A comprehensive decision framework with interval valued type-2 fuzzy AHP for evaluating all critical success factors of e-learning platforms.

The COVID 19 pandemic not only affected our health and social life in many aspects, but it also changed the classical way of training in classrooms and education preferences of society. As a solution various e-learning platforms were developed and preferred by many educational institutions where the individuals had the opportunity to try the advantages of e-learning platforms. Since the COVID-19 pandemic is neither the first nor the last epidemic, e-learning attracts more attention than ever before and the need for e-learning platforms is expected to be more in the near future. Thus it is necessary to define all critical success factors determining the efficiency of e-learning systems. E-learning platforms have advantages as well as disadvantages and comparisons involve uncertainties and qualitative assessments. A systematic approach should be used to determine the platforms' dimensions, features and weights of critical criteria. The motivation of our study is to determine the weights of all critical success criteria and offer a reliable method for evaluating e-learning platforms. In this study, the interval type-2 fuzzy Analytical Hierarchy Process was utilized to compare critical success factors of e-learning platforms. This is the most comprehensive study considering all critical success factors of e-learning platforms as an Multi Criteria decision Making problem, where 11 criteria and 106 sub-criteria were defined, evaluated and prioritized. This study provides an acceptable rationale for evaluations of e-learning platforms and the results of this study can be used in real-world performance evaluations.

Selection of suitable distance education platforms based on human-computer interaction criteria under fuzzy environment.

The rapid spread of the COVID-19 pandemic has affected not only the health industry but also the education sector. E-learning systems have recently become a compulsory part of all education institutions, including schools, colleges, and universities worldwide because of the COVID-19 pandemic crisis. The objectives of the current study were twofold: (1) to conduct an analytical approach for ranking of distance education platforms based on human-computer interaction criteria and (2) to identify the most appropriate distance learning platform for teaching and learning activities by using multi-criteria decision-making approaches. Selection criteria were grouped into human-computer interaction-related criteria, such as ease of use, possibility of causing mental workload, user-friendly interface design, presentation method, and interactivity. In the selection procedure, a spherical fuzzy extension of Analytical Hierarchy Process was utilized to identify the weights of selection criteria and to rank distance education platforms. The results revealed that the most important criterion was the possibility of causing mental workload while the most preferable e-learning system was identified as "A3".

Ranking the health precautions for the 'new normal' after the COVID-19 outbreak in production environments.

Objectives. With the outbreak of coronavirus (COVID-19) about a year ago and its quick spread all around the world, some serious decisions had to be made like halting production temporarily. The world now tries to take back its normal pace thanks to some medical improvements. However, the 'new normal' is unlikely to follow the old habits in which COVID-19 never appeared. In production environments, a number of new precautions should be defined to prevent a spread of COVID-19 disease among employees in the new normal period. The aim of this study is to propose an analytical approach to define these new precautions and prioritize them. Methods. To determine the precautions, open archive publications of the Turkish Health Ministry and the World Health Organization, and the opinions of occupational physicians and academicians were considered. Twenty-five precautions were specified under three main headings. The Pythagorean fuzzy analytical hierarchy process was employed to gain the rank of precautions. Results. The most critical precautions and sub-precautions were determined as organizational precautions and developing an appropriate working model to ensure social distance. Conclusion. Using the determined order of measures, the managers are able to apply them, starting from the most effective ones.

Elevated intracranial pressure and reversible eye-tracking changes detected while viewing a film clip.

OBJECTIVE The precise threshold differentiating normal and elevated intracranial pressure (ICP) is variable among individuals. In the context of several pathophysiological conditions, elevated ICP leads to abnormalities in global cerebral functioning and impacts the function of cranial nerves (CNs), either or both of which may contribute to ocular dysmotility. The purpose of this study was to assess the impact of elevated ICP on eye-tracking performed while patients were watching a short film clip. METHODS Awake patients requiring placement of an ICP monitor for clinical purposes underwent eye tracking while watching a 220-second continuously playing video moving around the perimeter of a viewing monitor. Pupil position was recorded at 500 Hz and metrics associated with each eye individually and both eyes together were calculated. Linear regression with generalized estimating equations was performed to test the association of eye-tracking metrics with changes in ICP. RESULTS Eye tracking was performed at ICP levels ranging from -3 to 30 mm Hg in 23 patients (12 women, 11 men, mean age 46.8 years) on 55 separate occasions. Eye-tracking measures correlating with CN function linearly decreased with increasing ICP (p < 0.001). Measures for CN VI were most prominently affected. The area under the curve (AUC) for eye-tracking metrics to discriminate between ICP < 12 and ≥ 12 mm Hg was 0.798. To discriminate an ICP < 15 from ≥ 15 mm Hg the AUC was 0.833, and to discriminate ICP < 20 from ≥ 20 mm Hg the AUC was 0.889. CONCLUSIONS Increasingly elevated ICP was associated with increasingly abnormal eye tracking detected while patients were watching a short film clip. These results suggest that eye tracking may be used as a noninvasive, automatable means to quantitate the physiological impact of elevated ICP, which has clinical application for assessment of shunt malfunction, pseudotumor cerebri, concussion, and prevention of second-impact syndrome.

Sensitivity and specificity of an eye movement tracking-based biomarker for concussion.

OBJECT: The purpose of the current study is to determine the sensitivity and specificity of an eye tracking method as a classifier for identifying concussion. METHODS: Brain injured and control subjects prospectively underwent both eye tracking and Sport Concussion Assessment Tool 3. The results of eye tracking biomarker based classifier models were then validated against a dataset of individuals not used in building a model. The area under the curve (AUC) of receiver operating characteristics was examined. RESULTS: An optimal classifier based on best subset had an AUC of 0.878, and a cross-validated AUC of 0.852 in CT- subjects and an AUC of 0.831 in a validation dataset. The optimal misclassification rate in an external dataset (n = 254) was 13%. CONCLUSION: If one defines concussion based on history, examination, radiographic and Sport Concussion Assessment Tool 3 criteria, it is possible to generate an eye tracking based biomarker that enables detection of concussion with reasonably high sensitivity and specificity.