GENERATION OF TRAINING INITIAL GENERATION CONTENT

The influence of the automation of content creation on the development trends of e-education based on artificial intelligence is considered. Widely used content generators do not actually create new content but modify the finished content accumulated in the databases. The concept of generating primary content is based on the use of simulation models of the studied objects. The methodology for generating the content initial-generation demonstrates the possibility of incorporating AI-based content management sys- tems into e-education.

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Hybrid Fluid Flow Simulation Combining Full Physics Simulation and Artificial Intelligence

10.2118/204728-ms ◽

2021 ◽

Author(s):

Mokhles Mezghani ◽

Mustafa AlIbrahim ◽

Majdi Baddourah

Keyword(s):

Artificial Intelligence ◽

Reservoir Simulation ◽

History Matching ◽

Hybrid Approach ◽

Flow Simulation ◽

Latin Hypercube Sampling ◽

Simulation Models ◽

Fine Scale ◽

Simulation Results ◽

Optimization Loop

Abstract Reservoir simulation is a key tool for predicting the dynamic behavior of the reservoir and optimizing its development. Fine scale CPU demanding simulation grids are necessary to improve the accuracy of the simulation results. We propose a hybrid modeling approach to minimize the weight of the full physics model by dynamically building and updating an artificial intelligence (AI) based model. The AI model can be used to quickly mimic the full physics (FP) model. The methodology that we propose consists of starting with running the FP model, an associated AI model is systematically updated using the newly performed FP runs. Once the mismatch between the two models is below a predefined cutoff the FP model is switch off and only the AI model is used. The FP model is switched on at the end of the exercise either to confirm the AI model decision and stop the study or to reject this decision (high mismatch between FP and AI model) and upgrade the AI model. The proposed workflow was applied to a synthetic reservoir model, where the objective is to match the average reservoir pressure. For this study, to better account for reservoir heterogeneity, fine scale simulation grid (approximately 50 million cells) is necessary to improve the accuracy of the reservoir simulation results. Reservoir simulation using FP model and 1024 CPUs requires approximately 14 hours. During this history matching exercise, six parameters have been selected to be part of the optimization loop. Therefore, a Latin Hypercube Sampling (LHS) using seven FP runs is used to initiate the hybrid approach and build the first AI model. During history matching, only the AI model is used. At the convergence of the optimization loop, a final FP model run is performed either to confirm the convergence for the FP model or to re iterate the same approach starting from the LHS around the converged solution. The following AI model will be updated using all the FP simulations done in the study. This approach allows the achievement of the history matching with very acceptable quality match, however with much less computational resources and CPU time. CPU intensive, multimillion-cell simulation models are commonly utilized in reservoir development. Completing a reservoir study in acceptable timeframe is a real challenge for such a situation. The development of new concepts/techniques is a real need to successfully complete a reservoir study. The hybrid approach that we are proposing is showing very promising results to handle such a challenge.

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Guidance for Acupuncture Robot with Potentially Utilizing Medical Robotic Technologies

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/8883598 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Tiancheng Xu ◽

Youbing Xia

Keyword(s):

Artificial Intelligence ◽

Clinical Trial ◽

Binocular Vision ◽

Future Development ◽

Force Feedback ◽

Development Trends ◽

Real Acupuncture ◽

The World ◽

Coordination Framework ◽

Robotic Technologies

Acupuncture is gaining increasing attention and recognition all over the world. However, a lot of physical labor is paid by acupuncturists. It is natural to resort to a robot which can improve the accuracy as well as the efficacy of therapy. Several teams have separately developed real acupuncture robots or related technologies and even went to the stage of clinical trial and then achieved success commercially. A completed clinical practical acupuncture robot is not far from reach with the combination of existing mature medical robotic technologies. A hand-eye-brain coordination framework is proposed in this review to integrate the potential utilizing technologies including force feedback, binocular vision, and automatic prescription. We should take acupuncture prescription with artificial intelligence and future development trends into account and make a feasible choice in development of modern acupuncture.

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Implications of Digital Transformation on the Strategy Development Process for Business Leaders

Promoting Inclusive Growth in the Fourth Industrial Revolution - Advances in Business Strategy and Competitive Advantage ◽

10.4018/978-1-7998-4882-0.ch001 ◽

2020 ◽

pp. 1-43

Author(s):

Theunis Gert Pelser ◽

Garth Gaffley

Keyword(s):

Artificial Intelligence ◽

Industrial Revolution ◽

Simulation Models ◽

Digital Economy ◽

Digital Transformation ◽

Strategy Development ◽

Skill Sets ◽

Fourth Industrial Revolution ◽

Use Of Technology ◽

Third Industrial Revolution

What the internet with its connectivity did to facilitate the third industrial revolution, cloud computing and artificial intelligence have done for the fourth industrial revolution. Technology is changing the world at an alarming rate, which includes products and services that require scale to manage the growing demands of an ever-changing and increasing population. Digital transformation is enabled through cloud technology where human comprehension cannot cope with the size and speed of data required to manage a business in the digital economy. Artificial intelligence and machine learning assist in activities to overcome human limitation, using algorithms to develop predictive and simulation models and scale to provide data for decision making. The technologies employed to run and execute these require skill and resource. The challenge for the modern-day CEO is that the use of technology and its demand in the digital economy of the Fourth Industrial Revolution is not fully understood by them due to their digital skill level and managing the generational skill sets in their structure.

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Impact of the Application of Artificial Intelligence Technologies in a Content Management System of a Media

Intelligent Systems in Industrial Applications - Studies in Computational Intelligence ◽

10.1007/978-3-030-67148-8_11 ◽

2021 ◽

pp. 139-152

Author(s):

Ignacio Romero ◽

Jorge Estrada ◽

Angel L. Garrido ◽

Eduardo Mena

Keyword(s):

Artificial Intelligence ◽

Management System ◽

Content Management ◽

Content Management System

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APPLICATION OF NEW INFORMATION TECHNOLOGY ON CONCRETE: AN OVERVIEW / NAUJŲ INFORMACINIŲ TECHNOLOGIJŲ NAUDOJIMAS RUOŠIANT BETONĄ. APŽVALGA

Journal of Civil Engineering and Management ◽

10.3846/13923730.2011.574343 ◽

2011 ◽

Vol 17 (2) ◽

pp. 248-258 ◽

Cited By ~ 16

Author(s):

Bakhta Boukhatem ◽

Said Kenai ◽

Arezki Tagnit-Hamou ◽

Mohamed Ghrici

Keyword(s):

Artificial Intelligence ◽

Information Technology ◽

Civil Engineering ◽

Systems Approach ◽

Simulation Models ◽

Concrete Technology ◽

Concrete Mix Design ◽

Recent Developments ◽

Scientific Challenge ◽

Systems Simulation

The development of information technology provides means for quick access to a wide variety of information and methods of modelling complex systems. Simulation models, databases, decision support systems and artificial intelligence have currently become more accessible. Advances of these techniques continue to impact highly on civil engineering. The aim of this paper is to present recent developments in information technology and their influence on concrete technology. A historical perspective on researches and a review of the application of artificial intelligence techniques on concrete are presented. Development of computer integrated knowledge systems, approach of virtual systems and soft- ware for concrete mix design are also discussed. These systems have greatly affected handling tasks in civil engineering design over the past decade and promise to have revolutionary impacts on the nature of the design tasks in the future. They are considered useful and powerful tools which are able to solve complex problems and represent a scientific challenge in concrete technology. Santrauka Vystantis informacinems technologijoms, atsiranda galimybiuų greitai gauti iųvairiausios informacijos ir metoduų, kaip modeliuoti sudėtingas sistemas. Pastaruoju metu paplito imitaciniai modeliai, duomenuų bazės, sprendimuų paramos sistemos ir dirbtinis intelektas. Šiuų metodikuų pažanga statybuų sektoriui ir toliau daro didžiule˛ iųtaka˛. Šiame darbe siekiama pristatyti informaciniuų technologijuų naujienas ir juų iųtaka˛ betono technologijoms. Apžvelgiami ankstesni tyrimai ir dirbtinio intelekto metoduų taikymas ruošiant betona˛. Be to, aptariamas integruotuų kompiuteriniuų žiniuų sistemuų vystymas, virtualiuų sistemuų naudojimas ir programinė iųranga betono mišiniams kurti. Per pastarajių dešimtmetių šios sistemos padarė nemenka˛ iųtaka˛ tam, kaip atliekamos inžinerinio projektavimo užduotys, ir turėtuų paskatinti projektavimo užduoČiuų perversma ateityje. Jos – naudingi ir galingi iųrankiai, leidžiantys spre˛sti sudėtingas problemas, tai mokslinis iššūkis betono technologijuų srityje.

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Success and Failure Aspects of LMS in E-Learning Systems

International Journal of Interactive Mobile Technologies (iJIM) ◽

10.3991/ijim.v15i11.20805 ◽

2021 ◽

Vol 15 (11) ◽

pp. 133

Author(s):

Abdulsalam Alhazmi ◽

Athar Imtiaz ◽

Fatima Alhammadi ◽

Ezzadeen Kaed

Keyword(s):

User Interfaces ◽

Structure Learning ◽

Content Management ◽

Future Research ◽

Content Creation ◽

Group Management ◽

Single Sign On ◽

E Learning ◽

Learning Management ◽

Engagement Assessment

Learning management systems (LMS) and their associated tools have created value for higher education institutions worldwide by improving content deliverability, accessibility, and retrievability. Nevertheless, many studies have criticised these systems for their teacher-centred approaches, which limit opportunities for social and informal learning. After several decades of institutions using LMS, this research aims to discuss the success and failure aspects of these LMS from various perspectives, including structure, content, and support for emerging technologies. Based on a thematic literature review and analysis, success and failure aspects are organised and verified by LMS experts. Alongside the aspects identified from the literature, these experts also noted several additional aspects of success and failure in LMS. The analysis results overall indicated the success aspects of LMS relate to seven key factors: single sign-on, learning management, content management, integration, security, tracking, and group management. Similarly, the failure aspects could be classified into eight factors: content creation and sharing, communicative features, structure, learning engagement, assessment, user interfaces, social and informal learning, and mobile features. The implications of the research for education institutions, instructors, developers, and system providers, as well as the resulting directions for future research, are thus also discussed to help increasing the chances of developing additional theoretical and practical insights.

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Modern Development Trends of Chatbots Using Artificial Intelligence (AI)

10.1109/itms52826.2021.9615258 ◽

2021 ◽

Author(s):

Julija Skrebeca ◽

Paula Kalniete ◽

Janis Goldbergs ◽

Liene Pitkevica ◽

Darja Tihomirova ◽

...

Keyword(s):

Artificial Intelligence ◽

Development Trends ◽

Modern Development

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Social Media Content: A Management Framework

International Journal of Business and Management ◽

10.5539/ijbm.v13n6p84 ◽

2018 ◽

Vol 13 (6) ◽

pp. 84 ◽

Cited By ~ 2

Author(s):

Maria Giovanna Confetto ◽

Alfonso Siano

Keyword(s):

Social Media ◽

Content Management ◽

Digital Content ◽

Media Content ◽

Management Tools ◽

Management Framework ◽

Content Creation ◽

Social Media Platforms ◽

Marketing Team ◽

Content Marketing

This paper aims to introduce a model for social media content management that is focused on both the strategic and operational levels to guide companies in setting, formulating and spreading social media marketing content and monitoring the achieved results. The framework has been realized considering different cognitive goals related to the organizational unit responsible of the development of the content marketing processes, corporate content identity, decision making elements for digital content creation, the diffusion of content through social media platforms, and the tools and parameters used to measure and evaluate performance. The model presented here is an attempt to fill in the existing gap in the recent literature regarding digital content marketing and social media content management. The framework introduces some consequential steps of a well-defined process that is composed of decisions and activities that must be carefully planned, thus preventing (from an operational level) the recurrent use of specific management tools. By adopting an integrated vision, is it possible to keep the business strategy’s objectives and all the operative tasks conducted by the content marketing team aligned.

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Artificial intelligence methods to control the energy efficiency of electric rolling stock online

E3S Web of Conferences ◽

10.1051/e3sconf/202017505046 ◽

2020 ◽

Vol 175 ◽

pp. 05046

Author(s):

Vasily Cheremisin ◽

Stanislav Istomin ◽

Artem Perestenko

Keyword(s):

Artificial Intelligence ◽

Energy Efficiency ◽

Energy Consumption ◽

Simulation Models ◽

Automated System ◽

Rolling Stock ◽

Artificial Intelligence Methods ◽

Electric Rolling Stock ◽

Motion Parameters ◽

Consumption Control

The international practices in organizing the energy consumption control of electric rolling stock are analyzed. As a result, it was concluded that currently the issue of organizing the energy consumption control of electric rolling stock is mainly solved by using analytical methods. These methods are based on designing the simulation models, which are usually based on the Pontryagin maximum principle. However, considering the development of recording systems for motion parameters of electric rolling stock, as well as other automated systems of Russian Railways, it seems promising to develop and study artificial intelligence methods and algorithms for solving real-time monitoring issues of electric rolling stock energy consumption. It was also determined that the most modern motion parameter recorders have a number of significant drawbacks from the data analysis point of view. Such drawbacks include insufficient data and their low reliability, lack of linking the recorded data to trips and locomotive teams, the impossibility of choosing a constant interval for recording measurement results. Moreover, there is also high probability of errors when recording data on the cartridge, lack of GPS/GLONASS satellite navigation system, lack of wireless data transmission, imperfection of software and inconvenience of exporting data from a cartridge file and its incompleteness. In order to test the energy efficiency assessment of electric rolling stock within the limits of arbitrary energy tracking areas, the Corresponding software was developed on the basis of data from the motion parameters recorders. However, developing the new complex automated system is required for the full implementation of the proposed consumption tracking method. Such system should combine the entire set of measured parameters, both for electric rolling stock and for the traction power supply system.

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