International Journal of Modern Education and Computer Science (IJMECS)

IJMECS Vol. 12, No. 4, Aug. 2020

Cover page and Table of Contents: PDF (size: 596KB)

Table Of Contents

REGULAR PAPERS

Proposal of a Digital Ecosystem Based on Big Data and Artificial Intelligence to Support Educational and Vocational Guidance

By Essaid EL HAJI Abdellah Azmani

DOI: https://doi.org/10.5815/ijmecs.2020.04.01, Pub. Date: 8 Aug. 2020

The work in this article focuses on the modelling of an intelligent digital ecosystem for educational and career guidance for students and young people seeking their first job or retraining. To do so, the multi-expert system paradigm was used to aggregate the different expertises required for a good guidance, the multi-agent system principle was used to have a modular and easily scalable ecosystem. Indeed, the agents of the system communicate with each other using the FIPA-ACL language, in a collaborative vision, throughout the orientation assistance process to perform tasks such as proposing business sectors, occupations, training, and training paths. The ontologies of the Semantic Web have been used to have a complete semantic description of the shared information and to promote communication between the different software agents of the ecosystem. Big Data principles have also been deployed to manage and exploit structured and unstructured data from different data sources related to the guidance ecosystem.
The ecosystem modeled in this way has several innovative and powerful technological and scientific aspects. Thus, in terms of design and modelling, the proposed ecosystem considers all the actors and factors involved in the guidance process, including labor market trends. In technological/scientific terms, it is based on methods that allow it to be modular and scalable.

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Rural Empowerment through Education: Case Study of a Learning Community Telecentre in Indonesia

By Wichitra Yasya

DOI: https://doi.org/10.5815/ijmecs.2020.04.02, Pub. Date: 8 Aug. 2020

This research aims to investigate the impact of information and communication technologies (ICTs) for development and social change in a rural telecentre in Indonesia. It attempts to contribute to the literature of ICTs for development and social change, in the field of analysis of a community-driven ICTs initiative and the analysis of an Indonesian telecentre, two research areas that had not been extensively explored. A qualitative case study approach was chosen to reveal the how ICTs are used in community empowerment in the case of Qaryah Thayyibah Learning Community, a school with a telecentre that in founded, run and funded by the community of Kalibening Village in Central Java, Indonesia. Through the application of the stakeholder theory, significant findings related to impact of ICTs for social change of the Qaryah Thayyibah Learning Community were revealed. These findings include patterns of access and participation of stakeholders in relation to ICTs. While ICTs had impacted the students of Qaryah Thayyibah, its impact had not yet been significantly experienced for the wider community outside of the school. Another important finding that emerged from the stakeholder analysis is the influence and value of the local champion in the establishment and sustainability of the ICTs initiative. In conclusion, the findings suggest that education such as that practiced in the Qaryah Thayyibah Learning Community can contribute in achieving rural empowerment, although the process may be long and complex. As this is an exploratory study investigating unquantifiable intangible impacts, further research can focus more on these intangible impacts through different lenses such as culture, power dynamics and social relations.

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Mean-Field Theory in Hopfield Neural Network for Doing 2 Satisfiability Logic Programming

By Saratha Sathasivam Shehab Abdulhabib Alzaeemi Muraly Velavan

DOI: https://doi.org/10.5815/ijmecs.2020.04.03, Pub. Date: 8 Aug. 2020

The artificial neural network system's dynamical behaviors are greatly dependent on the construction of the network. Artificial Neural Network's outputs suffered from a shortage of interpretability and variation lead to severely limited the practical usability of artificial neural networks for doing the logical program. The goal for implementing a logical program in Hopfield neural network rotates rounding minimizing the energy function of the network to reaching the best global solution which ordinarily fetches local minimum solution also. Nevertheless, this problem can be overcome by utilizing the hyperbolic tangent activation function and the Boltzmann Machine in the Hopfield neural network. The foremost purpose of this article is to explore the solution quality obtained from the Hopfield neural network to solve 2 Satisfiability logic (2SAT) by using the Mean-Field Theory algorithm. We want for replacing the real unstable prompt local field for the separate neurons into the network by its average local field utility. By using the solution to the deterministic Mean-Field Theory (MFT) equation, the system will derive the training algorithms in which time-consuming stochastic measures of collections are rearranged. By evaluating the outputs of global minima ratio (zM), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) with computer processing unit (CPU) time as benchmarks, we find that the MFT theory successfully captures the best global solutions by relaxation effects energy function.

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Controlling of Mean Arterial Pressure by Modified PI-ID Controller Based on Two Optimization Algorithms

By Ekhlaskaram RawaaHaamed

DOI: https://doi.org/10.5815/ijmecs.2020.04.04, Pub. Date: 8 Aug. 2020

High blood pressure is one of the diseases that most people suffer from, and it becomes a serious disease when it is not controlled precisely, especially during the surgical procedure. There must be anesthesiologists during the operation to monitor the pressure during the operation. It is not good and expensive, for patient safety and injection of the patient with the required dose, and it accurately requires an intelligent control to control the patient's pressure This paper presents nonlinear control system, to regulate the Mean Arterial Pressure (MAP) system. This controller is designed based on slate model that represent the mathematical equation that clarifies relationship between blood pressure and vasoactive drug injection. In this work Squirrel Search Algorithm (SSA) and Bacterial Foraging Optimization (BFO) are considered to optimize the controller parameters. Also nonlinear gain is used in PI-Id controller rather than fixed gain to make the controller much more sensitive to small value of error. Two algorithms applied to the controller to optimize its parameters to compare their results and determine which gives better results. The comparison results show best improvement when using the suggested controller based on SSA Algorithm. the results have no undershot with less (800s) settling time and low error.

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Service-Oriented Computing for Effective Management of Academic Records: In Case of Debre Markos University Burie Campus

By Robel Mamo

DOI: https://doi.org/10.5815/ijmecs.2020.04.05, Pub. Date: 8 Aug. 2020

It is difficult for higher education institutes to manage the growing volumes of educational data accurately and efficiently using conventional ways. Modern technology is required to deal with this difficulty and ICT is an emerging technology that can solve this problem. In this study, Service-Oriented Computing (SOC) is used to develop a Service-Oriented Registrar System (SORS) for Debre Markos University Burie campus registrar office. Web services are used to develop highly cohesive and loosely coupled subsystems that support location transparency and manage the academic records of students accurately and efficiently. Moreover, the developed system is secured, easily maintainable, expandable and open for either inter or intra-application integration on the campus.

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