115,853 research outputs found

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Economic impacts of SEZs: Theoretical approaches and analysis of newly notified SEZs in India

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    This study aims at examining the economic impacts of SEZs in the Indian context. While doing so, it addresses the conceptual confusion about SEZs, outlines the evolution of SEZs; traces economic philosophies explaining the rationale and benefits of SEZs; extends existing theoretical literature to explain the economic impacts of SEZs; assesses the economic impacts of newly notified SEZs in India; reviews the strategies followed by various state governments in the implementation of the policy ; and draws policy implications. It argues that the existing economic theories donot adequately explain the rationale and contribution of SEZs. These approaches need to be extended by integrating the provisions of the theories of agglomeration economies and global value chains within the existing theoretical frameworks. It analyses the economic impacts of SEZs within the extended theoretical framework. It finds that while SEZs are stimulating direct investment and employment, their role appears to be more valuable in bringing about economic transformation from a resource-led economy to a skill and technology-led economy; from low value added economic activities to high value added economic activities; from low productive sectors to high productive sectors; and from unorganised to organized sectors, both at the national and regional levels. They have the potential of promoting new knowledge intensive industries; augmenting existing industrial clusters/industrial states; diversifying the local industrial base; and localizing global value chain. However, a strategic approach is required to reap the opportunities offered by SEZs.Special economic zones; Exports; FDI; Economic diversification; Agglomeration economies; global value chains;India

    sj-docx-1-jdr-10.1177_00220345221098910 – Supplemental material for Systemic Multimorbidity Clusters in People with Periodontitis

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    Supplemental material, sj-docx-1-jdr-10.1177_00220345221098910 for Systemic Multimorbidity Clusters in People with Periodontitis by H. Larvin, J. Kang, V.R. Aggarwal, S. Pavitt and J. Wu in Journal of Dental Research</p

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Healing Effect of Botox in Dental Office

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    ABSTRACT In this era of passion to look beautiful, various new technologies are emerging to enhance and improve the physical appearance of people. Botox is emerging as one such popular treatment to improve various facial anomalies. Minimally invasive treatment can be done by botox, which can expand our therapeutic options for the benefit of our patients. The aim of this article is to elaborate the healing aspect of this toxin, i.e., botox. How to cite this article Mittal R, Singla M, Aggarwal H. Healing Effect of Botox in Dental Office. J Oral Health Comm Dent 2017;11(1):13-18. </jats:sec

    Decoding "Public authority" under the RTI act: a comment on Subhash Chandra Aggarwal v. Indian national congress

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    The June, 2013 order of the Central Information Commission ("CIC") in Subhash Chandra Aggarwal v. Indian National Congress which brought political parties within the scope of the Right to Information ("RTI") Act, has highlighted some issues regarding the drafting and interpretation of the RTI Act. The CIC held that the six national political parties which were respondents in the case, have the ingredients that qualify them as "public authorities" within the meaning of section 2(h) of the RTI Act. In this comment the author argues that the reasoning for holding what constitutes substantial financing that makes a body a "public authority" is not clear and the interpretation of the definition of "public authority" is inconsisten

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods

    Extracting knowledge from big data for sustainability: A comparison of machine learning techniques

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    At present, due to the unavailability of natural resources, society should take the maximum advantage of data, information, and knowledge to achieve sustainability goals. In today's world condition, the existence of humans is not possible without the essential proliferation of plants. In the photosynthesis procedure, plants use solar energy to convert into chemical energy. This process is responsible for all life on earth, and the main controlling factor for proper plant growth is soil since it holds water, air, and all essential nutrients of plant nourishment. Though, due to overexposure, soil gets despoiled, so fertilizer is an essential component to hold the soil quality. In that regard, soil analysis is a suitable method to determine soil quality. Soil analysis examines the soil in laboratories and generates reports of unorganized and insignificant data. In this study, different big data analysis machine learning methods are used to extracting knowledge from data to find out fertilizer recommendation classes on behalf of present soil nutrition composition. For this experiment, soil analysis reports are collected from the Tata soil and water testing center. In this paper, Mahoot library is used for analysis of stochastic gradient descent (SGD), artificial neural network (ANN) performance on Hadoop environment. For better performance evaluation, we also used single machine experiments for random forest (RF), K-nearest neighbors K-NN, regression tree (RT), support vector machine (SVM) using polynomial function, SVM using radial basis function (RBF) methods. Detailed experimental analysis was carried out using overall accuracy, AUC-ROC (receiver operating characteristics (ROC), and area under the ROC curve (AUC)) curve, mean absolute prediction error (MAE), root mean square error (RMSE), and coefficient of determination (R2) validation measurements on soil reports dataset. The results provide a comparison of solution classes and conclude that the SGD outperforms other approaches. Finally, the proposed results support to select the solution or recommend a class which suggests suitable fertilizer to crops for maximum production
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