190,157 research outputs found
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe 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
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
-supercontinuous functions
No full textsummary:A new class of functions called “-supercontinuous functions” is introduced. Their basic properties are studied and their place in the hierarchy of strong variants of continuity that already exist in the literature is elaborated. The class of -supercontinuous functions properly includes the class of -supercontinuous functions, Tyagi, Kohli, Singh (2013), which in its turn contains the class of -supercontinuous ( clopen continuous) functions, Singh (2007), Reilly, Vamanamurthy (1983), and is strictly contained in the class of -supercontinuous, Kohli, Tyagi, Singh, Aggarwal (2014), which in its turn is properly contained in the class of -supercontinuous functions, Kohli, Singh, Aggarwal (2010)
Economic impacts of SEZs: Theoretical approaches and analysis of newly notified SEZs in India
No full textThis 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
Novel Polypseudorotaxanes Hydrogel based Nail Lacquer of Efinaconazole for Transungual Drug Delivery
No full textResearch dat
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe 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
Extracting knowledge from big data for sustainability: A comparison of machine learning techniques
No full textAt 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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