E-Learning Readiness Assessment Using Machine Learning Methods

Assessing e-learning readiness is crucial for educational institutions to identify areas in their e-learning systems needing improvement and to develop strategies to enhance students' readiness. This paper presents an effective approach for assessing e-learning readiness by combining the ADKAR model and machine learning-based feature importance identification methods. The motivation behind using machine learning approaches lies in their ability to capture nonlinearity in data and flexibility as data-driven models. This study surveyed faculty members and students in the Economics faculty at Tlemcen University, Algeria, to gather data based on the ADKAR model's five dimensions: awareness, desire, knowledge, ability, and reinforcement. Correlation analysis revealed a significant relationship between all dimensions. Specifically, the pairwise correlation coefficients between readiness and awareness, desire, knowledge, ability, and reinforcement are 0.5233, 0.5983, 0.6374, 0.6645, and 0.3693, respectively. Two machine learning algorithms, random forest (RF) and decision tree (DT), were used to identify the most important ADKAR factors influencing e-learning readiness. In the results, ability and knowledge were consistently identified as the most significant factors, with scores of ability (0.565, 0.514) and knowledge (0.170, 0.251) using RF and DT algorithms, respectively. Additionally, SHapley Additive exPlanations (SHAP) values were used to explore further the impact of each variable on the final prediction, highlighting ability as the most influential factor. These findings suggest that universities should focus on enhancing students' abilities and providing them with the necessary knowledge to increase their readiness for e-learning. This study provides valuable insights into the factors influencing university students' e-learning readiness.

Impact of ICER Assessments on Payer Decision Making in the United States

Objectives: To evaluate how payers utilize Institute for Clinical and Economic Review (ICER) assessments to inform coverage or formulary decisions. Method(s): Double-blinded, web-based survey was fielded through Xcenda's research panel, the Managed Care Network, from June to July 2022. Result(s): A total of 51 payers from health plans (n=27), integrated delivery networks (n=12), and pharmacy benefit managers (n=12) participated in the survey. When assessing the usefulness of ICER's value assessment framework (VAF) to inform formulary decisions within their organizations, 57% of payers indicated it was extremely/very useful, 33% indicated somewhat useful, and 10% indicated not at all/not very useful. Most respondents (73%) agreed that ICER assessments are aligned with their organization's internal assessment. Utilization of ICER's VAF was most prevalent in high-cost drug or disease states (78%), rare/orphan disease states (71%), and oncology/hematology disease states (67%). Payers reported less use in primary care disease states (29%), COVID-19 (8%), and digital therapeutics (4%). In the last 24 months, 20% of payers reported ICER's recommendations often influenced coverage decisions, 59% indicated occasional influence, and 22% indicated no influence. In the last 24 months, payers indicated the top 5 ICER assessments that influenced their coverage decisions included high cholesterol (38%), Alzheimer's disease (36%), atopic dermatitis (33%), multiple myeloma (31%), and chemotherapy-induced neutropenia (28%). ICER assessments that were less impactful included beta thalassemia (3%), digital health technologies (3%), and supervised injection facilities (3%). Payers reported using ICER assessments to inform both expanded and restricted coverage decisions. Conclusion(s): Payers find ICER's VAF useful to inform their organization's formulary decisions. ICER's assessments often align with payers' internal assessments and are most frequently utilized for high-cost drugs or disease states. Payers indicate ICER assessments have affected both expansion and restriction in their coverage policies.Copyright © 2023

Passenger Perceptions, Information Preferences, and Usability of Crowding Visualizations on Public Displays in Transit Stations and Vehicles

Large crowds in public transit stations and vehicles introduce obstacles for wayfinding, hygiene, and physical distancing. Public displays that currently provide on-site transit information could also provide critical crowdedness information. Therefore, we examined people's crowd perceptions and information preferences before and during the pandemic, and designs for visualizing crowdedness to passengers. We first report survey results with public transit users (n = 303), including the usability results of three crowdedness visualization concepts. Then, we present two animated crowd simulations on public displays that we evaluated in a field study (n = 44). We found that passengers react very positively to crowding information, especially before boarding a vehicle. Visualizing the exact physical spaces occupied on transit vehicles was most useful for avoiding crowded areas. However, visualizing the overall fullness of vehicles was the easiest to understand. We discuss design implications for communicating crowding information to support decision-making and promote a sense of safety. © 2023 ACM.

Pandemic vulnerability knowledge visualisation for strategic decision-making: A COVID-19 index for government response in Australia

Purpose: First, the key vulnerability factors from the literature are identified. Second, using the vulnerability factors as indicators, a composite index is developed. Last, from the index values, a set of vulnerability knowledge maps, showing the vulnerability hotspots, are prepared. Design/methodology/approach: This study aims to develop a pandemic vulnerability knowledge visualisation index to support the strategic decision-making efforts of authorities. Findings: Ten indicators are identified as vulnerability factors that could significantly impact the virus spread risks. Verifying the identified hotspots against the recorded infected cases and deaths has evidenced the usefulness of the index. Determining and visualising the high-vulnerability locations and communities could help in informed strategic decision-making and responses of the authorities to the pandemic. Originality/value: The study demonstrates that the developed pandemic vulnerability knowledge visualisation index is particularly appropriate in the context of Australia. Nonetheless, by replicating the methodologic steps of the study, customised versions can be developed for other country contexts. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Concept Drift Adaptation Methods under the Deep Learning Framework: A Literature Review

With the advent of the fourth industrial revolution, data-driven decision making has also become an integral part of decision making. At the same time, deep learning is one of the core technologies of the fourth industrial revolution that have become vital in decision making. However, in the era of epidemics and big data, the volume of data has increased dramatically while the sources have become progressively more complex, making data distribution highly susceptible to change. These situations can easily lead to concept drift, which directly affects the effectiveness of prediction models. How to cope with such complex situations and make timely and accurate decisions from multiple perspectives is a challenging research issue. To address this challenge, we summarize concept drift adaptation methods under the deep learning framework, which is beneficial to help decision makers make better decisions and analyze the causes of concept drift. First, we provide an overall introduction to concept drift, including the definition, causes, types, and process of concept drift adaptation methods under the deep learning framework. Second, we summarize concept drift adaptation methods in terms of discriminative learning, generative learning, hybrid learning, and others. For each aspect, we elaborate on the update modes, detection modes, and adaptation drift types of concept drift adaptation methods. In addition, we briefly describe the characteristics and application fields of deep learning algorithms using concept drift adaptation methods. Finally, we summarize common datasets and evaluation metrics and present future directions.

Caesarean section in critically unwell peri-partum patients with COVID-19: A tertiary centre's experience

Introduction: The COVID-19 pandemic has required clinical teams to function with an unprecedented amount of uncertainty, balancing complex risks and benefits in a highly fluid environment. This is especially the case when considering the delivery of a pregnant woman critically unwell with COVID-19. This is one maternal critical care team's reflections on establishing best practice and a shared mental model when undertaking a Caesarean section in critically unwell patients with COVID-19. Objective(s): We describe our experience of balancing the risks and streamlining the process of this high-risk intervention. Method(s): We used our standard clinical governance forums across four specialties (Obstetrics, Intensive care, Anaesthetics and Neonatology) to identify key challenges and learning points. We developed a working group to combine our learning and develop a shared mental model across the involved teams. Result(s): 1. The decision to deliver must be multidisciplinary involving Obstetrics, Intensive care, Anaesthetics, Neonatology and the patient according to their capacity to participate. The existing structure of twice daily ITU ward rounds could be leveraged as a 'pause' moment to consider the need for imminent delivery and review the risk-benefit balance of continued enhanced pharmacological thromboprophylaxis. 2. We identified a range of scenarios that our teams might be exposed to: 3. Perimortem Caesarean section 4. Critically unwell - unsafe to move to theatre 5. Critically unwell - safe to move to theatre 6. Recreating an obstetric theatre in the ICU Advantages Avoids moving a critically unstable patient, although our experience is increasing moving patients for ECMO. Some forms of maximal non-invasive therapy such as High Flow Nasal Oxygen may require interruption to move to theatre with resultant risk of harm or be difficult to continue in transport mode through a bulky ICU ventilator e.g. CPAP Disadvantages Significant logistics and coordination burden: multiple items of specialist equipment needing to be brought to the ICU. Human factors burden: performing a caesarean section in an unfamiliar environment is a significant increase in cognitive load for participating teams. Environmental factors: ICU side rooms may offer limited space vs the need to control the space if performed on an open unit. Delivering a Neonate into a COVID bubble. Conclusion(s): Developing a shared mental model across the key teams involved in delivering an emergency caesarean section in this cohort of critically unwell patients has enabled our group to own a common understanding of the key decisions and risks involved. We recommend a patient centred MDT decision making model, with a structure for regular reassessment by senior members of the teams involved. In most circumstances the human factors and logistical burden of recreating an operating theatre in the ICU outweighs the risk of transport to theatre. Pre-defined checklists and action cards mitigate the cognitive and logistical burden when multiple teams do perform an operative delivery in ICU. Action cards highlight key aspects of routine obstetric care to be replicated in the ICU environment.

Vaccine Hesitancy Among African Americans

The limited participation of African Americans in clinical trials has been a topic of discussion among medical and scientific researchers for some time. With the testing of coronavirus vaccines, this discussion has continued, particularly given the disproportionate impact of the virus on members of the African American community. With the public health goal of achieving widespread or "herd" immunity, the concept of "vaccine hesitancy" has also been addressed with regard to the population in general, and in relation to the African American community, among others. Vaccine hesitancy has been reported among groups from healthcare workers to rural residents to the poor. As is the case with all segments of society, African Americans are not monolithic. However, there are aspects of the issue of vaccine hesitancy which are unique and specific to the African American community in the U.S. In particular, the nature of the information about the coronavirus itself and about the vaccine, and importantly, the increasing availability of the information about the Tuskegee experiment, Henrietta Lacks, and other cases, along with the prevalence of misinformation and disinformation on aspects of science, such as that involving vaccines, are relevant to understanding the nature of vaccine hesitancy among African Americans.

Youth recommendations for early intervention responses by governments for future pandemics

Aims: During the pandemic, youth were particularly vulnerable to experiencing financial hardship, education and employment disruption, and mental health impacts. Ensuring governments and services are prepared to support youth during future outbreaks or novel pandemics should be a key priority. This work aimed to explore youth experiences during COVID-19 and gather youth opinions on government responses to inform planning, policy, and decision-making for future pandemics. Method(s): Youth (ages 15-25) from Ireland and two provinces in Canada (British Columbia and Ontario) were interviewed at three time points during the COVID-19 pandemic. A thematic analysis was conducted using an inductive approach. This research was primarily youth-led and developed. Result(s): Across all three time points, youth experienced mental health and service uptake challenges, with mixed views on pandemic response. Opportunities for personal and societal growth were identified, with desire for incorporating youth voices into governmental decision making processes. Youth offered recommendations for effectively communicating accurate information, prevention of misinformation, and expressed needs regarding service accessibility throughout the pandemic and beyond. Conclusion(s): This work provides insights into the opinions of young people on government and information sharing during the progression of the COVID-19 pandemic. Recommendations were developed to ensure youth are consulted and represented in future pandemics.

Farmers' willingness to stabilize the land contract relationship facing the upcoming expiry of land contracts

On the verge of the expiry of land contracts, it is theoretically and practically important to explore the willingness and motivations of farmers to stabilize the land contract relationship, with regards to protecting their land contract rights, addressing potential contradictions during the land contract extension, and maintaining the stability of contracted land. Using China Land Economic Survey Data in 2020, this paper explores the impact of differences in areas per capita of household contracted land on farmers' willingness to stabilize land contract relationship. The findings show that most farmers support the stability of land contract relationship;the smaller areas per capita of contracted land are occupied by households than the average in the village, the weaker of the farmers' willingness to stabilize the land contract relationship. The difference between the areas per capita of contracted land ownership of a household and the average in the village has a greater impact on the willingness to stabilize land contract relationship for middle-and low-income farmers, while the development of land transfer market does not increased the willingness. Affected by the COVID-19 pandemic, the land plays a more important role of employment security, which reduces farmers' willingness to stabilize the land contract relationship. Furthermore, the promotion of socialized agricultural service has also mitigated the willingness of farmers o stabilize the land contract relationship.

Anaesthetic pre-assessment of obese patients in obstetrics: challenges in COVID recovery

Introduction: One in five pregnant women in the UKis obese. Obesity is associated with increased risk of both maternal and foetal adverse outcomes. RCOG guidelines [1] recommend that all women with a booking BMI over 40 kg/m2 should be reviewed antenatally by a senior obstetric anaesthetist to guide risk assessment, medical optimisation and shared decision-making. The 2021 MBRRACE report [2] recommends that all women should be reweighed in the third trimester for accurate VTE risk scoring and prophylactic LMWH dosing. In our institution, reconfiguration of hospital areas as part of the COVID-19 response led to loss of designated clinic space for our obstetric anaesthetic clinic. As a result, our practice since has been to initially offer a telephone consultation followed by a face-to-face review if needed. Finding space for the latter has often been a significant logistical challenge. Our project sought to assess whether our practice continued to meet national standards in the wake of these changes. Method(s): Following audit approval, we retrospectively reviewed all women with a BMI >40 kg/m2 undergoing caesarean section (CS) over a six-month period (1/4/22 to 31/9/22). Result(s): 20 women met inclusion criteria (Category 1-3 CS - 12 women;Category 4 CS - 8 women). 100% of patients had booking height, weight and BMI recorded. 20% (4/20) of patients were reweighed in the 3rd trimester. Only 55% (11/20) of patients had been referred to and reviewed in the antenatal obstetric anaesthetic clinic (Figure). Of the 11 patients referred, 6 were referred later than 30 weeks. Of the 9 patients not referred, 8 had a BMI between 40 and 45 kg/m2. By contrast, 87% (6/7) of patients with BMI over 45 kg/m2 were referred and seen. Discussion(s): Our audit showed that we are not meeting national standards. Possible reasons identified were lack of awareness of the RCOG standards and referral criteria (especially for women with a BMI of 40 to 45 kg/m2) and logistical issues in undertaking face-to-face reviews without designated clinic space. Presentation of our results at the joint anaesthetic, obstetric and midwifery governance meeting has helped identify space in the antenatal clinic for face-to-face reviews, to start from March 2023 and to raise awareness of the national standards to ensure referral of all women with a BMI over 40 kg/m2. A reaudit is planned in 6 months. [Figure presented]Copyright © 2023 Elsevier Ltd

Investigation of high school students' motivation for physical activity participation and eating attitude levels during the COVID-19 period

The aim of this study is to determine the motivation of high school students to participate in physical activity and their eating attitude levels during the COVID-19 period as well as to examine the relationship between the two variables. In addition, it was also determined whether the motivation for participate in physical activity and eating attitudes differ according to gender, weekly exercise, spending time with technology, family communication times, and participation in exercise during and before the pandemic. A total of 576 high school students, including 406 girls and 170 boys, participated in the study. "Motivation Scale for Participation in Physical Activity (MSPPA)", "Eating Attitude Test (EAT-40)" and "Personal Information Form (KBF)" were used as data collection tools. Data were evaluated using correlation, multiple linear regression, MANOVA and t-test analysis techniques. It was concluded that the motivation of the students to participate in physical activity was moderate, and they did not have eating disorders. It was observed that physical activity motivation did not predict eating attitude, but there were positive and low relationships between sub-factors in relational dimension. According to gender, it was determined that the eating attitudes of female students were more positive than male students. It has been found that the motivation to participate in physical activity is higher for those who exercise before and during the pandemic than those who do not. Consequently, it can be said that during the COVID-19 process, high school students' motivation to participate in physical activity is at a moderate level, and their eating attitudes are generally not at the level of behavioral disorders.

Research on the Optimal Energy Saving and Emission Reduction Path for Promoting High-Quality Industrial Development in Hubei Province

In December 2019, a novel coronavirus broke out in Wuhan City, Hubei Province, and, as the center of the coronavirus disease 2019 (COVID-19) epidemic, the economy and production throughout Hubei Province suffered huge temporary impacts. Based on the input–output and industrial pollution emissions data of 33 industrial industries in Hubei from 2010 to 2019, this article uses the non-parametric frontier analysis method to calculate the potential production losses and compliance costs caused by environmental regulations in Hubei's industrial sector by year and industry. Research has found that the environmental technology efficiency of the industrial sector in Hubei is showing a trend of increasing year-on-year, but the overall efficiency level is still not high, and there is great room for improvement. The calculation results with and without environmental regulatory constraints indicate that, generally, production losses and compliance costs may be encountered in the industrial sector in Hubei, and there are significant differences by industry. The potential production losses and compliance costs in pollution-intensive industries are higher than those in clean production industries. On this basis, we propose relevant policy recommendations to improve the technological efficiency of Hubei's industrial environment, in order to promote the high-quality development of Hubei's industry in the post-epidemic era.

Analysis of the assessment profile of KrasSMU students providing medical aid to COVID-19 patients.

The aim of the research. To conduct a cluster analysis of the assessment profile of students who participated in work of medical organisations providing care to COVID-19 patients to develop recommendations for its correction. Material and methods. The study was carried out at the premises of Prof. V.F. Voino-Yasenetsky Krasnoyarsk State Medical University (KrasSMU). The study group was constituted by 66 students in 3-6 years of study of the Medical and the Paediatric faculties of the University who took part in activities of medical organisations providing healthcare to patients with COVID-19. The items were presented in the form of binary questions and ranking scales. The analysis of qualitative attributes was carried out in the form of relative values with calculation of the standard error of the proportion. For ranking and nonparametric quantitative characteristics, the mode, median, centiles (Me [P25;P75]) and other nonparametric criteria for comparative statistics and communication statistics were used. For segmentation of respondents according to some criteria, depending on the answers, the method "two-step cluster analysis" and the method of "decision tree" were used. Results. The results of the study indicate a high motivational component related to practical medical activity of medical students during the difficult epidemiological situation since 94.1% of the respondents declared the readiness to support practical healthcare. Almost half of the surveyed 47.0% of students included in cluster 2, in contrast to students of clusters 1 and 3, are characterised by a high opinion on the degree of their contribution to the struggle against the COVID-19 epidemic and a high level of knowledge and skills, rating themselves at about 9.0 points out of 10 possible. In addition, the results of the study indicate an association between the level of students' self-esteem in regard to their contribution to the fight against COVID-19 with the level of the students' self-esteem of knowledge and skills and the duration of work in a medical organisation. Conclusion. The analysis performed has made it possible to formulate guidelines for support of medical students' professional attitudes within the framework of practice-oriented education, including distance learning.Copyright © 2021, Krasnoyarsk State Medical University. All rights reserved.

The Relationship between Air Travel Service Quality and Factors of Theory of Planned Behavior: Evidence from Low-Cost Airlines in Thailand

Despite an increased emphasis on improvement in airline service quality concerning consumer behavior, such as passenger repurchasing as a result of their behavioral intention over the last several decades, there is still much less concern with the nature of airline service quality than should exist in the so-called "logistics service quality” and less concern with examining the specific behavioral intention preceding repurchasing behavior together with the theory of planned behavior. As such, this study aims to explore these issues, along with the psychological factors of the theory of planned behavior, that can lead to repurchasing behavior via word-of-mouth intention (WOMI). With an online survey of 383 respondents experienced with flying, the results reveal that the logistics service quality and each determinant in the theory positively influence a passenger's repurchasing behavior through WOMI. Accordingly, service marketers can implement service design and apply integrated marketing communication by learning from repurchasing behavior that was formed by the given factors to retain their existing customers. Moreover, this study is the first to empirically and explicitly validate dimensions of airline services through the lens of logistics that are deemed fit with the nature of the airlines. It advances the understanding of theory approaching and connects what has hampered its advancement in a body of knowledge, simultaneously in a context of airline context where it should not be relegated to transportation and consumer and service orientation.

Impact of the COVID-19 Pandemic on Cervical Cancer Screening Rates in Colombia: An Interrupted Time Series Analysis, Stratified By Region

Objectives: The objective of this study is to measure the national impact of COVID-19 on cervical cancer screening rates in Colombia in five of its geographic regions to inform future health policy decision making. Method(s): This study utilized a quasi-experimental interrupted time-series design to examine changes in trends for the number of cervical cancer screenings performed in five geographic regions of Colombia. Result(s): In the rural region of Vichada, we found the lowest incidence of cervical cancer screenings, totaling at 3,771 screenings. In Cundinamarca, the region which hosts the capital city, a total of 1,213,048 cervical cancer screenings were performed. The researcher measured the impact on cervical cancer screenings in December 2021 against the counterfactual. This impact was ~269 cases that were not performed in December 2021 as a result of the COVID-19 pandemic compared to the counterfactual. In Cundinamarca, unlike other regions, we observed a stagnant pre-pandemic trend, a sharp drop in screenings in March 2020, and an immediate upward trend starting in April 2020. In the month of April 2020, compared to the counterfactual, there were 27,359 screenings missed, and by the month of December 2021, there were only 5,633 cervical cancer screenings missed. Conclusion(s): The region of Cundinamarca's sharp climb back to pre-pandemic screening levels could signal the relatively stronger communication system in the region, and especially in the capital district of Bogota, in re-activating the economy. This can serve as an example of what should be implemented in other regions to improve cervical cancer screening rates. Areas for further research include the examination of social determinants of health, such as the breakdown of the type of insurance screened patients hold (public versus private), zone (urban versus rural), insurance providers of those screened, ethnicities of the patients screened, and percentage of screenings that resulted in early detection of cervical cancer.Copyright © 2023

Supplier selection framework to evade pseudo-resilience and to achieve sustainability in supply chains

PurposeDue to increasing uncertainty in the global business scenario, research on supply chain resilience is gaining significance. The outbreak of the COVID-19 pandemic has accelerated and magnified the issues already pertaining in the supply chain thereby increasing the vulnerabilities in the network. This study attempts to build the concept of pseudo-resilience in supplier selection and evaluation for supply chain sustainability.Design/methodology/approachA combination of multi-criteria decision-making methods AHP and R is adopted, and an integrated method called Combined AHP–R method is used to identify and include the property of pseudo-resilience into supplier selection processes.FindingsThe authors identified various factors contributing to pseudo-resilience considering supplier selection process and found the most important attribute. Using the combined AHP–R method, the suppliers were evaluated, considering the attributes contributing to the pseudo-resilience of supply chains and best supplier was selected.Originality/valueTo the best of our knowledge, this is the first study addressing a supplier selection problem for sustainable supply chains, considering pseudo-resilience. Also, this is the first study to apply the AHP–R method for supplier selection in the resilience or sustainability context.

A quantitative framework for health‐care service quality assessment in India

PurposeThe present situation of COVID-19 pandemic has put the health-care systems under tremendous stress and stringent tests for their ability to offer expected quality of health-care services, as it decides the sustainability and growth of health-care service providers. This study aims to deliver a quantitative framework for service quality assessment in the health-care industry by classifying the health-care service quality parameters into four balanced scorecard (BSC) perspectives.Design/methodology/approachTo determine the service quality for the Indian health-care system, decision-making trial and evaluation laboratory and analytical network process are integrated in a fuzzy environment to contemplate the interaction among BSC perspectives and respective performance measures.FindingsThe results indicate "internal processes” perspective assumes the key role within BSC perspectives, while performance measures "nursing staff turnover” and "staff training” play the key roles. The results also signify that "patient satisfaction” is the most vital issue and can be strongly influenced by measures belonging to the "learning and growth” perspective. In "learning and growth” perspective, "staff training” is the most decisive criteria, very highly influencing "patient satisfaction”, highly influencing "profitability,” "change of cost per patient (both in and out patients)” and "outpatient waiting time” while moderately influencing "staff satisfaction,” "bed occupancy” and "nursing staff turnover”. Moreover, "staff training” criteria have a positive influence on "nursing staff turnover.”Originality/valueThe contributions of this study are in two folds in the domain of quantification of service quality for the health-care system. First, it delivers an assessment framework for Indian health-care service quality. Second, it demonstrates an application of the framework for a case situation and validates the proposed framework.

Intelligent Methods and Models for Assessing Level of Student Adaptation to Online Learning

The problem of introducing online learning is becoming more and more popular in our society. Due to COVID-19 and the war in Ukraine, there is an urgent need for the transition of educational institutions to online learning, so this paper will help people not make mistakes in the process and afterward. The paper's primary purpose is to investigate the effectiveness of machine learning tools that can solve the problem of assessing student adaptation to online learning. These tools include intelligent methods and models, such as classification techniques and neural networks. This work uses data from an online survey of students at different levels: school, college, and university. The survey consists of questions such as gender, age, level of education, whether the student is in the city, class duration, quality of Internet connection, government/non-government educational institution, availability of virtual learning environment, whether the student is familiar with IT, financial conditions, type of Internet connection, a device used for studying, etc. To obtain the results on the effectiveness of online education were used the following machine learning algorithms and models: Random Forest (RF), Extra Trees (ET), Extreme, Light, and Simple Gradient Boosting (GB), Decision Trees (DT), K-neighbors (K-mean), Logistic Regression (LR), Support Vector Machine (SVM), Naїve Bayes (NB) classifier and others. An intelligent neural network model (NNM) was built to address the main issue. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR Workshop Proceedings (CEUR-WS.org)