Meenakshi Sharma ¹, Himanshu Aggarwal ²

Affiliations
1 Computer Science and Engineering Department, S.S.C.E.T, Badhani - 145001, Punjab, IN
2 Computer Engineering Department, Punjabi University, Patiala - 147002, Punjab, IN

Abstract

Background/Objectives: Electronic Health Record are unique electronic documents composed of information like patient history records, demographics, prescribed medications, laboratory reports and computerized tomography etc. to pertaining the patient health care. The main objective of the paper is to review the present adoption rate of EHR in India with respect to global market. Methods/Statistical Analysis: EHR is the key component for the clinical decision support system .To review the current scenario of adaption rate of EHR, bibliographic learning was obtained from many hospital sources. In addition, contact was made with EHR vendors. Findings: During the pilot study of about seven month, around twenty major hospitals encounters in which successfully the EHR system has been implemented. Globally the adoption rate of EHR in major countries are China (96%), Brazil (92%), France (85%), and Russia (93%) in this respect. In year of 2020, globally Market of electronic health records will place at US$25.98 billion as per the reporting of CAGR. Interoperability standards issues; lack of funds; shortage of suitable governance health policies are the major barriers in adoption of EHR in India. Application/Improvements: Adoption and implementation of EHR should be made mandatory in large sized and medium sized hospitals. In upcoming years EHR system require to incorporated a framework of standards, latest tools and consolidation of system providers.

Keywords

Electronic Health Record, FHIR, HL7, Public Health, Security.

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Bhim Sain Singla ¹, Himanshu Aggarwal ²

Affiliations
1 Department of Computer Science and Engineering, College of Engineering and Management, Punjabi University Neighbourhood Campus, Rampura Phul - 151103, Punjab, IN
2 Department of Computer Science and Engineering, Punjabi University, Patiala - 147002, Punjab, IN

Abstract

Objectives: In this globalized competitive world, websites have become so important that an academic institution cannot think of surviving for a long time without an appropriately designed and engineered website. Therefore, the key objective of this study was to evaluate the internal quality aspects of some selected universities’ websites of Punjab, northern state of India. Methods/Statistical Analysis: For the sample selection of universities, stratified random sampling was used by categorizing all the universities’ websites of Punjab into four groups such as State, Private, Deemed, or Central universities on the basis of their status. For the measurement of website’s internal quality attributes such as load time, total size of web page, requests per content type during loading, HTML check errors and broken links which cannot be perceived by users otherwise, three web testing tools such as W3C validator, Web Page Test and Selenium were used in this study. Findings: The results obtained in this study shows that the efficiency/performance of Lovely University’ website is the best among the websites of other universities considered in this study. This particular website which represents a private university takes the least download time. Minimum number of HTML errors and broken links were found on this website as compared to other websites. It shows that web designers and administration of private universities are utmost concerned regarding their website quality. Application/Improvements: By improving the internal quality parameters of websites considered in this study, website’s visibility in search engines can be improved which is an imperative aspect for high traffic rank.

Keywords

Automation Testing, Internal Quality Factors, Universities’ Websites, Website Evaluation, Web Testing Tools.

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Raghu Garg ¹, Himanshu Aggarwal ¹

Affiliations
1 Department of Computer Engineering, Punjabi University, Patiala - 147002, Punjab, IN

Abstract

Objective: With the digital advancements in the field of agriculture, a large amount of data is being produced constantly as a result agriculture data has entered the world of big data. Statistical Analysis: As the development processes, the requirement of the parallel computing, compatible data management infrastructure and novel analytics paradigm to extract information from huge amounts are also increases. A single machine cannot store and analyze this large amount of data. The polynomial time required to access this kind of large data. Findings: The solution to store and analyze such massive amounts of data is big data analytics. In this paper a big data analytics recommendation framework is developed for providing solutions of crop disease based on historical data using Hive and Hadoop. The data is collected from various sources like laboratory reports, agriculture information web pages, and expert recommendation for the developed framework. After the collection of raw data, the irrelevant or the redundant data that is also known as the noise, should be removed. The next step is to extract the features from cleaned data, normalization of data is done in order to remove the technical variations. Once normalization is complete the data is uploaded on HDFS and save in a file that is supported by Hive. Thus classified data is finally located on the specific place. In the next step HiveQL is used to analyze agriculture data based on features and then prioritize the outcome based on crop disease symptoms and in the last a high priority solution is recommended. Application/Improvements: In the paper prioritize outcomes are useful for agriculture officers, researchers to easily understand, and helpful for recommending a solution based on evidence from historical data.

Keywords

Agriculture, Big Data, Expert Recommendation, Hadoop, Hive

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