Blockchain-based online education content ranking.

Nowadays, internet technology plays a vital role in all the fields of our daily lives ranging from the world economy, professional careers, higher education, and almost all the spheres that are deeply impacted. In the current situation, due to COVID19, the dependence on the Internet for almost everything, including learning, getting daily needs, etc., is heavily dependent on the Internet. Online learning is made possible by the Internet, and today most students, educators, researchers are leveraging online learning platforms to enhance their knowledge at their own pace. Generally, the quality of the E-learning courses is evaluated with the help of the courses' review and rating mechanisms. In the present context, review systems are centralized, storing highly valuable information at one location and are liable to manipulation, hacking, and tampering. In this paper, the Blockchain-based Online Education Content Ranking system is proposed for an online review and ranking system that offers a decentralized trustworthy system, ensuring the integrity of the rating and the independence and integrity of content reviews by Subject Matter Experts (SME).

A Review of Supervised Classification based on Contrast Patterns: Applications, Trends, and Challenges.

Supervised classification based on Contrast Patterns (CP) is a trending topic in the pattern recognition literature, partly because it contains an important family of both understandable and accurate classifiers. In this paper, we survey 105 articles and provide an in-depth review of CP-based supervised classification and its applications. Based on our review, we present a taxonomy of the existing application domains of CP-based supervised classification, and a scientometric study. We also discuss potential future research opportunities.

A Pattern-Based Approach for Detecting Pneumatic Failures on Temporary Immersion Bioreactors.

Temporary Immersion Bioreactors (TIBs) are used for increasing plant quality and plant multiplication rates. These TIBs are actioned by mean of a pneumatic system. A failure in the pneumatic system could produce severe damages into the TIB. Consequently, the whole biological process would be aborted, increasing the production cost. Therefore, an important task is to detect failures on a temporary immersion bioreactor system. In this paper, we propose to approach this task using a contrast pattern based classifier. We show that our proposal, for detecting pneumatic failures in a TIB, outperforms other approaches reported in the literature. In addition, we introduce a feature representation based on the differences among feature values. Additionally, we collected a new pineapple micropropagation database for detecting four new types of pneumatic failures on TIBs. Finally, we provide an analysis of our experimental results together with experts in both biotechnology and pneumatic devices.