Artificial Intelligence Decision and Validation Powered Smart Contract for Open Learning Content Creation

2021 ◽  
pp. 359-362
Author(s):  
Frederick Ako-Nai ◽  
Enrique de la Cal Marin ◽  
Qing Tan
Keyword(s):  
Artificial Intelligence ◽  
Open Learning ◽  
Content Creation ◽  
Learning Content ◽  
Smart Contract

scholarly journals Artificial Intelligence, Smart Contract and Islamic Finance

2018 ◽  
Vol 14 (2) ◽  
pp. 145 ◽  
Author(s):  
Siti Rohaya Mat Rahim ◽  
Zam Zuriyati Mohamad ◽  
Juliana Abu Bakar ◽  
Farhana Hanim Mohsin ◽  
Norhayati Md Isa
Keyword(s):  
Artificial Intelligence ◽  
Computer Code ◽  
Islamic Finance ◽  
Human Intelligence ◽  
Human Beings ◽  
Finance Industry ◽  
Smart Contract ◽  
Huge Impact ◽  
Block Chain

This study examines the two important aspect of latest technology issues in Islamic finance that related to artificial intelligence (AI) and smart contract. AI refers to the ability of machines to understand, think, and learn in a similar way to human beings, indicating the possibility of using computers to simulate human intelligence. Smart contract is a computer code running on top of a block-chain containing a set of rules under which the parties to that smart contract agree to interact with each other. The main objectives of this article are to evaluate the operations of AI and smart contract, to make comparison between the operations of AI and smart contract. This article concludes that AI and smart contract will have a huge impact in future for Islamic Finance industry.

Automatic Organization and Generation of Presentation Slides for E-Learning

2012 ◽  
Vol 10 (3) ◽  
pp. 35-52 ◽  
Author(s):  
K. Sathiyamurthy ◽  
T. V. Geetha
Keyword(s):  
Distance Education ◽  
Language Processing ◽  
Learning System ◽  
Learning Material ◽  
Content Creation ◽  
Learning Content ◽  
E Learning ◽  
Processing Techniques ◽  
The Web ◽  
Extract Information

The effectiveness of an e-learning system for distance education to a large extent depends on the relevancy and presentation of learning content to the learner. The ability to gather documents on a particular topic from the web and adapt the contents of the document to suit the learner is an important task from the content creation perspective of e-learning. For the developer of e-learning material the provision to automatically extract, organize, and present content material would improve its effectiveness. This paper proposes to extract information from documents using language processing techniques and organizing the content into appropriate presentation slides for learning purposes using domain ontology and learning oriented pedagogy ontology.

scholarly journals GENERATION OF TRAINING INITIAL GENERATION CONTENT

2020 ◽  
Vol 33 (108) ◽  
pp. 66-73
Author(s):  
V. Rotkin ◽  
Keyword(s):  
Artificial Intelligence ◽  
Simulation Models ◽  
Content Management ◽  
Development Trends ◽  
Content Creation ◽  
Initial Generation

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.

scholarly journals An Open Learning Environment for the Diagnosis, Assistance and Evaluation of Students Based on Artificial Intelligence

2014 ◽  
Vol 9 (3) ◽  
pp. 36 ◽  
Author(s):  
Maria Samarakou ◽  
Andreas Papadakis ◽  
Emmanouil D Fylladitakis ◽  
Antonios Hatziapostolou ◽  
Grammatiki Tsaganou ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Learning Environment ◽  
Open Learning ◽  
Open Learning Environment

scholarly journals Evaluation of an intelligent open learning system for engineering education

2016 ◽  
pp. 496-513
Keyword(s):  
Artificial Intelligence ◽  
User Interface ◽  
Evaluation System ◽  
Continuous Monitoring ◽  
Engineering Students ◽  
Knowledge Building ◽  
Learning System ◽  
Computer Assisted ◽  
Open Learning ◽  
Personalized Education

In computer-assisted education, the continuous monitoring and assessment of the learner is crucial for the delivery of personalized education to be effective. In this paper, we present a pilot application of the Student Diagnosis, Assistance, Evaluation System based on Artificial Intelligence (StuDiAsE), an open learning system for unattended student diagnosis, assistance and evaluation based on artificial intelligence. The system demonstrated in this paper has been designed with engineering students in mind and is capable of monitoring their comprehension, assessing their prior knowledge, building individual learner profiles, providing personalized assistance and, finally, evaluating a learner's performance both quantitatively and qualitatively by means of artificial intelligence techniques. The architecture and user interface of the system are being exhibited, the results and feedback received from a pilot application of the system within a theoretical engineering course are being demonstrated and the outcomes are being discussed.

Artificial intelligence in periodontics – A dip in the future

2021 ◽  
pp. 1-6
Author(s):  
Shivani Sachdeva ◽  
Amit Mani ◽  
Hiral Vora ◽  
Harish Saluja ◽  
Shubhangi Mani ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Learning Algorithm ◽  
Three Dimensional ◽  
Computer Software ◽  
Learning Content ◽  
The Face ◽  
Cad Cam ◽  
Radiographic Data ◽  
Cam Systems

BACKGROUND: Artificial intelligence is a relatively newer technology in the field of medical world. This science uses the machine – learning algorithm and computer software to aid in the diagnostics in medical and dental fields. It is a huge talking point in the field of technology which is spreading it’s wings in all possible sectors at a great speed. This field covers solutions from coaching solutions to diagnostics in medical field covering under the umbrella of all what can be achieved by machine and deep learning. CONTENT: In dentistry, artificial intelligence is creating a revolution in all sections from collection of data, creating algorithms for orthodontic procedures, diagnostic records in the aspect of radiographic data, three dimensional scans and cone beam computed tomography, CAD CAM systems for restorative and prosthetic purposes. Similarly continuous research is being done in the field of periodontics in terms of measuring bone loss, amount of plaque present and much more. CONCLUSION: The field of artificial technology with its varied applications will change the face of dentistry in the upcoming times. Artificial intelligence with its application of machine learning will change the face of dentistry in future.

For an Intelligent E-Learning

2018 ◽  
pp. 297-309
Author(s):  
Utku Kose
Keyword(s):  
Artificial Intelligence ◽  
Critical Point ◽  
Learning Process ◽  
Educational Process ◽  
Educational Institutions ◽  
Educational Activities ◽  
Related Literature ◽  
Learning Content ◽  
E Learning ◽  
The Stability

During a typical e-learning process, there are many different factors that should be taken into consideration to keep the stability of the process or improve the process to get more effective results. Nowadays, employing Artificial Intelligence-based approaches is one of the most popular ways to improve the process and obtain the desired objectives rapidly. In this sense, there are many different kinds of scientific works in order to improve the related literature. However, ensuring control among the performed Artificial Intelligence-based e-learning process is a critical point because there is sometimes a misunderstanding about employing intelligent e-learning process that running intelligent educational tools or materials does not always mean the related e-learning process will improve greatly. In order to ensure that there should be some managerial procedures focused on some aspects of the process, this chapter aims to introduce a managerial model that can be used for especially Artificial Intelligence-supported e-learning content flow in order to improve the educational process. The suggested model is usable for the educational institutions, which focus on especially Artificial Intelligence-oriented e-learning solutions, research works, and educational activities.

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