Role of Eco-Friendly Products in the Revival of Developing Countries’ Economies and Achieving a Sustainable Green Economy

Mustafa, Sohaib; Hao, Tengyue; Jamil, Khalid; Qiao, Yu; Nawaz, Muhammad

doi:10.3389/fenvs.2022.955245

Cited by 41 publications

(68 citation statements)

References 41 publications

(93 reference statements)

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“…An ANN is a non-linear statistical data simulation tool that can be trained several times to enhance model performance (Mustafa et al, 2022b). An ANN is used for prediction and categorization of data.…”

Section: Artificial Neural Networkmentioning

confidence: 99%

“…Table 6 presents the root mean square of errors (RMSEs). An RMSE represents the predictive power of a model (Mustafa et al, 2022b;Talwar et al, 2022). In our model, the RMSE values (Table 6) for training (mean = 0.088, STD = 0.007) and testing (mean = 0.082, STD = 0.014) represent the high predictive power of the constructed ANN model for AI.…”

Section: Artificial Neural Networkmentioning

confidence: 99%

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Digital Students’ Satisfaction With and Intention to Use Online Teaching Modes, Role of Big Five Personality Traits

et al. 2022

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During the COVID-19 pandemic, online teaching modes were found vital to continue students’ learning process, but sustainable implementation of online teaching models is an area of concern for policymakers. Psychiatrists are also eager to know students’ behavior toward learning and modes of teaching during COVID-19. We have drawn a model based on the big five personality traits to study students’ satisfaction with online teaching modes and their adoption intentions toward online teaching modes. We have collected data from 718 bachelor’s and master’s level students from four different universities. We have applied the SEM-ANN dual-stage approach to test personality traits’ influence and ranked them based on their normalized importance. The results revealed that agreeableness, conscientiousness, neuroticism, and openness positively influence students’ satisfaction with online teaching models, but that extraversion negatively influences their satisfaction. Agreeableness, extraversion, and neuroticism positively impact, but openness negatively influences. Conscientiousness does not affect adoption intention. Furthermore, agreeableness is the most significant, and conscientiousness is the least important factor for students to adopt online teaching modes. The findings of the study have useful perceptiveness for educational policymakers, academics, and psychiatrists.

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Section: Artificial Neural Networkmentioning

confidence: 99%

Section: Artificial Neural Networkmentioning

confidence: 99%

Digital Students’ Satisfaction With and Intention to Use Online Teaching Modes, Role of Big Five Personality Traits

et al. 2022

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“…It means our model has high predictive power and is accurate in prediction (Kalinić et al, 2021;Mustafa et al, 2021). Furthermore, to assess the efficacy of the ANN models, we calculated a goodness-of-fit coefficient equivalent to the R 2 in the regression models based on a given approach (Figure 5) (Kalinić et al, 2021;Mustafa et al, 2022c).…”

Section: Artificial Neural Network Analysismentioning

confidence: 99%

How a Successful Implementation and Sustainable Growth of e-Commerce can be Achieved in Developing Countries; a Pathway Towards Green Economy

Mustafa

Hao

Qiao

et al. 2022

Front. Environ. Sci.

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Apart from the goal of the digital world and other benefits of e-commerce, it becomes the need of time during this COVID-19 pandemic. Successful implementation and sustainable growth of e-commerce in developing countries is a challenge. The goal of the digital world without the implementation and sustainable growth of e-commerce in developing countries is incomplete. Based on UTAUT theory, we have developed an integrated model to study the developing countries’ consumers’ adoption intentions towards e-commerce. We collected a valid useable sample of 796 respondents from a developing country, applied the SEM-ANN two-step hybrid approach to testing the proposed hypothesis, and ranked the antecedents according to their importance. Results revealed that Trust in e-commerce, Perceived risk of using e-commerce, Ease of use in e-commerce, Curiosity about e-commerce, Facilitating Conditions, and Awareness of e-commerce benefits influence the adoption intentions of developing countries’ consumers. Sensitivity analysis results revealed that Ease of use in e-commerce platforms and awareness of e-commerce benefits are the two most crucial factors behind the adoption intentions in developing countries. The study’s findings help authorities adopt sustainable e-commerce, multinational companies effectively market their goods online, and academics better understand how inhabitants of developing nations perceive e-commerce.

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“…The lightweight application programming interface (API) is used for direct sensor connectivity with a cloud while the data collected, users, and sensors are served in a highly scalable way. Fitness data monitors are standard instruments used to assess physical involvement in class times and strengthen fitness principles related to well-being, such as aerobic ability and enhancing quantitative physical activity metrics inside and outside schools (Mustafa et al, 2022c). The understanding of wearable technology started with a wearable device, that is, a completely controllable device that can run without thinking or effort.…”

Section: Wearable Sensor-based Fitness Processmentioning

confidence: 99%

Physical education and emergency response system using deep learning: A step toward sustainable development of physical education environment

Guangde

2022

Front. Environ. Sci.

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The physical education (PE) system’s key goal is to educate individuals and the large community of participating students to achieve self-fulfillment. Deep learning uses integrated expertise to help students master challenging conditions in unfamiliar contexts. It is normal to get injuries while training or playing, and as an emergency response to mitigating students’ future risks by the availability of first aid, safety steps are promptly taken. Therefore, this article suggests a “physical education and emergency response system using deep learning” (PSERS-DL) to handle such situations effectively. In real-time, the PE environment can be tracked using a global positioning system-enabled surveillance system to immediately provide the wounded student with protective measures. The acquired visuals are immediately analyzed using a deep learning model, convolutional neural network (CNN). The 27 layers proposed in the CNN model have been evaluated compared with other deep learning models. The simulation results showed that the proposed PSERS-DL can assure the emergency response with the highest accuracy of 97.61%. The experimental results showed that the proposed PSERS-DL model enhances an accuracy ratio of 95.6%, a performance ratio of 97.6%, movement detection analysis ratio of 96.3%, a learning rate of 95.2%, an efficiency ratio of 98.1%, a security ratio of 93.5%, a delay time ratio of 33.2%, and a behavior analysis ratio of 90.7% when compared to other existing approaches.

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Role of Eco-Friendly Products in the Revival of Developing Countries’ Economies and Achieving a Sustainable Green Economy

Cited by 41 publications

References 41 publications

Digital Students’ Satisfaction With and Intention to Use Online Teaching Modes, Role of Big Five Personality Traits

Digital Students’ Satisfaction With and Intention to Use Online Teaching Modes, Role of Big Five Personality Traits

How a Successful Implementation and Sustainable Growth of e-Commerce can be Achieved in Developing Countries; a Pathway Towards Green Economy

Physical education and emergency response system using deep learning: A step toward sustainable development of physical education environment

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