World Wide Web is exploding in terms of the number of web sites and users. Without search engines the web sites will not be visible to the users. Different search engine crawlers behave in different ways while they access a web site. The number of visits and pages crawled by search engines could be helpful in identifying their behavior and also the server load. A forecasting model in time series has been proposed for predicting the number of pages crawled by search engines. This model was compared with the actual values and it was found feasible. General TermsWeb log mining, Web analytics

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World Wide Web is growing at a tremendous rate in terms of the number of visitors and number of web pages. Search engine crawlers are highly automated programs that periodically visit the web and index web pages. The behavior of search engines could be used in analyzing server load, quality of search engines, dynamics of search engine crawlers, ethics of search engines etc. The more the number of visits of a crawler to a web site, the more it contributes to the workload. The time delay between two consecutive visits of a crawler determines the dynamicity of the crawlers. The ARIMA(1,1,0) Model in time series analysis works well with the forecasting of the time delay between the visits of search crawlers at web sites. We considered 5 search engine crawlers, all of which could be modeled using ARIMA(1,1,0).The results of this study is useful in analyzing the server load.

In India the clinical pharmacy services are yet at the infancy stage, very few private hospitals were adopted this system while these services are totally scarce in government hospitals. The aim of the study was to demonstrate the role and importance of clinical pharmacist and to assess the clinical pharmacy services provided. A Prospective analysis of the documented clinical pharmacy services performed by Pharm D interns were assessed for a period of 6 months. A total of 334 past medication history interviews, 333 patient counseling, 325 prescription auditing, 302 drug interactions, 55 medication errors and 23 Drug information queries were provided. Among 272 drug-drug interactions, 60.66% moderate drug-drug interactions and a least of 8.08% major drugdrug interactions and most common management plan recommended was dose adjustments (23.52%). Majority of the patients were counseled regarding the name and purpose of the prescribed medicines (96.39 %) and 34.83% reported barriers during their counseling. Among Past medication history interviews, 32.63% of patients had a history of medication intake. 59.38% of prescriptions were not prescribed drugs in their generic names. Maximum number of injections prescribed per prescription was three (20%), antibiotics per prescription were one (44.3%) and 91% of drugs were prescribed from the essential drug list. Of 55 prescribing errors reported majority of errors were belonging to category A (72.72%). It was found that 65.21% queries were to update the requestor's knowledge and 52.71% used primary sources to respond the queries. The study stresses impeccable role of clinical pharmacist in patient's care.