LFR Waiter: Arduino Based Android Application Controlled Waiter Robot

One of the most pressing challenges facing restaurants since the COVID-19 outbreak began is personnel. A staffing scarcity across the business has resulted in a slew of issues, including significantly longer wait times and irritated clients. A robot waiter may make a huge impact in a restaurant in this situation. This research led to the formation of a low-cost Arduino-based Android application control Robot that can work as a restaurant waiter. The proposed model can follow a path, avoid obstacles, serve meals to a specific consumer, and return to the kitchen on its own. To precisely follow the line, the PID algorithm is utilized. To detect potential obstructions, a sonar sensor is used. On an LCD, messages and warnings are displayed. An Android app that allows the chief to select a particular table for serving meals. For convenience, the robot's current state is displayed in the application. Our testing results show that the robot performs satisfactorily over 90% of the time. It should be emphasized that the offered model is adaptable to any restaurant. © 2022 IEEE.

Note: Cheating and Morality Problems in the Tertiary Education Level: A COVID-19 Perspective in Bangladesh

COVID-19 pandemic has impacted every sphere of students' life along with forcing the transition to online education which brought a significant change in the learning habits of students. Different options like using file-sharing websites, online solvers etc. for cheating were exploited by the students in the tertiary education level. We explored the driving factors of cheating by the university students (Female = 17, Male = 28). We found that the stress during the pandemic;easy availability of online materials;and competitive nature of students impelled them to cheat. The students asserted that adapting these ways of cheating has affected their various significant skills as students. The conversations show that appropriate measures to motivate students to stop cheating must be taken. Our study contributes to the research community by exploring the different factors of cheating in online exams in Bangladesh. © 2022 ACM.

Evaluating the Performance of ID3 Method to Analyze and Predict Students' Performance in Online Platforms

The primary goal of this work was to establish the influence of the epidemic on education, especially the impact of online platforms on students' overall performance. To improve education quality in this new normal, it is vital to ascertain the elements influencing students' performance. During the Covid-19 epidemic, online-based learning (e-learning) activities increased significantly as every educational institution shifted its operations to digital means. To improve education quality in this circumstance, it is vital to ascertain the elements that influence students' performance. Data mining techniques are becoming more used in educational field research. Educational data mining is a new area that tries to study the unique, ever more extensive data sets generated by educational settings to better understand the students who use them. In this study, Iterative Dichotomiser 3 was implemented to explore precisely 280 students' data to evaluate its performance on an online learning platform. 10-fold cross-validation and the percentage split method were used to assess the classifier. In this analysis, the 10-fold cross-validation method outperformed the percentage split by almost 3 percent, where this validation method achieved almost 77.86 percent accuracy. The effectiveness of the ID3 classifier in predicting students' performance on an online platform will be investigated in this research. © 2022 IEEE.