scholarly journals Unattended Video Classifying System based on Transfer Leaning

2019 ◽  
Vol 3 (5) ◽  
Author(s):  
Yarong Li
Keyword(s):  
Artificial Intelligence ◽  
Human Resources ◽  
Traditional Method ◽  
Great Increase ◽  
Low Cost ◽  
The Internet ◽  
Average Wage ◽  
Content Recognition ◽  
Short Video ◽  
Great Development

As the internet techniques advances, the demand of entertainment of the general public increases rapidly. A majority of short video applications like “TikTok” have appeared. The unbelievable growth of the number of the new videos and the increase of the average wage makes it almost impossible to identify the categories of the videos manually. In order to cater to the users’ preferences efficiently, detecting the content of the videos is inevitable. Fortunately, due to the great development on both the algorithm and hardware, the golden era of artificial intelligence is coming which makes it is possible to use computers to recognize the content of the videos. Comparing to the traditional method of content recognition, machine learning increases the efficiency with low cost, which is a better way to cope with the conflicts between the great increase of the number of the new videos uploaded by users and the lack of human resources.

scholarly journals The ideology of information and computer technology as a vector of development of intellectual resources in a digital society

2019 ◽  
Vol 31 (1) ◽  
pp. 84-88
Author(s):  
N. Kirichenko
Keyword(s):  
Artificial Intelligence ◽  
Human Resources ◽  
Computer Technology ◽  
High Tech ◽  
The Internet ◽  
Digital Society ◽  
Technological Unemployment ◽  
Computer Technologies ◽  
Information And Computer Technology ◽  
The World

The relevance of the study of this problem is that information and computer technologies contribute to the development of digital society, based on the development of human resources that are intellectual capital.  Information and computer technology affect the development of machines that replaced people and gave rise to "technological unemployment."  The purpose of the study is to show how the information revolution of the twenty-first century contributes to the reduction of labor as a result of progressive robotization.  The technologies that are used today to replace people are different; the need for human resources is reduced thanks to robots, computers and other high-tech gadgets.  Methods of theoretical analysis - deduction and induction, historical and logical, comparative and structural-genetic analysis, information method, which contribute to the insight into the essence of the phenomenon under study as a complex phenomenon and dynamic process.  Results: It has been proven that, thanks to various well-known developments in information-computer technologies and robotics, many experts believe that society is at an early stage of the new industrial (post-industrial) revolution, which in the future can change the way people live and work just like  200 years ago made a steam engine.  Technological unemployment is one of the main reasons for the increase in the overall unemployment rate in Western countries over the past 30 years.  Although to some extent this is due to the demographic revolution and the changing structure of the economy in many countries, the development of information and computer technologies, as well as other types of automation and the Internet have played a significant role, especially since 2000.  Findings.  We have shown that many jobs with cheap labor can disappear, because the digital society focuses on the development of human (intellectual) resources.  The world is turning into a digital society and the world is ruled by a figure based on intelligence, intelligence, algorithms, digitalization.  The digital society consists of a set of algorithms that are controlled by information and computer technologies that penetrate digital management, which is based on intellectual-rational force represented by human resources.  It is human resources that develop robotics, artificial intelligence, computerization, mechanization, robotization, which are based on robotics, artificial intelligence.  These varieties of digital society will accelerate the potential for long-term productivity gains through intellectualization.  Practical recommendations - to develop a small business that rests on the network of intelligent platforms, in connection with which to create jobs on the Internet and create new types of employment.

Bringing Security to The Smallest Embedded Systems

2017 ◽  
Author(s):  
JOSEPH YIU
Keyword(s):  
Internet Of Things ◽  
Embedded Systems ◽  
Low Cost ◽  
Security Requirements ◽  
The Internet ◽  
Security Measures ◽  
Significant Challenge ◽  
Iot Devices

The increasing need for security in microcontrollers Security has long been a significant challenge in microcontroller applications(MCUs). Traditionally, many microcontroller systems did not have strong security measures against remote attacks as most of them are not connected to the Internet, and many microcontrollers are deemed to be cheap and simple. With the growth of IoT (Internet of Things), security in low cost microcontrollers moved toward the spotlight and the security requirements of these IoT devices are now just as critical as high-end systems due to:

Virtual Screening Meets Deep Learning

2018 ◽  
Vol 15 (1) ◽  
pp. 6-28 ◽  
Author(s):  
Javier Pérez-Sianes ◽  
Horacio Pérez-Sánchez ◽  
Fernando Díaz
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Virtual Screening ◽  
Great Increase ◽  
New Drugs ◽  
Learning Approach ◽  
Screening Strategies ◽  
Computer Aided ◽  
Recent Developments

Background: Automated compound testing is currently the de facto standard method for drug screening, but it has not brought the great increase in the number of new drugs that was expected. Computer- aided compounds search, known as Virtual Screening, has shown the benefits to this field as a complement or even alternative to the robotic drug discovery. There are different methods and approaches to address this problem and most of them are often included in one of the main screening strategies. Machine learning, however, has established itself as a virtual screening methodology in its own right and it may grow in popularity with the new trends on artificial intelligence. Objective: This paper will attempt to provide a comprehensive and structured review that collects the most important proposals made so far in this area of research. Particular attention is given to some recent developments carried out in the machine learning field: the deep learning approach, which is pointed out as a future key player in the virtual screening landscape.

The Future of Human Workers

2018 ◽  
Author(s):  
Mahesh K. Joshi ◽  
J.R. Klein
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Mental Capacity ◽  
Machine Intelligence ◽  
The Internet ◽  
Traditional Model ◽  
Global Workforce ◽  
Repetitive Tasks ◽  
The Internet Of Things

New technologies like artificial intelligence, robotics, machine intelligence, and the Internet of Things are seeing repetitive tasks move away from humans to machines. Humans cannot become machines, but machines can become more human-like. The traditional model of educating workers for the workforce is fast becoming irrelevant. There is a massive need for the retooling of human workers. Humans need to be trained to remain focused in a society which is constantly getting bombarded with information. The two basic elements of physical and mental capacity are slowly being taken over by machines and artificial intelligence. This changes the fundamental role of the global workforce.

Artificial Intelligence and Inequality in the Middle East

2020 ◽  
pp. 624-649 ◽  
Author(s):  
Nagla Rizk
Keyword(s):  
Artificial Intelligence ◽  
Human Resources ◽  
Young Population ◽  
Mena Region ◽  
Poor Countries ◽  
Current State ◽  
Resource Poor ◽  
Youth Entrepreneurship ◽  
The Arab Spring ◽  
The Impact

This chapter looks at the challenges, opportunities, and tensions facing the equitable development of artificial intelligence (AI) in the MENA region in the aftermath of the Arab Spring. While diverse in their natural and human resource endowments, countries of the region share a commonality in the predominance of a youthful population amid complex political and economic contexts. Rampant unemployment—especially among a growing young population—together with informality, gender, and digital inequalities, will likely shape the impact of AI technologies, especially in the region’s labor-abundant resource-poor countries. The chapter then analyzes issues related to data, legislative environment, infrastructure, and human resources as key inputs to AI technologies which in their current state may exacerbate existing inequalities. Ultimately, the promise for AI technologies for inclusion and helping mitigate inequalities lies in harnessing grounds-up youth entrepreneurship and innovation initiatives driven by data and AI, with a few hopeful signs coming from national policies.

scholarly journals Lessons from the COVID-19 Pandemic on the Use of Artificial Intelligence in Digital Radiology: The Submission of a Survey to Investigate the Opinion of Insiders

Healthcare ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 331
Author(s):  
Daniele Giansanti ◽  
Ivano Rossi ◽  
Lisa Monoscalco
Keyword(s):  
Artificial Intelligence ◽  
General Purpose ◽  
Point Of View ◽  
General Point ◽  
Thoracic Radiography ◽  
Digital Radiology ◽  
Electronic Survey ◽  
Radiology Technicians ◽  
Medical Radiology ◽  
Great Development

The development of artificial intelligence (AI) during the COVID-19 pandemic is there for all to see, and has undoubtedly mainly concerned the activities of digital radiology. Nevertheless, the strong perception in the research and clinical application environment is that AI in radiology is like a hammer in search of a nail. Notable developments and opportunities do not seem to be combined, now, in the time of the COVID-19 pandemic, with a stable, effective, and concrete use in clinical routine; the use of AI often seems limited to use in research applications. This study considers the future perceived integration of AI with digital radiology after the COVID-19 pandemic and proposes a methodology that, by means of a wide interaction of the involved actors, allows a positioning exercise for acceptance evaluation using a general purpose electronic survey. The methodology was tested on a first category of professionals, the medical radiology technicians (MRT), and allowed to (i) collect their impressions on the issue in a structured way, and (ii) collect their suggestions and their comments in order to create a specific tool for this professional figure to be used in scientific societies. This study is useful for the stakeholders in the field, and yielded several noteworthy observations, among them (iii) the perception of great development in thoracic radiography and CT, but a loss of opportunity in integration with non-radiological technologies; (iv) the belief that it is appropriate to invest in training and infrastructure dedicated to AI; and (v) the widespread idea that AI can become a strong complementary tool to human activity. From a general point of view, the study is a clear invitation to face the last yard of AI in digital radiology, a last yard that depends a lot on the opinion and the ability to accept these technologies by the operators of digital radiology.

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