, as a new way to cultivate talents. School-enterprise integration practice teaching is the way to cultivate innovative talents and the core goal of higher education teaching reform in the new era. The collaborative cultivation mode of logistics talents provides an implementation plan for improving students’ practical ability, practical ability, problem-solving ability and strain ability, and also provides a specific realization path for logistics professionals, to provide comprehensive talents more in line with the needs of enterprises. Therefore, under the background of new business, it is necessary to strengthen the cooperation between logistics industry and enterprises, and strengthen the research mode of collaborative education of professional talents oriented by industry-university-research. On the one hand, it is conducive to the cultivation of applied talents in colleges and universities, and on the other hand, it lays a favorable foundation for our school to cultivate applied talents serving local areas.

scholarly journals Research on art design and application of indoor environment based on Artificial Intelligence

2021 ◽  
Vol 275 ◽  
pp. 03036
Author(s):  
Yao Hou ◽  
Xue-Feng Xu
Keyword(s):  
Artificial Intelligence ◽  
Design Theory ◽  
Rapid Development ◽  
Three Dimensional ◽  
Environmental Design ◽  
Development Trend ◽  
Future Trend ◽  
Design Activity ◽  
Wide Range ◽  
Art Design

The application of artificial intelligence in environmental design has entered a stage of rapid development, artificial intelligence in environmental design tools, methods, expression, as well as the expansion of design content, the richness of design language and other aspects have produced a wide range of changes. From the perspective of artificial intelligence in environmental design, this paper discusses the future trend and possible revolutionary changes of artificial intelligence in environmental design. This paper combs the application of artificial intelligence in environmental design, analyzes the design works with wide influence, and discusses the value and significance of artificial intelligence in applied environmental design, as well as its possible future development trend. The application of artificial intelligence in environmental design is a great change from design means to design content. From the interactive ability, virtual ability, to the integration of big data, all are new opportunities and challenges brought by the ability of artificial intelligence to environmental design. In response to such changes, environmental art design practitioners should establish a more systematic, three-dimensional and data-based design activity system and a broader design theory system.

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.

scholarly journals OP0327 EVALUATION OF THE ARTIFICIAL INTELLIGENCE SYSTEM ACCURACY IN DETERMINING THE RADIOGRAPHIC STAGE OF KNEE OSTEOARTHRITIS

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 201.2-201
Author(s):  
O. Georginova ◽  
M. Kobzar
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Rapid Development ◽  
Control Sample ◽  
Magnetic Resonance Images ◽  
Knee Joints ◽  
X Rays ◽  
Intelligence System ◽  
Consumer Healthcare ◽  
Machine Reading

Background:Within the last decade, rapid development of artificial neural networks and machine reading programs and their introduction into medical practice is reported [1,2,3]. Recently, an innovative program, based on the artificial intelligence (AI) technologies (a neural network and machine reading) that analyses knee X-ray images for determining the radiographic stage of OA was created. It was launched on the Osteoscan.ru website and is available for use by patients and doctors.Objectives:to validate the system ability to accurately stage OA through machine interpretation of standard knee radiographs.Methods:Initially, 1300 x-rays of both knee joints where used to teach the neural network. Of these, 350 were presented in the form of film scans, 950 in the DICOM format.The accuracy of the system in recognition of OA stage by knee radiographs was evaluated on a quality control sample of 130 cases (of all 1300). Independently, the radiographs were assessed by certified radiologists (considered the “gold standard”) and the System.Results:In 124 out of 130 cases the conclusion of a specialist and the System was the same, which represents 95.4% predictive power. Coincidence or discrepancy is a qualitative attribute, so, the accuracy of the estimation was calculated. Assuming a discrepancy of 0, and coincidence - of 1, µ = 0,954, the standard error sp= 1.8%. It can be concluded that in 95% of cases the accuracy of the system assessment will be in the range from 91.8% to 99%.Conclusion:Osteosan is a program developed on the base of AI technologies, analyzes radiographic images of the knee joints for determining OA stage. It provides high accuracy in OA stage determining by assessing knee radiographs, in 95% of cases, the accuracy of the system varies from 91.8% to 99%.References:[1]Fischl B, Salat DH, van der Kouwe AJ, Makris N, Ségonne F, Quinn BT, Dale AM. Sequence-independent segmentation of magnetic resonance images. Neuroimage. 2004;23 Suppl 1:S69-84[2]Faust O, Acharya U R, Ng EY, Ng KH, Suri JS. Algorithms for the automated detection of diabetic retinopathy using digital fundus images: a review. J Med Syst. 2012; 36(1): 145-57.[3]Balyen L, Peto T. Promising Artificial Intelligence-Machine Learning-Deep Learning Algorithms in Ophthalmology. Asia Pac J Ophthalmol (Phila). 2019; 8(3): 264-272.Disclosure of Interests:Olga Georginova Speakers bureau: GlaxoSmithKline Consumer Healthcare, Margarita Kobzar Employee of: GSK Consumer Healthcare

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