Passivity-Based Decentralized Criteria for Small-Signal Stability of Power Systems with Converter-Interfaced Generation

With the increasing penetration of converter-interfaced distributed generation systems, it would be advantageous to specify local compliance criteria for these devices to ensure the small-signal stability of the interconnected system. Passivity of the device admittance, which is an example of a local criterion, has been used previously to avoid resonances between these devices and the lightly damped oscillatory modes of the network. Typical active and reactive power control strategies like droop control and virtual synchronous generator control inherently violate the passivity constraints on admittance at low frequencies, although this does not necessarily mean that the interconnected system will be unstable. Therefore, passivity of the admittance is unsuitable as a stability criterion for devices that are represented by their wide-band models. To overcome this problem, this paper proposes the use of criteria based on admittance at higher frequencies and an alternative transfer function at lower frequencies. The alternative representation uses active and reactive power and the derivatives of the polar components of voltage as interface variables. To allow for the separate analysis at low and high frequencies, the device dynamics should exhibit a slow-fast separation; this is proposed as an additional constraint. Adherence to the proposed criteria is not onerous and is easily verifiable through frequency response analysis

Capturing user sentiments for online Indian movie reviews.

Sentiment analysis and opinion mining are emerging areas of research for analysing Web data and capturing users’ sentiments. This research aims to present sentiment analysis of an Indian movie review corpus using natural language processing and various machine learning classifiers. In this paper, a comparative study between three machine learning classifiers (Bayesian, naïve Bayesian and support vector machine [SVM]) was performed. All the classifiers were trained on the words/features of the corpus extracted, using five different feature selection algorithms (Chi-square, info-gain, gain ratio, one-R and relief-F [RF] attributes), and a comparative study was performed between them. The classifiers and feature selection approaches were evaluated using different metrics (F-value, false-positive [FP] rate and training time).The results of this study show that, for the maximum number of features, the RF feature selection approach was found to be the best, with better F-values, a low FP rate and less time needed to train the classifiers, whereas for the least number of features, one-R was better than RF. When the evaluation was performed for machine learning classifiers, SVM was found to be superior, although the Bayesian classifier was comparable with SVM. This is a novel research where Indian review data were collected and then a classification model for sentiment polarity (positive/negative) was constructed.N

Clinico-biochemical correlation between psoriasis and lipid profile

Background: Psoriasis is an autoimmune disorder associated with alteration of different metabolism. The present study was aimed to assess the lipid metabolism and its correlation with severity of disease and associated cardiovascular risk factors in psoriasis.Methods: Study comprises total of 60 cases of psoriasis attended the dermatology clinics at Maharaja Yashwant Rao hospital, Indore, Madhya Pradesh, India and 30 age, gender matched healthy controls. Subjects were enrolled in the study as per the inclusion criteria. Severity of the disease was assessed by PASI score. Fasting blood samples were collected and evaluated for Lipid profile and risk ratio was calculated.Results: The results indicated that serum total cholesterol, triglycerides, LDL-C,VLDL-C were significantly increased in moderate to severe cases in comparison to control and level of HDL-C significantly decreased in moderate psoriasis and highly significant decreased was observed in severe cases when compared to control. Serum triglyceride (TG), total cholesterol, low density lipoprotein showed a significant positive correlation with severity of psoriasis. Study concludes that lipid derangement correlate with the severity of disease and also acts as a good prognostic sign.  Conclusions: Present study concludes that psoriatic patients should be evaluated and followed up for the risk of dyslipidemia and cardiovascular morbidity

Hypoadiponectinemia is associated with increased insulin resistance, dyslipidemia and presence of type 2 diabetes in non obese central Indian population

Background: Accumulating evidence suggests that adiponectin, a major adipocyte secretory protein, has insulin-sensitizing and anti-atherogenic properties and protects against later development of type 2 diabetes. We investigated the association of adiponectin with insulin resistance, blood lipids and type 2 diabetes in non obese central Indian population.Methods: Anthropometric and biochemical parameters were measured in 149 (81 male and 68 female) newly diagnosed non obese type 2 diabetic patients and 157 (85 male and 72 female) age and body mass index (BMI) matched controls.Results: Adiponectin level (p<0.0001) was significantly lower in the diabetic group than in non diabetic control. In an age, gender and BMI adjusted model, adiponectin level was significantly negatively correlated with waist circumference, waist to hip ratio, systolic blood pressure, fasting insulin, homeostasis model assessment-insulin resistance (HOMA-IR) (p= 0.0034), HbA1C, total cholesterol, LDL-cholesterol, and triglycerides (p<0.0001) and positively correlated with HDL-cholesterol (p =0.0014) in non obese type 2 diabetic group. However, there was no significant correlation between adiponectin and glucose in this study. In stepwise linear regression analysis, adjusted for potential confounder, significant inverse association was observed between serum adiponectin level and HOMA-IR (p = 0.0001). In multivariate logistic regression model, adjusted for age, gender, BMI, waist circumference, and waist-hip ratio, lower adiponectin was independently associated with the presence of type 2 diabetes (p<0.0001).Conclusions: Lower adiponectin levels in non obese type 2 diabetic patients were significantly related to the increased insulin resistance, dyslipidemia, and presence of type 2 diabetes, independently of overall and abdominal adiposity, thereby suggesting a direct link between adiponectin and carbohydrate and lipid metabolism in human

Laboratory instructions as a cause of student dissonance

Improving the quality of education is the goal of all pedagogical research. By using student surveys and course evaluations problem areas can be identified in most courses offered by universities. In this paper we perform a large-scale student survey in order to find the causes of, and remedies to, a widespread student dissonance in a mandatory course with over 100 students at Lund University. Our research shows that aiming for deeper learning, without providing time and a stimulating environment, can be worse than settling for expository learning. This problem has persisted for years despite attempts by the course administrators to solve the problem. We propose that major improvements can be achieved, both in learning and pass rates, primarily by improving the lab instructions but also by using a more intellectually stimulating lab equipment

Low-frequency noise in vertical InAs nanowire FETs

This letter presents dc characteristics and low-frequency noise (LFN) measurements on single vertical InAs nanowire MOSFETs with 35-nm gate length and HfO2 high-kappa dielectric. The average normalized transconductance for three devices is 0.16 S/mm, with a subthreshold slope of 130 mV/decade. At 10 Hz, the normalized noise power S-I/I-d(2) measures 7.3 x 10(-7) Hz(-1). Moreover, the material-dependent Hooge's parameter at room temperature is estimated to be 4.2 x 10(-3)