Air pollution consists of harmful gases and fine Particulate Matter (PM2.5) which affect the quality of air. This has not only become the key issues in scientific research but also turned to be an important social issues of the public’s life. Therefore, many experts and scholars at different R&Ds, universities, and abroad are involved in lot of research on PM2.5 pollutant predictions. In this scenario, the authors proposed various machine learning models such as linear regression, random forest, KNN, ridge and lasso, XGBoost, and AdaBoost models to predict PM2.5 pollutants in polluted cities. This experiment is carried out using Jupyter Notebook in Python 3.7.3. From the results with respect to MAE, MAPE, and RMSE metrics, among the models, XGBoost, AdaBoost, random forest, and KNN models (8.27, 0.40, and 13.85; 9.23, 0.45, and 10.59; 39.84, 1.94, and 54.59; and 49.13, 2.40, and 69.92, respectively) are observed to be more reliable models. The PM2.5 pollutant concentration (PClow-PChigh) range observed for these models is 0-18.583 μg/m3, 18.583-25.023 μg/m3, 25.023-28.234μg/m3, and 28.234-49.032 μg/m3, respectively, so these models can both predict the PM2.5 pollutant and can forecast the air quality levels in a better way. On comparison between various existing models and proposed models, it was observed that the proposed models can predict the PM2.5 pollutant with a better performance with a reduced error rate than the existing models.
The tremendous development in mobile technology attracts users’ attention. Thus, the users are shifting from traditional computational devices to smartphones and tablets, and because of that, mobile devices have anticipated most of the global IP traffic. However, mobile device’s resource-constrained behaviour cannot handle the heavy computational load. Mobile cloud computing (MCC) mitigates resource-constrained issues by enabling computing resources with minimal effort. However, providing security in MCC is an obstacle due to users’ uncertain and dynamic behaviour and the explosion of online computerized data. Providing security, confidentiality, and authentication is not enough in MCC; therefore, the users need authorization. Thus, the paper designs an access control mechanism by computing the trust based on the user’s uncertain behaviour. This mechanism mitigates the malicious actions caused by authenticated users. Performance results indicate that the access control mechanism accurately detects and mitigates malicious users from the MCC environment.
In this article, the photovoltaic thermal collector (PVT) have designed and fabricated using nanoparticle nanofluid. The cause of this is to check out the effect of using water and water-based totally graphene nanoplatelets at an awareness of 0.05 wt% on the performance of PVT structures. Outdoor assessments have been performed at quantity along with the float prices of 0.5 L/min and 1.0 L/min for the aforementioned nanofluids, respectively, using water as a reference fluid. The results that have been analyzed from an active angle confirmed and determined that, graphene water nanofluid achieved higher in phrases of photovoltaic active conversion, than water that might generate the first-class thermal performance sooner or later of the peak period of sun radiation and high mobile temperature. The inclusion of water in the PVT collector increases average daily electrical efficiency by 7.8%, and 8.5%at flow rates of 0.5 LPM and 1.0 LPM, respectively. Furthermore, using water in the PVT collector increases average daily thermal efficiency by 24.9%, and 26.3%at flow rates of 0.5 LPM and 1.0 LPM, respectively.
In this study, from a tree with a quasi-spanning face, the algorithm will route Hamiltonian cycles. Goodey pioneered the idea of holding facing 4 to 6 sides of a graph concurrently. Similarly, in the three connected cubic planar graphs with two-colored faces, the vertex is incident to one blue and two red faces. As a result, all red-colored faces must gain 4 to 6 sides, while all obscure-colored faces must consume 3 to 5 sides. The proposed routing approach reduces the constriction of all vertex colors and the suitable quasi-spanning tree of faces. The presented algorithm demonstrates that the spanning tree parity will determine the arbitrary face based on an even degree. As a result, when the Lemmas 1 and 2 theorems are compared, the greedy routing method of Hamiltonian cycle faces generates valuable output from a quasi-spanning tree. In graph idea, a dominating set for a graph S = V , E is a subset D of V . The range of vertices in the smallest dominating set for S is the domination number ( S ). Vizing’s conjecture from 1968 proves that the Cartesian fabricated from graphs domination variety is at least as big as their domination numbers production. Proceeding this work, the Vizing’s conjecture states that for each pair of graphs S , L .
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