The field of Engineering is that which needs a high level of analytical thinking, intuitive knowledge, and technical know-how. The area of communication engineering deals with different components including, wireless mobile services, radio, broadband, web and satellites. There is a rapid decline in the quality of students produced by engineering faculties as a result of sufficient and quality methods and frameworks of student assessment. The production of high-potential engineers is limited by the utilization of old and traditional education methodology and frameworks. The student presentation estimation system in engineering institution is a motionless manual. Usually, the assessment of student’s performance using the traditional system is limited to the use of students’ performance scores, while failing to evaluate their performance based on activities or practical applications. In addition, such systems do not take cognizance of individual knowledge of students that connects to different activities within the learning environment. Recently, engineering institutions have started paying attention to evaluation solutions that are based on wireless networks and Internet of Things (IoT). Therefore, in this study, an automated system has been proposed for the assessment of engineering students. The proposed system is designed based on IoT and wireless communication networks with the aim of improving the process of virtual education. The data used in this study has been collected through the use of different IoT sensors within the premises of the college, and pre-processed using normalization. After the data was pre-processed, it was stored in cloud. In order to enable the classification of student’s activity, an Adaptive Layered Bayesian Belief Network (AL-BBN) classifier is proposed in this work. The student’s scores have been calculated using fuzzy logic, while Multi-Gradient Boosting Decision Tree (MGBDT) was proposed for decision making. The use of python simulation tool is employed in the implementation of the proposed system, and the evaluation of the performance benchmarks was done as well. Based on the findings of the study, the proposed conceptual model outperformed the existing ones in terms of improving the process of online learning.

/pdf/enhancement-of-online-education-in-engineering-college-based-24br6yvy.pdf

Enhancement of Online Education in Engineering College Based on Mobile Wireless Communication Networks and IOT

Digital transformation and automation in the shipping industry is resulting disruptive changes to ship design, operations, and manning that aim to enhance safety, efficiency, and the environmental sustainability of maritime logistics. While there is growing research interest in these areas, examining the role of human element in the new smart shipping context is largely neglected. Through a systematic literature review, this paper aims to explore the multi-dimensional impact of autonomous shipping technology resulting from the application of Industry 4.0 and future industrial revolutions on seafarers. The impacts include the changing role of seafarers on-board and the strategies required to engage seafarers in their transition from traditional shipping to autonomous and smart shipping. The paper concludes that Industry 4.0 is being challenged for its shortfall in recognition of the importance of human role and its intelligence in the expected current industrial revolution. As a result, there is a demand to look further and beyond Industry 4.0 by introducing the next generation of industrial revolution, namely Industry 5.0. This paper suggests that the impact of this revolution in the maritime industry can be defined by concepts such as Maritime 5.0, Shipping 5.0, Seafarer 5.0, Maritime Education and Training 5.0 (MET 5.0). 

Industrial revolutions and transition of the maritime industry: The case of Seafarer’s role in autonomous shipping

Biomarkers are required to track disease progression and measure the effectiveness of interventions for people with spinocerebellar ataxia type-6 (SCA6). Gait is a potential biomarker that is sensitive to SCA6 which can be measured using wearable technology, reducing the need for expensive specialist facilities. However, algorithms used to calculate gait using data from wearables have not been validated in SCA6. This study sought to examine the validity of a single wearable for deriving 14 spatio-temporal gait characteristics in SCA6 and control cohorts. Participants performed eight intermittent walks along a 7 m instrumented walkway at their preferred walking pace while also wearing a single accelerometer-based wearable on L5. Gait algorithms previously validated in neurological populations and controls were used to derive gait characteristics. We assessed the bias, agreement and sensitivity of gait characteristics derived using the instrumented walkway and the wearable. Mean gait characteristics showed good to excellent agreement for both groups, although gait variability and asymmetry showed poor agreement between the two systems. Agreement improved considerably in the SCA6 group when people who used walking sticks were excluded from the analysis, suggesting poorer agreement in people with more severe gait impairment. Despite poor agreement for some characteristics, gait measured using the wearable was generally more sensitive to group differences than the instrumented walkway. Our findings indicate mean gait characteristics can be accurately measured using an accelerometer-based wearable in people SCA6 with mild-to-moderately severe gait impairment yet further development of algorithms are required for people with more severe symptoms.

/pdf/validity-of-a-wearable-accelerometer-to-quantify-gait-in-2bm3t8d18z.pdf

Validity of a wearable accelerometer to quantify gait in spinocerebellar ataxia type 6

Recently, machine learning (ML) has evolved and finds its application in higher education (HE) for various data analysis. Studies have shown that such an emerging field in educational technology provides meaningful insights into several dimensions of educational quality. An in-depth analysis of the application of ML could have a positive impact on the HE sector. However, there is a scarcity of a systematic review of HE literature to gain from the overarching trends and patterns discovered using ML. This paper conducts a systematic review and meta-analyses of research studies that have reported on the application of ML in HE. The differentiating factors of this study are primarily vested in the meta-analyses including a specific focus on student academic performance, at-risk, and attrition in HE. Our detailed investigation adopts an evidence-based framework called PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) for reporting the findings of our systematic review and meta-analyses of literature on the use of ML models, algorithms, evaluation metrics, and other criteria, including demographics for assessing student academic performance, at-risk and attrition in HE. After undergoing the PRISMA steps such as selection criteria and filtering, we arrive at a small-scale dataset of 89 relevant studies published from 2010 to 2020 for an in-depth analysis. The results show the outcomes of the quantitative analysis of the application of ML types, models, evaluation metrics, and other related demographics and provide quality insights of publication patterns and future trends towards predicting and monitoring student academic progress in HE.

Application of machine learning in higher education to assess student academic performance, at-risk, and attrition: A meta-analysis of literature

Broadband and high-efficiency of garnet-typed ceramic dielectric resonator antenna for 5G/6G communication application

Artificial Intelligence (AI) will play a key role in Higher Education. Our contribution leads the road to innovation within IoT for Education 4.0, using a system comprising smartwatch data, health data, learning analytics and Artificial Intelligence. By using embedded sensors from wearable devices, we can add value to Education 4.0. Smartwatches are IoT devices, equipped with a multitude of embedded sensors collecting distraction-free huge amounts of real-time data during students’ learning. In our paper we highlight advantages of wrist-based wearables like smartwatches for Education 4.0. We develop a User Experience Questionnaire for the measurement of acceptance of advanced electronic technology in Higher Education. We identify as experiment’s results the most important sensors and protocols for Education 4.0.

Education 4.0 – Jump to Innovation with IoT in Higher Education

Over the past decade, there has been significant evolution in the security field, specifically in the authentication and authorization part. The standard authentication protocol nowadays is OAuth 2.0-based authentication. This method relies on a third-party authentication service provider with complete control over the users’ data, which it can filter or modify at will. Blockchain and decentralization have generated much interest in recent years, and the decentralized web is considered the next significant improvement in the world wide web (also known as Web 3.0). Web3 authentication, also known as decentralized authentication, allows for the secure and decentralized authentication of users on the web. The use cases for this technology include online marketplaces, social media platforms, and other online communities that require user authentication. The advantages of Web3 authentication include increased security and privacy for users and the ability for users to have more control over their data. The proposed system implementation uses Ethereum as the blockchain and a modern web stack to enhance user interaction and usability. The solution brings benefits both to the private and the public sector, proving that it has the capability of becoming the preferred authentication mechanism for any decentralized web application.

/pdf/a-secure-and-decentralized-authentication-mechanism-based-on-2vs96ss6.pdf

A Secure and Decentralized Authentication Mechanism Based on Web 3.0 and Ethereum Blockchain Technology

This paper is presenting the latency requirement, one of the main requirements for 5G mobile communications. After presenting the general issues, the main usage scenarios, associated applications and potential latency requirement for these in 5G system are presented. The 5G latency requirement for much faster packet trips will enable network service providers to fully comply with customers needs.

Latency requirement for 5G mobile communications

The Education 4.0 process can be used to foster students' performance, to motivate them by means of adaptive and personalized learning, to automate answering routine questions and to improve the quality of online examinations. It releases teachers from routine tasks, and it enables them to be more involved in the individualization of the educational process and in innovation. We apply artificial intelligence methodology to motivate students to improve their performance, and to identify early in course which students are at-risk of dropping out. In the adaptive Education 4.0 loT framework, the environmental and embedded sensors from wearables examine biosignals with biofeedback, such as pulse (HR) and heart rate variability (HRV), thereby increasing students' self-reflection, and allowing for a more personalized learning experience. The first experiments corroborate meaningful correlations between the data-points reached in the self-assessments, and values of the biosignals.

Education 4.0: An Adaptive Framework with Artificial Intelligence, Raspberry Pi and Wearables - Innovation for Creating Value

This paper gives an overview of the two levels of Bayesian inference: model fitting and model selection and shows how they can be used for the image texture analysis. The applied models are the Gauss‐Markov and Gibbs auto‐binomial Random Fields. In the second part the article introduces a linear model for the image wavelet coefficients able to explain the full description of the spatial, inter‐scale and inter‐band behavior of a multi‐resolution decomposed image. The model parameters, model variance and evidence are used to characterize the image texture.

Model Fitting and Model Evidence for Multiscale Image Texture Analysis

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Dan Alexandru Stoichescu

Author Tools

Chat about Author