E-learning is the synthesis of multimedia and social media platforms powered by Internet and mobile technologies. Great popularity of e-learning is encouraging governments and educational institutions to adopt and develop e-learning cultures in societies in general and universities in particular. In traditional e-learning systems, all components (agents and services) are tightly coupled into a single system. In this study, we propose a new architecture for e-learning with two subsystems, namely, e-learning and e-testing. The motivation of the research is to improve the effectiveness of the learning process by extracting relevant features for elastic learning and testing process. We employ a multi-agent system because it contains five-layer architecture, including agents at various levels. We also propose a novel method for updating content through question and answer between e-learners and intelligent agents. To achieve optimization, we design a system that applies various technologies, which guarantee various dynamic features for e-learning systems, such as intelligence, distributed nature, adaptive attitude, interaction, accessibility, and security. Agent assisted e- learning enable the users to collect the quantifiable and sensible material; examine, and distribute customized knowledge from multiple e-learning sources. Intelligent agents, being program helper or assistants, are deployed at different levels of abstraction in this architecture to manage information overload and create environment for learners. Moreover, this proposed system is designed by keeping in view several characteristics specific to e-learning system such as interaction, personalization, adaptation, intelligence, interoperability, accessibility and security. The architecture is designed to support instructional design, to retrieve relevant learning materials, to process and analyses data to enable meaningful e-learning recommendations for instructors and learners by considering all issues that existing e-learning architectures don’t address. Most of the existing e-learning architectures don’t consider all the features in a single system so there is a need for a generic architecture that should support all the features to make the e-learning system more efficient. The outcome of this approach is to provide flexible and lightweight systems for e-learning environments.

/pdf/an-architecture-of-agent-based-multi-layer-interactive-e-1hzz5834f3.pdf

An architecture of agent-based multi-layer interactive e-learning and e-testing platform

Multi-agent system is one of the emerging trends in computer science. It can provide new solutions to very complex and restrictive system. The application of multi-agent systems is spreading in almost every field though e-learning is also not left untouched. E-learning has provided us with the capability of providing quality education to masses without restricting them to specific time or place. We have lots of different existing systems, but most of them are lacking all the features like personalization, intelligence, accessibility and security in one single system. Here in this paper we have proposed a new architecture for Multi agent based system for e-learning environment wherein in addition to these basic feature, the focus is interactivity and ease of use. This architecture takes the personalized status of the student into consideration and accordingly provides interactive and effective teaching and learning process. General Terms

/pdf/a-new-approach-to-multi-agent-based-architecture-for-secure-igw2ihbi26.pdf

A New Approach to Multi Agent Based Architecture for Secure and Effective E-learning

E-learning refers to the way by which the learning content is provided by means of electronic technology. In a traditional E-learning system, there is only one layer and all agents and services are connected together. The architecture of the proposed E-learning system, in this paper, contains four tier layers. It is based on multi agent systems' paradigm. In this research we propose a novel method for updating content through Question-Answer between E-learners. We use sharable content object reference model (SCORM) for reuse and sharing the contents of the E-learning system. To achieve this, we have designed a system that applies various technologies, which guarantee various vital features for E-learning systems. These features include intelligence, distributed nature, adaptive attitude, interaction, accessibility and security. We have used multilayer modeling approach to provide flexible and light weight systems for E-learning environments.

An agent based multilayered architecture for E-learning system

This paper presents recommendation algorithms that personalize course and curriculum content for individual students, within the broader scope of Pervasive Cyberinfrastructure for Personalizing Learning and Instructional Support (PERCEPOLIS). The context considered in making recommendations includes the academic background, interests, and computing environment of the student, as well as past recommendations made to students with similar profiles. Context provision, interpretation, and management are the services that facilitate consideration of this information. Context modeling is through a two-level hierarchy of generic and domain ontologies, respectively; reducing the reasoning search space. Imprecise query support increases the flexibility of the recommendation engine, by allowing interpretation of context provided in terms equivalent, but not necessarily identical to database access terms of the system. The relevance of the recommendations is increased by using both individual and collaborative filtering. Correct operation of the algorithms has been verified through prototyping.

Ontology-Based Recommendation Algorithms for Personalized Education

E-learning can be referred to as “education through electronic media”. It is one of the most emerging concepts in the field of technology. E-learning systems can be either synchronous or asynchronous. Agent based e-learning is helpful in managing the information overload, it can serve as academic expert and manages creation of programming environment for learners. There are many characteristics that an E-learning environment has to support; they are Interaction, Data Security, User Personalization, Adaptability, Intelligence, Interoperability, Accessibility and User Authentication. E-learning must also support a few other features like cost effectiveness, reusability, storage capacity, powerful computing and virtualization which can be provided by Cloud computing. Cloud computing is everywhere these days, pick any blogs, journals, papers. The Cloud computing Architecture is built using three models, Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS), which provides a variety of services. This proposed architecture integrates the features of Agents and Cloud Computing to produce an Agent based Cloud Computing Architecture to enhance e-learning.

A Generic Agent Based Cloud Computing Architecture for E-Learning

E-learning refers to the way by which the learning content is provided by means of electronic technology. E-learning system is classified as either synchronous or asynchronous. It is the effective learning process so that the web-based learning system has become a promising paradigm in education. Agent based E-learning can manage the information overload, serve as academic experts, and create programming environments for the learners. There are several characteristics specific to E-learning system such as Interaction, Personalization, Adaptation, Intelligence, Interoperability, Accessibility and Security. Agent based architecture for E-learning system provides the above mentioned features to support instructional design, to retrieve relevant learning materials, to process and analyze data to enable meaningful E-learning recommendations to instructors and learners. But most of the existing E-learning architectures doesn't consider all the features in a single system. So there is a need for a generic architecture that should support all the features to make the E-learning system more efficient. In this paper, we provide a generic architecture for E-learning system. This architecture considers interactivity, personalization, adaptation, interoperability, collaboration, security to enhance the quality of learning process.

A generic architecture for agent based E-learning system

The coronavirus disease‐2019 (COVID 19) caused by the Severe Acute Respiratory Syndrome – Corona Virus‐ 2 (SARS‐CoV‐2) is an ongoing pandemic as of June 2021. The rate of infection, rapid progression and associated mortality are alarming and called for an emergency in all the countries over the world. This pandemic has necessitated a shared responsibility of every individual. The importance of oral hygiene methods in this regard is one of the most essential steps. The angiotensin‐converting enzyme 2 (ACE2) receptors, (one of the viral target receptors) are seen on the dorsal surface of the tongue, gingiva and taste buds.[1] The asymptomatic COVID19 patients act as carriers and shed virus for 16.8‐19.4 days when infected. In moderate and severe (patients on corticosteroid treatment) COVDI‐19 stages, the viral shedding is for 24.2 and 28.3 days respectively.[2] This viral shedding may be seen in various biological fluids (e.g. saliva, stool, urine, tears, and blood).[3] The oral cavity acts as a major habitat for virus throughout the infection. This mandates an individual to maintain a safe oral hygiene practice to ensure reduction in the viral load thus reducing cross‐contamination or infection. The common queries prevailing regarding the oral hygiene are discussed as simple question and answers below. The overview of the same is illustrated in [Figure 1].

https://doi.org/10.4103/jfmpc.jfmpc_1441_21

Oral hygiene practices in the pandemic- Evidence-based discussion of 8 common issues

Sir, Coronavirus disease 2019 (COVID-19) is an ongoing pandemic (as of September 2022) and is known to be caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The possibility of cross-infection between family members when in-home isolation was highlighted previously which is still underrated.[1] The cross-infection is attributable to “shared sanitation” which may be explained as sharing common washrooms between family members irrespective of the status of infectivity. The shared sanitation facilities could become sources of both airborne and contact exposures to SARS-CoV-2, especially in the absence of adequate hygiene practices.[2] The shared wash basins/brushing areas, and the use of inappropriate measures in the dental environment could also contribute to the indirect transmission of COVID-19 between co-habitants.[3] This leads us to discuss eight common queries that seem to be prevailing regarding oral hygiene along with an illustration.[1] However, this does not guide the practices for home-isolated infected cases (HIIC) and their co-habitants in a sequential manner. We developed the sequential flow that can be followed by these two cases in these specific scenarios. The same was copyrighted by the authors and submitted as an additional flowchart. See Figure 1. This flowchart clearly guides HIIC and their co-habitants/family members towards specific measures that can be implemented to avoid cross-infection, and thus the spread of COVID-19. The flowchart was registered as artistic copyright (Reference number: A-143366/2022) and shall act as a tool for health education.Figure 1: Oral hygiene practices in the COVID-19 pandemic: Systematic approach for home-isolated cases and their co-habitantsThe factors such as household vulnerability, lack of home isolation option, and the difficulty to stay home-isolated (due to wanting to be with family, parental caring responsibilities, mental well-being concerns, and the need for locomotion when ill) still promote cross-infection from HIIC.[4] The spread of the virus in pre-symptomatic and asymptomatic cases is estimated to contribute to 53% of COVID-19 transmission, making home isolation a difficult task. Home isolation is thus a double-sided sword, which is a real need for society when COVID-19 patients surge, but may also put household members at high risk of infection, and overall add up to disease propagation in a cyclic manner.[5] Given the various factors that increase risk after home isolation, we encourage following proper oral and general hygiene practices when shared washrooms or wash basins are determined to exit for specific families. Abbreviations Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest. 

K. Sakthiyavathi

Papers

A generic architecture for agent based E-learning system

Oral hygiene practices in the pandemic- Evidence-based discussion of 8 common issues

Oral hygiene practices in the COVID-19 pandemic: A flowchart showing a systematic approach for home-isolated cases and their co-habitants