Cloud computing is emerging as an increasingly popular computing paradigm, allowing dynamic scaling of resources available to users as needed. This requires a highly accurate demand prediction and resource allocation methodology that can provision resources in advance, thereby minimizing the virtual machine downtime required for resource provisioning. In this paper, we present a dynamic resource demand prediction and allocation framework in multi-tenant service clouds. The novel contribution of our proposed framework is that it classifies the service tenants as per whether their resource requirements would increase or not; based on this classification, our framework prioritizes prediction for those service tenants in which resource demand would increase, thereby minimizing the time needed for prediction. Furthermore, our approach adds the service tenants to matched virtual machines and allocates the virtual machines to physical host machines using a best-fit heuristic approach. Performance results demonstrate how our best-fit heuristic approach could efficiently allocate virtual machines to hosts so that the hosts are utilized to their fullest capacity.

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Within the context of technological and digital communication boom in India, the concern of fake news and misinformation plays a muted role in democratic and social welfare process; the current research focuses on narratives of social media users from Achrol and Chandwaji villages (Jaipur, Rajasthan). This paper tries to understand the logic of social media engagement and participation of users within the framework of understanding cultural turn in fake news and belief among the users. The paper tries to argue that the fakeinformation disseminated in form of news becomes more complicated when it passes through filters of anonymity and identity misinterpretation in social media. The logic of information consumption and dissemination should be studied with the changing communication patterns and business models of modem India. The current research is part of social research project carried over after 2016 Indian banknote demonetization to understand the derivations of fake news and its evolution in daily life of Indian users.

The information flow in digital societies is discussed and analyzed for more than a decade with a close watch on social media networks. The shift from traditional forms of communication to social media enables users to gratify their daily needs of information digitally. The current paper builds on narrative analysis of selected social media active users and their digital social engagement to understand how a user and a network of users engagement with information. To understand the role of social media literacy, the current paper interviews the users and correlated the findings with contemporary literature on social media. The results show that social media literacy becomes the pillar of the information system, but it works in the micro-level of societies at the crossroads of online and offline spaces.

I S S N 2 3 4 9 -4 3 7 9 V o l u m e 5 N u m b e r 1 J o u r n a l o f A d v a n c e s I n H u m a n i t i e s 221 | P a g e h t t p : / / c i r w o r l d . AbstractThe advent of new technology such as the social media has become one of the important business imperative. It has altered marketing strategies of growing hotel industry. Its interactivity and accessibility qualify it as one of the most cost effective marketing tools today. With growing competition and demand hoteliers need to rethink their strategy at each level of business model and also need to align its strategies with customer requirement. This research seeks to explore use of social media by business hotels in NCR and customers perspective in context to usage and advantages of social media. The results and limitations of the study and future directions of research are discussed.

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To assess C reactive protein (CRP) in detecting type-II diabetes mellitus with nephropathy. Patients with a history of diabetes type 2 with nephropathy and patients with diabetes type 2 without nephropathy were included in the study. A total of 30 cases, both male and female, were recruited and compared with30 normal healthy adults. Each participant (age, gender, BMI, i.e. body mass index and WHR, i.e. waist-hip ratio) were recorded. CRP was measured by immunoturbidimetric method. Total cholesterol, triglycerides, and high-density lipoprotein (HDL) cholesterol were measured by the CHOD-POD method, GPO-PAP method, and CHOD-POD/phosphotungstic method. Low-density lipoprotein (LDL)cholesterol and very low-density cholesterol were measured by Friedewald formula. Lipoprotein ratios ware also calculated. CRP was significantly (p=0.0001) higher among cases (12.60±3.30) compared to controls (5.47±4.29). CRP >9.5 correctly (efficacy) predicted DM2 with DN among 46.7% cases with sensitivity and specificity of 93.3 (95%CI=84.4-102.3) and 76.7 (95%CI=61.5-91.8) respectively. The area under the curve (AUC) was also high (AUC=0.85, 95%CI=0.75-0.95). There was a poor correlation of CRP with lipid profile among DM-2 with DN. Linear regression analysis showed that lipid biomarkers such as HDL, LDL, VLDL & total cholestarol-to-HDL ratio as well as BMI and WHR were positive predictors of CRP after adjusted for age and sex. In turn, HDL, LDL, VLDL and TC to HDL ratio level were a negative predictive factor of CRP levels. The increase of 1 unit on HDL was associated with a reduction of 1.25 in CRP levels. However, all the predictors had no statistical significance (p>0.05). In this study, the level of CRP was higher among cases compared to controls. This study also found that CRP >9.5 had good sensitivity and specificity in predicting DM2 with DN.