Prevalence of nonalcoholic fatty liver disease and metabolic syndrome in psoriasis in a tertiary health center.

Psoriasis vulgaris is a common dermatological condition, worldwide, with a higher prevalence of 0.8-5.6% India. Psoriasis is not just skin deep, and psoriasis patients suffer with many systemic illness directly or indirectly. AIMS AND OBJECTIVES: To study the prevalence of nonalcoholic fatty liver disease and metabolic syndrome in psoriasis in south Indian population and to correlate the severity of psoriasis with the prevalence of NAFLD . MATERIALS AND METHODS: Ours is a cross sectional study 6 months, with 165 psoriasis patients. Psoriasis patients on hepatotoxic drugs, significant alcohol use are excluded from the study. After clinical history and examination all the patients are subjected to battery of investigations including ultrasonography. 1. Post Graduate, Institute of Internal Medicine, RGGGH, Chennai. 2. Professor of Medicine, Institute of Internal Medicine, RGGGH, Chennai. 3. Head of Department, Department of Hepatology, RGGGH, Chennai. RESULTS: The prevalence of NAFLD and metabolic syndrome among psoriasis in our study is 75(45.5%) and 27(16%) respectively. All other components of metabolic syndrome are also increased in our study. There is no association of NAFLD with severity of psoriasis. Patients with psoriasis and metabolic syndrome had significant dyslipidemia. CONCLUSION: There is a significant association between psoriasis and metabolic syndrome and NAFLD. Psoriasis is independently associated with NAFLD

Open Issues, Research Challenges, and Survey on Education Sector in India and Exploring Machine Learning Algorithm to Mitigate These Challenges

The nation's core sector is education. But dealing with problems in educational institutions, particularly in higher education, is a challenging task. The growth of education and technology has led to a number of research challenges that have attracted significant attention as well as a notable increase in the amount of data available in academic databases. Higher education institutions today are worried about outcome-based education and various techniques to assess a student's knowledge level or capacity for learning. In general, there are more contributors in the academic field than there are authors. Research is being done in this field to determine the best algorithm and features that are crucial for predicting the future outcomes. This survey can help educational institutions assess themselves and find any gaps that need to be filled in order to fulfil their purpose and vision. Machine Learning (ML) approaches have been explored to solve the issues as higher education systems have grown in size

Energy Meter Data Analysis Using Machine Learning Techniques

With the advancement of technology, existence of energy meters are not merely to measure energy units. The proliferation of energy meter deployments had led to significant interest in analyzing the energy usage by the machines. Energy meter data is often difficult to analyzeowing to the aggregation of many disparate and complex loads. At utility scales, analysis is further complicated by the vast quantity of data and hence industries turn towards applying machine learning techniques for monitoring and measuring loads of the machines. The energy meter data analysis aims at analyzing the behavior of the machine and providing insights on usage of the energy. This will help the industries to identify the faults in the machine and to rectify it.Two use cases with two different motor specifications is considered for evaluation and the efficiency is proved by considering accuracy, precision, F-measure and recall as metrics

Vibrational, electrical, dielectric and optical properties of PVA-LiPF6 solid polymer electrolytes

Solid polymer electrolytes based on polyvinyl alcohol (PVA) doped with LiPF6 have been prepared using solution casting technique. Electrical properties of prepared electrolyte films were analyzed using AC impedance spectroscopy. The ionic conductivity was found to increase with increasing salt concentration. The maximum conductivity of 8.94 × 10−3 S·cm−1 was obtained at ambient temperature for the film containing 20 mol% of LiPF6. The conductivity enhancement was correlated to the enhancement of available charge carriers. The formation of a complex between the polymer and salt was confirmed by Fourier transform infrared spectroscopy (FT-IR). The optical nature of the polymer electrolyte films was analyzed through UV-Vis spectroscopy

SIFT and SURF Features Based Classification of Yoga Hand Mudras Using Machine Learning Techniques

Yoga is an unique spiritual discipline of self-development and self-realization that teaches us how to live our lives to the fullest. Yoga's integrative approach brings deep harmony and unwavering balance to body and mind to awaken our dormant capacity for higher consciousness, which is the true purpose of human evolution. The numerous documented physical and mental benefits of yoga have played a large part in the interest in yoga. Due to a lack of datasets and thus the necessity to identify mudra in real time, distinguishing yoga hand mudras seems to be a tough undertaking. The yoga hand mudras are used as input in the proposed study, and the two components Scale Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF) are extracted, followed by classification utilising machine learning techniques including Support Vector Machine (SVM) and Random Forest. By comparing the experimental results the performance of SIFT with SVM yields better results

SOFT-SWITCHING CURRENT-FED PUSH-PULL CONVERTER FOR PV APPLICATION

ABSTRACT In this paper, a soft switching single-inductor push-pull converter is discussed. A push-pull converter is suitable for low voltage photovoltaic applications, because the step up ratio of high frequency transformer is high. Photovoltaic is considered to be a popular source of renewable energy due to several advantages, specifically low operational cost, and maintenance free and environmental friendly. In the conventional converter, primary switches are turned ON at the zero voltage switching condition and turned off at zero current switching condition through parallel resonance between the secondary leakage inductance of a transformer and resonant capacitor. The proposed push-pull converter also decreases the switching loss using soft switching of the primary switching. The boost rectifier added reduces the turn's ratio of the transformer further when compared to the voltage doubler

SIFT and SURF features based classification of yoga hand mudras using machine learning techniques

Yoga is an unique spiritual discipline of self-development and self-realization that teaches us how to live our lives to the fullest. Yoga's integrative approach brings deep harmony and unwavering balance to body and mind to awaken our dormant capacity for higher consciousness, which is the true purpose of human evolution. The numerous documented physical and mental benefits of yoga have played a large part in the interest in yoga. Due to a lack of datasets and thus the necessity to identify mudra in real time, distinguishing yoga hand mudras seems to be a tough undertaking. The yoga hand mudras are used as input in the proposed study, and the two components Scale Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF) are extracted, followed by classification utilising machine learning techniques including Support Vector Machine (SVM) and Random Forest. By comparing the experimental results the performance of SIFT with SVM yields better results

EVALUATION OF COMPUTABILITY CRITERIONS FOR RUNTIME WEB SERVICE INTEGRATION

ABSTRAC