What Is Grounded Theory Good For?

Grounded theory (GT) made its appearance in the social sciences in 1967 with publication of Barney Glaser and Anselm Strauss’s The Discovery of Grounded Theory. Glaser and Strauss advocated for systematically discovering and interpreting empirical data to generate theory, in contrast to testing or verifying theory derived from a priori assumptions. In the intervening 50 years, GT has spread into a wide range of fields including journalism and mass communication. Variations of the method have been developed, and debate has ensued about its relation to positivism and constructivism as well as pragmatism and postmodernism and about its value for critical race theory, feminist theory, and indigenous and other critical methods and theories. When and how is it best used? Is it misunderstood or misused by some? Is it more than a method? We asked senior scholars with expertise in GT to reflect on these issues, beginning with Vivian Martin, coeditor with Astrid Gynnild of Grounded Theory: The Philosophy, Method, and Work of Barney Glaserpublished by BrownWalker Press (2012). Martin, professor and chair of the Department of Journalism at Central Connecticut State University, argues the method has been misunderstood even by those who use it, often conflated with qualitative studies, with only two GT studies published in journalism and mass communication. It is practical and subversive, she observes, with the ability to develop new concepts and link ideas across disciplines. She advocates a closer adherence to Glaser’s original intentions for the method. Responding to Martin is Clifton Scott, associate professor in the Department of Communication Studies at the University of North Carolina at Charlotte. Scott is the author of “Grounded Theory” in Encyclopedia of Communication Theory, edited by Steven Littlejohn and Sonja Foss published by SAGE (2009). While agreeing with Martin that the name often is misapplied, Scott argues for less preoccupation with policing the purity of the method in favor of developing multiple approaches appropriate to it as a methodology. Reacting to both Martin and Scott, Bonnie Brennen critiques the original GT approach as neglecting “methodological self-consciousness,” which would uncover researchers “theoretical assumptions, power relations, class positions and personal experiences.” Brennen, the Nieman Professor of Journalism in the Diederich College of Communication at Marquette University, is the author of Qualitative Research Methods for Media Studies, second edition, published by Routledge in 2017. Finally, Meenakshi Gigi Durham, responding to all three, expresses optimism about GT’s potential to spur new inquiry through exploration of social life, while she proposes that, like all theory, it be seen as necessarily dynamic and evolutionary. Durham is a professor in the School of Journalism and Mass Communication at the University of Iowa and associate dean of the College of Liberal Arts and Sciences. She is the editor with Douglas M. Kellner of Media and Cultural Studies: Keyworks, second edition, published by Blackwell (2011). Lana Rakow, Associate Editor Louisa Ha, Edito

Performance evaluation of Map-reduce jar pig hive and spark with machine learning using big data

Big data is the biggest challenges as we need huge processing power system and good algorithms to make an decision. We need Hadoop environment with pig hive, machine learning and hadoopecosystem components. The data comes from industries. Many devices around us and sensor, and from social media sites. According to McKinsey There will be a shortage of 15000000 big data professionals by the end of 2020. There are lots of technologies to solve the problem of big data Storage and processing. Such technologies are Apache Hadoop, Apache Spark, Apache Kafka, and many more. Here we analyse the processing speed for the 4GB data on cloudx lab with Hadoop mapreduce with varing mappers and reducers and with pig script and Hive querries and spark environment along with machine learning technology and from the results we can say that machine learning with Hadoop will enhance the processing performance along with with spark, and also we can say that spark is better than Hadoop mapreduce pig and hive, spark with hive and machine learning will be the best performance enhanced compared with pig and hive, Hadoop mapreduce jar

AN OVERVIEW ON THE BIOLOGICAL PERSPECTIVES OF SIDA CORDIFOLIA LINN

Plants have been used since ancient times to heal and cure diseases and to improve health and well being. Sida cordifolia Linn belonging to family Malvaceae is widely distributed throughout the plains of India. The various parts of Sida cordifolia possess different biological perspectives such as antidiabetic, anti stress, anti-inflammatory, analgesic, hepatoprotective and anticancer activity. This plant has great potential for development of ayurvedic and modern medicines. The present study is focused on pharmacological review of Sida cordifolia L

Role of Iron Deficiency in Chronic Diffuse Hair Loss

There are conflicting reports of association between iron deficiency and hair loss in the literature. So we conducted this study to evaluate the role of iron deficiency in chronic diffuse hair loss in women of reproductive age group. Serum ferritin, a marker of iron deficiency, was recorded in 150 consecutive patients of chronic diffuse hair loss (FPHL n=69, CTE n=81) and in healthy controls (n=100). The mean serum ferritin (SF) recorded was 9.87, 10.80, 10.30 and 11.20 ng/mL for FPHL, CTE, total patients (FPHL and CTE) andcontrol group respectively, and it did not show any significant difference between these groups. Number of patients who recorded a serum ferritin label of less than 10 ng/mL (normal range 10–126ng/mL) were 48 (69.51%), 51 (62%), 99 (66%) and 63 (63%) for FPHL, CTE, total patients and controls respectively, and this also did not reveal any significant difference between the groups. We did not find any association between low serum ferritin (iron deficiency) and chronic diffuse hair loss in women of reproductive age group

A Competent Approach for Type of Phishing Attack Detection Using Multi-Layer Neural Network

With the enlargement of contemporary technologies and the large-scale global computer networks web-attacks are escalating because of emergent curiosity of people and lawful institutions towards internet. Phishing is one of web-attack carried out by attacker using both social and technical engineering. Generally on web more attacks are launched every month with seek of crafting web addict to consider that they are contacting with a legalized entity for the intention of embezzle identity information, logon records and account details. The phishing attack detection and classification methods are utilized for the prevention and in-depth analysis of the attacks. In this paper, the proposed model has been designed with the multi-directional feature analysis along with the Back-Propagation Probabilistic neural network (BP-PNN) classification. The proposed model has performed better in the terms of the accuracy in all of the domains based upon the attack detection and classification

Academic Excellence in Technical Institutions

The paper describes the changes taking place in the external environment of education institutions and their effects on the functioning of institutions. It highlights various management philosophies being used by industries and companies providing employment to graduates. All the stakeholders expects the excellence in all respects from educational institutions. It is very dificult to translate and satisfy the expectations of different stakeholders. So in this paper deinition of excellence, its dimensions, and characteristics in context of education institutions are described. At the end formats are suggested to assess the effectiveness of the institution on dimensions and characteristics of excellence. The paper is based on literature review, experiences of the authors and views of experts

Survey on Managing XML Search through Personalization

Information Retrieval IR based on keyword on web has become very significant and XML has become the widely used format for sharing of information. The number of resources of information has increased significantly and retrieval of correct data according to user preference may not be achieved efficiently. In order to improve the search of XML documents according to the user requirement and preference we use personalized search based on user preference stored as an XML. The problem in personalized search is in identifying the correct preferences based on the search text. In this paper we have done a survey of papers related to XML search and personalization. From this survey we have come up with a proposed solution, to store the user preferences with keywords and sub preferences as an XML document and related text as keywords. To identify the user preferences based on the query the user preference XML is loaded. The user preference nodes related to the keyword is identified and ranked based ranking function of top k algorithm. The documents will now be listed based on keyword and also based on keyword and preference node combination. The relevance status value of the resulting documents will be identified in both the search and the final search result will be listed by considering the RSV value using the re-ranking strategies. DOI: 10.17762/ijritcc2321-8169.15039

PUBLISHING SEARCH LOGS PRIVACY GUARANTEE FOR USER SENSITIVE INFORMATION

Search Engine companies maintain the search log to store the histories of their users search queries. These search logs are gold mines for researchers. However, Search engine companies take care of publishing search log in order to provide privacy for user’s sensitive information. In this paper we analyze algorithm for publishing frequent keywords, Queries, and Clicks of a search log. Before Zealous algorithm, we discuss how different variants of anonymity failed to provide good utility (publishing frequent items) and strong privacy for the search logs. And also this paper includes how zealous algorithm provides good utility and strong privacy for publishing search logs

Biochemical attributes of Indian mustard (Brassica juncea) and rapeseed (B. napus) as influenced by salicylic acid and benzothiadiazole

A field experiment was conducted during 2011-12 at Punjab Agricultural University, Ludhiana, India to assess the effect of foliar application of elicitors viz., salicylic acid (SA) and benzothiadiazole (BTH) on biochemical constituents of Brassica seeds. Seeds of Brassica juncea and B. napus were sown in the field during rabi season. Four different treatments of elicitors along with a fungicide and control were given to 10 week old plants up to four consecutive weeks. After harvesting, the seeds were analyzed for oil, total soluble protein and glucosinolate content. Results indicated that the elicitor treatments increased the oil, total soluble protein and glucosinolate content in seeds of both the Brassica species. In B. juncea, BTH (7 ppm) + SA (17 ppm) showed 12.5% higher oil content than control. In B. napus, the combinations of elicitors viz., BTH (3 ppm) + SA (33 ppm) and BTH (7 ppm) + SA (17 ppm) exhibited 15% increase in oil content compared to control. Treatment containing BTH (3 ppm) + SA (33 ppm) showed 18.72 and 15.86% higher total soluble protein content in B. juncea and B. napus seeds, respectively compared to control. In B. juncea, BTH (3 ppm) + SA (33 ppm) exhibited 7.13% higher glucosinolate content compared to control. In B. napus, BTH (7 ppm) + SA (17 ppm) showed 11.23% higher glucosinolate content than control. In conclusion, the application of elicitors, i.e., SA and BTH could be a useful tool for improving the nutritive value of B. juncea and B. napus seeds