SELECTING THE SUITABLE E-COMMERCE MARKETPLACE WITH NEUTROSOPHIC FUZZY AHP AND EDAS METHODS FROM THE SELLER'S PERSPECTIVE IN THE CONTEXT OF COVID-19

E-commerce, which is defined as making commercial transactions in an electronic environment, is becoming widespread with the increase of the use of internet and mobile devices. COVID-19 has greatly changed the consumption habits of individuals, increasing interest in electronic sales channels. Regardless of their size, most companies and retailers are currently looking for ways to engage their customers through electronic channels due to the effect of COVID-19. In this process, the rapidly increasing trend of electronic commerce raises an important question for companies, "In which e-marketplace should we sell?” In this study, five criteria that are important in the choice of the right e-marketplace were determined and eight online alternative e-marketplaces were evaluated. The study was carried out using the neutrosophic fuzzy AHP and EDAS methods, which are multi-criteria decision making techniques, and a framework was established for choosing the right e-commerce marketplace for sellers. © 2022,International Journal of the Analytic Hierarchy Process. All Rights Reserved.

A Systematic Literature Survey of Emotion Detection of Students in E-learning

Affective computing is a part of artificial intelligence, which is becoming more important and widely used in education to process and analyze large amounts of data. Consequently, the education system has shifted to an E-learning format because of the COVID-19 epidemic. Then, e-learning is becoming more common in higher education, primarily through Massive Open Online Courses (MOOCs). This study reviewed many prior studies on bolstering educational institutions using AI methods, including deep learning, machine learning, and affective computing. According to the findings, these methods had a very high percentage of success. These studies also helped academic institutions, as well as teachers, understand the emotional state of students in an e-learning environment. © 2022 IEEE.

Detection of COVID-19 Using Classification of an X-Ray Image Using a Local Binary Pattern and K-Nearest Neighbors

The recently identified coronavirus pneumonia, which was later given the name COVID-19, is a virus that can be fatal and has affected more than 300,000 individuals around the world. Because there is currently no antiviral therapy or vaccine that has been granted approval by the FDA to cure or prevent this sickness, an automatic method for disease identification is required because of the fast global distribution of this exceedingly contagious and lethal virus. A unique machine learning strategy for automatically detecting this ailment was discovered. Machine learning approaches should be applied in essential jobs in infectious illnesses. As a result, our major aim is to use computer vision algorithms to identify COVID-19 without the need for human interaction. This paper suggested using image processing to classify objects and make early detections using X-ray pictures. Features are extracted for this region using a variety of techniques, including (LBP), (HOG), and use K-Nearest Neighbor algorithm (KNN) for classification, with training percentages of 50%, 60%, 70%, 80%, and 90%. Experiments indicated that using the suggested approach to identify X-ray photos of corona patients, it is feasible to diagnose the disease using X-ray images by training the device on the image data set (about 2,400 photos). The results were tested on the average of the samples taken (random 2000 images) each time and the measurement of multiple training ratios (50%, 60%, 70%, 80%, and 90%). The experimental findings revealed remarkable prediction accuracy in all investigated scenarios, ranging from 85% to 99%. © 2022 IEEE.

THE PERSPECTIVES OF THE AIR TRANSPORT MARKET IN TURKEY DURING COVID-19 PANDEMIC

In this study, the situation of the Turkish aviation industry during COVID-19 was examined. Turkish aviation industry entered a rapid growth phase in the 21st century, great developments were achieved in aviation with the investments made, and the share received from the world aviation industry grew day by day. However, this growth has been hit hard by the emerging COVID-19 pandemic. There have been great losses in passenger and freight transport. It is considered that the compensation of these losses will take a long time. In addition, in this study, the steps taken by the aviation authority and aviation companies to prevent the pandemic and to reduce its effects for the COVID-19 pandemic were evaluated.