Asian Indian Perceptions of Normality: A Qualitative Study

Normal mental health has always been defined from a Euro-centric worldview that excludes non-Westem cultures. In fact, what is normal is biased against non-Westem cultural ideals that influenced the definition of mental health. The difference between Eastern and Western cultural values suggest that the two cultures may also have differing views on the definition of normal mental health. The most commonly accepted definition of normality currently in use in the West is based on the models of health, utopia, average, transactional systems, and pragmatism. However, people from non-European cultures, such as Asian Indians, may not be represented by these current parameters of mental health and illness. In this study, the construct of normality was investigated from an Asian Indian perspective. Specifically, interviews were conducted with Asian Indian graduate students in which participants were asked to discuss their perceptions of normal mental health. A Consensual Qualitative Research analysis strategy was then conducted. Five domains were created: Perceptions of Normal, Perceptions of Abnormal, Cause of Mental Illness, Criteria Used to Differentiate Normal from Abnormal, and Difficulties in Defining Normal. The categories within these domains were discussed as they related to psychological treatment services for international students such as well as implications for future research

Exploiting Data Mining Techniques For Improving the Efficiency of Time Series Data

The research work in data mining has achieved a high attraction due to the importance of its applications This paper addresses some theoretical and practical aspects on Exploiting Data Mining Techniques for Improving the Efficiency of Time Series Data using SPSS-CLEMENTINE. This paper can be helpful for an organization or individual when choosing proper software to meet their mining needs. In this paper, we propose utilizes the famous data mining software SPSS Clementine to mine the factors that affect information from various vantage points and analyse that information. However the purpose of this paper is to review the selected software for data mining for improving efficiency of time series data. Data mining techniques is the exploration and analysis of data in order to discover useful information from huge databases. So it is used to analyse a large audit data efficiently for Improving the Efficiency of Time Series Data. SPSS- Clementine is object-oriented, extended module interface, which allows users to add their own algorithms and utilities to Clementine’s visual programming environment. The overall objective of this research is to develop high performance data mining algorithms and tools that will provide support required to analyse the massive data sets generated by various processes that is used for predicting time series data using SPSS- Clementine. The aim of this paper is to determine the feasibility and effectiveness of data mining techniques in time series data and produce solutions for this purpose

Space-efficient Feature Maps for String Alignment Kernels

String kernels are attractive data analysis tools for analyzing string data. Among them, alignment kernels are known for their high prediction accuracies in string classifications when tested in combination with SVM in various applications. However, alignment kernels have a crucial drawback in that they scale poorly due to their quadratic computation complexity in the number of input strings, which limits large-scale applications in practice. We address this need by presenting the first approximation for string alignment kernels, which we call space-efficient feature maps for edit distance with moves (SFMEDM), by leveraging a metric embedding named edit sensitive parsing (ESP) and feature maps (FMs) of random Fourier features (RFFs) for large-scale string analyses. The original FMs for RFFs consume a huge amount of memory proportional to the dimension d of input vectors and the dimension D of output vectors, which prohibits its large-scale applications. We present novel space-efficient feature maps (SFMs) of RFFs for a space reduction from O(dD) of the original FMs to O(d) of SFMs with a theoretical guarantee with respect to concentration bounds. We experimentally test SFMEDM on its ability to learn SVM for large-scale string classifications with various massive string data, and we demonstrate the superior performance of SFMEDM with respect to prediction accuracy, scalability and computation efficiency.Comment: Full version for ICDM'19 pape

Multidetector CT arthrography in shoulder instability and its comparison with MR arthrography and arthroscopy

Background: Purpose of this study was to compare diagnostic effectiveness of MDCT arthrography (MDCTA) in shoulder instability and pain in throwing and its comparison to MR arthrography (MRA) and arthroscopy taking arthroscopy as gold standard.Methods: 20 patients with history of recurrent shoulder dislocation in activity were included in this study. After detailed clinical examination, each patient underwent MDCT-MR arthrography in one sitting followed by diagnostic arthroscopy within 6 weeks. Results were compared with the help of statistician.Results: At arthroscopy, 10 Bankart’s lesions, 7 Hill Sachs lesion, 6 SLAP lesion, 1 ALPSA, 1 capsular laxity, 1 partial subscapularis tear and 1 supraspinatus fraying were visualized in 20 shoulders. For Bankart’s lesion MDCT has sensitivity 80%, specificity 100%, positive predictive value (PPV) 100% and negative predictive value (NPV) 83.3%. MRA has sensitivity of 90%, specificity 100%, PPV 100% and NPV 90.9%. For SLAP lesions sensitivity, specificity, PPV and NPV for MDCTA and MRA are 88.3%, 100%, 100%, 93.3%. For Hill-Sachs lesion; sensitivity, specificity, PPV and NPV for MDCTA are all 100% and for MRA they are 85.7%, 100%, 100%, 92.8% respectively. For ALPSA; sensitivity is 100%, specificity is 95%, PPV is 50% and NPV is 100% both for MDCTA and MRA. К value for MRA is 0.60 and for CTA is 0.55 suggesting moderate agreement.Conclusions: Considering availability, cost, time consumption, superior detection of bony lesions and comparable detection of soft tissue lesions; MDCTA can be used as single investigation of choice in shoulder instability pain

Synthesis of 2-(substituted aryl)-3-(N9-carbazolylacetamidyl)-4-oxothiazolidines and their 5-arylidine derivatives as antifungal agents

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