Simulation of English feature recognition based on machine learning and artificial intelligence technology

2021 ◽  
Author(s):  
Li Na
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Feature Recognition ◽  
Artificial Intelligence Technology

Development of migrant workers in construction based on machine learning and artificial intelligence technology

2020 ◽  
pp. 1-12
Author(s):  
Chen Guang
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Labor Force ◽  
Migrant Workers ◽  
Engineering Industry ◽  
Agricultural Industry ◽  
Construction Engineering ◽  
Artificial Intelligence Technology ◽  
Chinese Labor ◽  
The Times

Artificial intelligence technology has been widely used in all aspects of our life. Similarly, the application of artificial intelligence in the field of construction engineering is a necessary trend in the development of engineering industry, especially in the traditional construction engineering department. Under the background of the times, from the perspective of knowledge, artificial intelligence technology has appeared a huge development, which may have an impact on the employment of Chinese labor force, may create new jobs, or replace traditional jobs. This effect on employment is essential. From the perspective of machine learning and artificial intelligence, this paper reviews the transformation prospects of engineering industry and the development of agricultural industry in construction industry, and examines the intellectual transformation of individual human capital in Chinese labor force.

scholarly journals Application of Sensors in Intelligent Clothing Design

2018 ◽  
Vol 14 (06) ◽  
pp. 4
Author(s):  
Shali Jiang ◽  
Qiong Ren
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Experimental Results ◽  
Machine Learning Method ◽  
Learning Method ◽  
Clothing Design ◽  
Artificial Intelligence Technology ◽  
Contact Sensor ◽  
Intelligent Clothing ◽  
Contact Sensors

<p class="0abstract"><span lang="EN-US">In order to study the application of sensors in intelligent clothing design, the artificially intelligent cutting-edge technology -machine learning method was proposed to combine a variety of signals of non-contact sensors in several different positions. Higher accuracy was achieved, while maintaining the comfort brought by a non-contact sensor. The experimental results showed that the proposed strategy focused on the combination of clothing design technology and artificial intelligence technology. As a result, without changing the sensor materials, it enhances the comfort and precision of clothing, eliminates the comfort reduced by sensor close to the skin, and transforms inaccurate measurement into accurate measurement. </span></p>

scholarly journals Machine Learning Based Behavioral Modification

2019 ◽  
Vol 8 (6S2) ◽  
pp. 1134-1138
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Behavior Analysis ◽  
Time Of Day ◽  
Computational Techniques ◽  
Behavioral Modification ◽  
Optimal Temperature ◽  
The Past ◽  
Different Types ◽  
Artificial Intelligence Technology

To build up a particular profile about a person, the study of examining the comportment is known as Behavior analysis. Initially the Behavior analysis is used in psychology and for suggesting and developing different types the application content for user then it developed in information technology. To make the applications for user's personal needs it becoming a new trends with the use of artificial intelligence (AI). in many applications like innovation to do everything from anticipating buy practices to altering a home's indoor regulator to the inhabitant's optimal temperature for a specific time of day use machine learning and artificial intelligence technology. The technique that is use to advance the rule proficiency that rely upon the past experience is known as machine learning. By utilizing the insights hypothesis it makes the numerical model, and its real work is to infer from the models gave. To take the information clearly from the data the methodology utilizes computational techniques.

Recent Advances in Medical Image Processing

2020 ◽  
pp. 1-14
Author(s):  
Zhen Huang ◽  
Qiang Li ◽  
Ju Lu ◽  
Junlin Feng ◽  
Jiajia Hu ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Machine Learning ◽  
Image Processing ◽  
Medical Imaging ◽  
Medical Image ◽  
Medical Image Processing ◽  
Convolution Neural Network ◽  
Artificial Intelligence Technology ◽  
Deep Convolution Neural Network

<b><i>Background:</i></b> Application and development of the artificial intelligence technology have generated a profound impact in the field of medical imaging. It helps medical personnel to make an early and more accurate diagnosis. Recently, the deep convolution neural network is emerging as a principal machine learning method in computer vision and has received significant attention in medical imaging. <b><i>Key Message:</i></b> In this paper, we will review recent advances in artificial intelligence, machine learning, and deep convolution neural network, focusing on their applications in medical image processing. To illustrate with a concrete example, we discuss in detail the architecture of a convolution neural network through visualization to help understand its internal working mechanism. <b><i>Summary:</i></b> This review discusses several open questions, current trends, and critical challenges faced by medical image processing and artificial intelligence technology.

Design of industrial internet of things system based on machine learning and artificial intelligence technology

2020 ◽  
pp. 1-11
Author(s):  
Xu Kun ◽  
Zhiliang Wang ◽  
Ziang Zhou ◽  
Wang Qi
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Internet Of Things ◽  
Monitoring System ◽  
Remote Monitoring ◽  
Industrial Equipment ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Test Platform ◽  
Artificial Intelligence Technology

For industrial production, the traditional manual on-site monitoring method is far from meeting production needs, so it is imperative to establish a remote monitoring system for equipment. Based on machine learning algorithms, this paper combines artificial intelligence technology and Internet of Things technology to build an efficient, fast, and accurate industrial equipment monitoring system. Moreover, in view of the characteristics of the diverse types of equipment, scattered layout, and many parameters in the manufacturing equipment as well as the complexity of the high temperature, high pressure, and chemical environment in which the equipment is located, this study designs and implements a remote monitoring and data analysis system for industrial equipment based on the Internet of Things. In addition, based on the application scenarios of the actual aeronautical weather floating platform test platform, this study combines the platform prototype system to design and implement a set of strong real-time communication test platform based on the Windows operating system. The test results show that the industrial Internet of Things system based on machine learning and artificial intelligence technology constructed in this paper has certain practicality.

Logistics engineering optimization based on machine learning and artificial intelligence technology

2020 ◽  
pp. 1-12
Author(s):  
Suhua Bu
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Optimal Solution ◽  
Engineering Optimization ◽  
Artificial Intelligence Technology ◽  
Important Means ◽  
Practical Effect ◽  
Combined Classifier ◽  
The Internet Of Things

In the era of the Internet of Things, smart logistics has become an important means to improve people’s life rhythm and quality of life. At present, some problems in logistics engineering have caused logistics efficiency to fail to meet people’s expected goals. Based on this, this paper proposes a logistics engineering optimization system based on machine learning and artificial intelligence technology. Moreover, based on the classifier chain and the combined classifier chain, this paper proposes an improved multi-label chain learning method for high-dimensional data. In addition, this study combines the actual needs of logistics transportation and the constraints of the logistics transportation process to use multi-objective optimization to optimize logistics engineering and output the optimal solution through an artificial intelligence model. In order to verify the effectiveness of the model, the performance of the method proposed in this paper is verified by designing a control experiment. The research results show that the logistics engineering optimization based on machine learning and artificial intelligence technology proposed in this paper has a certain practical effect.

Artificial Intelligence and the Temporality of Machine Images

2021 ◽  
Author(s):  
Andrew R. Johnston
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Video Games ◽  
Learning Strategies ◽  
Learning Algorithms ◽  
Computational Time ◽  
Artificial Intelligence Technology ◽  
Learning Test ◽  
The Relationship

DeepMind, a recent artificial intelligence technology created at Google, references in its name the relationship in AI between models of cognition used in this technology‘s development and its new deep learning algorithms. This chapter shows how AI researchers have been attempting to reproduce applied learning strategies in humans but have difficulty accessing and visualizing the computational actions of their algorithms. Google created an interface for engaging with computational temporalities through the production of visual animations based on DeepMind machine-learning test runs of Atari 2600 video games. These machine play animations bear the traces of not only DeepMind‘s operations, but also of contemporary shifts in how computational time is accessed and understood.

scholarly journals The Rise of Deepfakes: A Conceptual Framework and Research Agenda for Marketing

2021 ◽  
pp. 183933492199947
Author(s):  
Lucas Whittaker ◽  
Kate Letheren ◽  
Rory Mulcahy
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Conceptual Framework ◽  
Research Agenda ◽  
Theory And Practice ◽  
Digital Content ◽  
Future Research ◽  
Marketing Theory ◽  
Artificial Intelligence Technology ◽  
The Media

Deepfakes, digital content created via machine learning, a form of artificial intelligence technology, are generating interest among marketers and the general population alike and are often portrayed as a “phantom menace” in the media. Despite relevance to marketing theory and practice, deepfakes—and the opportunities for benefit or deviance they provide—are little understood or discussed. This article introduces deepfakes to the marketing literature and proposes a typology, conceptual framework, and associated research agenda, underpinned by theorizing based on balanced centricity, to guide the future investigation of deepfakes in marketing scholarship. The article makes an argument for balance (i.e., situations where all stakeholders benefit), and it is hoped that this article may provide a foundation for future research and application of deepfakes as “a new hope” for marketing.

scholarly journals A review of the use of artificial intelligence in orthodontics

2021 ◽  
Vol 38 (SI-2) ◽  
pp. 157-162
Author(s):  
Serdar AKDENİZ ◽  
Muhammet Emir TOSUN
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Current Literature ◽  
Treatment Process ◽  
Review Article ◽  
Clinical Use ◽  
Efficient Treatment ◽  
Artificial Intelligence Technology ◽  
Near Future

The clinical use of artificial intelligence technology in orthodontics has increased significantly in recent years. Artificial intelligence can be utilized in almost every part of orthodontic workflow. It is an important decision making aid as well as a tool for building more efficient treatment mechanics. The use of artificial intelligence reduces costs, speeds up the diagnosis and treatment process and reduces or even eliminates the need for manpower. This review article evaluates the current literature on artificial intelligence and machine learning in the field of orthodontics. The areas that the artificial intelligence is still lacking were also discussed in detail. Despite its shortcomings, artificial intelligence is considered to have an integral part of orthodontic practice in the near future.

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