The present study systematically examines the structure and functions of metasearch engines (MSEs) viz. Dogpile, Metacrawler, DuckDuckGo and Startpage. Further, it identifies the features and services of four metasearch engines and compares them. A checklist method was used to evaluate the four metasearch engines.These check spots are prepared regarding features and services of metasearch engines. The data were collected between April 1 to June 14, 2021, spending two hours daily. Initially, the data was recorded after accessing each MSE, and later,the data was transferred to MS Excel. The study ascertained that out of 101 check spots, Dogpile scored (66) points, Metacrawler (63), DuckDuckGo (71), and Startpage (59). DuckDuckGo is ranked first among all the four metasearch engines with 70.3 %, followed by Dogpile, Metacrawler, and Startpage respectively. A checklist used in the study contains only 101 check spots to compare the metasearch engines. Further, users’ perception regarding the four metasearch engines is also not covered in the present study. The present study is the first of its kind, which compares four popular metasearch engines using a checklist method. The outcomes of the study shall help research scholars, librarians, information scientists, faculty members, and common masses choose the appropriate metasearch engine. Further, the study shall also help the developers of e-resources in incorporating more features so that users can benefit.

Increase in number of spam incidents is causing a very serious threat to Social Networking World which has in turn become an important means of interaction and communication between public users. It is not only dangerous to the public users, but it also covers much of the bandwidth of the Internet traffic. Most of current spam filters in use are based on the subject content of email, Facebook, twitter. Social Networking Services also provide great possibilities to take advantage of user identification and other social graphdependent features to improve classification. In this paper, the proposed System uses machine learning [3] approach for spam detection based on features extracted from social networks constructed from social networking site message metadata and logs. Flags and scores are assigned to senders based on their possibility of being a legitimate sender or spammer. Moreover, proposed System also explores various spam filtering techniques and possibilities. Social networking sites are vulnerable to mass spam incidence as well as users data theft such as credit card details, user activities and users taste for criminal purposes .Email subject headers are used to check spam email, spam on Social networking Sites is often accompanied by a wealth of data on the sender, metadata can be used to build more accurate detection mechanisms. System uses these terminologies to choose features that best differentiate spammers from legitimate users. On basis of this technique system flag user system or message as spam and legitimate messages.

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Health and Medical informatics is the intersection of information science, medicine and healthcare. It began to take-off in the United States in the 1950s with the rise of the microchip and computers. Over the course of time, health and medical informatics has evolved as a new field. Today, there are multiple challenges faced in medicine pertaining to record keeping like lots of paper-based records, medication errors and documenting patient related information. It deals with the resources, devices and methods required to optimize the acquisition, storage, retrieval and use of information in health and biomedicine. Health informatics tools include not only computers but also medical and health data, clinical guidelines, formal medical terminologies, knowledge for scientific inquiry and problem solving and decision making through information and communication systems. Health informatics technology includes the electronic information technology used during the course to track patient care and drawing insights from informatics data are of increasing value.Healthcare and medical industry is undergoing a paradigm shift with plethora of big data in healthcare research and advances of data science in the medical domain. With the advancements of computer knowledge, internet and voice recognition and development of wearable health monitoring devices and wireless communication network, it is quite easy to collect complex volume of health data. Another powerful impetus which help in collection of large volume of data, previously inaccessible, is social media and health awareness thorough these platforms. Digital health monitoring devices are helping and playing an important role in educating people to identify telltale signs of serious medical conditions. As the technology will continue evolving and the information collected will pave path for new ideas, thinking and transformation of the overall healthcare industry and motivated to improve human health.There are several medical technologies under development which has the potential to revolutionize the healthcare industry. Some of these medical technologies are orthopedic devices embedded with chips, screening device for cancer, and the Tricorder that can scan patients and help diagnose what is wrong. Due to the availability of such huge information of data and their availability through various applications, people are nowadays taking control of their own health in a highly personalized manner. These technologies are not only being transforming the care of chronic ill patients but also for those people who remain want to be healthy.Integrating the latest developments in technology into the field of medicine is challenging and would require more healthcare professionals to become formally trained in technology. As the technology for collecting, analyzing and transmitting data in medical and health informatics continues to grow, there is possibility of more and more healthcare applications and systems to emerge. It will also need an additional education/training to understa...

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