At present, ensuring the security of MANET is a highly challenging chore due to the dynamic topology of the network. Hence, most of the existing Frameworks for Intrusion Detection Systems (IDS) seek to predict the attacks by utilising the clustering and classification mechanisms. Still, they face the major problems of reduced convergence speed, high error rate and increased complexity in the algorithm design. Therefore, this paper intends to utilise integrated optimisation and classification methods for accurately predicting the classified label. This framework comprises the working modules of preprocessing, feature extraction, optimisation and classification. Initially, the input datasets are preprocessed by filling the missing values, and normalising the redundant contents. After that, the Principal Component Analysis (PCA) technique is employed for selecting the set of features used for improving the classification performance. Consequently, the Grey Wolf Optimisation (GWO) technique is utilised for selecting the most optimal features based on the best fitness value, which reduces the overall complexity of IDS. Finally, the Deterministic Convolutional Neural Network (DCNN) technique is utilised for predicting whether the classified outcomes are normal or attacks. For validating the results, various performance metrics have been assessed during the analysis, and the obtained results are compared with the recent state-of-the-art models.

Evaluation is an analytical and organized process to figure out the present positive influences, favourable future prospects, existing shortcomings and ulterior complexities of any plan, program, practice or a policy. Evaluation of policy is an essential and vital process required to measure the performance or progression of the scheme. The main purpose of policy evaluation is to empower various stakeholders and enhance their socio-economic environment. A large number of policies or schemes in different areas are launched by government in view of citizen welfare. Although, the governmental policies intend to better shape up the life quality of people but may also impact their every day’s life. A latest governmental scheme Saubhagya launched by Indian government in 2017 has been selected for evaluation by applying opinion mining techniques. The data set of public opinion associated with this scheme has been captured by Twitter. The primary intent is to offer opinion mining as a smart city technology that harness the user-generated big data and analyse it to offer a sustainable governance model.

Irresponsible and imprudent usage of natural resources has presented a significant threat to the environment and its resources, contaminating them, and impeding their development. To mitigate this effect, responsible policies and practices must be adopted and implemented. One of the most successful strategies is to reduce our reliance on conventional items and replace them with green alternatives. However, insufficient information and expertise among consumers hamper their efforts to promote green products. Thus, it is critical to understand the factors influencing consumers' behavior and intentions toward green products to increase their acceptance. The purpose of the study is to learn more about how caring about the environment, having a desire to make a positive impact, and having a positive attitude towards the environment can help encourage people to buy ecofriendly products. 549 responses were collected using Google form from India, China, Sri Lanka, Bangladesh, and Pakistan. Structural Equation Modelling was used to test the forming assumptions. It was found that the study supports the hypotheses and the constructs of social issues, environmental conservation, and mindset, are significantly associated with the green buying behavior of the consumers. Additionally, it was found that environmental attitude should be further integrated to reinforce these relationships.

Evaluation is an analytical and organized process to figure out the present positive influences, favourable future prospects, existing shortcomings and ulterior complexities of any plan, program, practice or a policy. Evaluation of policy is an essential and vital process required to measure the performance or progression of the scheme. The main purpose of policy evaluation is to empower various stakeholders and enhance their socio-economic environment. A large number of policies or schemes in different areas are launched by government in view of citizen welfare. Although, the governmental policies intend to better shape up the life quality of people but may also impact their every day’s life. A latest governmental scheme Saubhagya launched by Indian government in 2017 has been selected for evaluation by applying opinion mining techniques. The data set of public opinion associated with this scheme has been captured by Twitter. The primary intent is to offer opinion mining as a smart city technology that harness the user-generated big data and analyse it to offer a sustainable governance model.

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