Analysis of an unswept propfan blade with a semiempirical dynamic stall model

The time history response of a propfan wind tunnel model with dynamic stall is studied analytically. The response obtained from the analysis is compared with available experimental data. The governing equations of motion are formulated in terms of blade normal modes which are calculated using the COSMIC-NASTRAN computer code. The response analysis considered the blade plunging and pitching motions. The lift, drag and moment coefficients for angles of attack below the static stall angle are obtained from a quasi-steady theory. For angles above static stall angles, a semiempirical dynamic stall model based on a correction to angle of attack is used to obtain lift, drag and moment coefficients. Using these coefficients, the aerodynamic forces are calculated at a selected number of strips, and integrated to obtain the total generalized forces. The combined momentum-blade element theory is used to calculate the induced velocity. The semiempirical stall model predicted a limit cycle oscillation near the setting angle at which large vibratory stresses were observed in an experiment. The predicted mode and frequency of oscillation also agreed with those measured in the experiment near the setting angle

Early Detection and Prevention of Lungs Cancer using Artificial Neural Network

Out of the dangerous diseases, cancer being one of the cause of death and it can be avoided if correctly detected in the early stage. The possibilities of survival will be increased if predicted and cured at early stage. To predict accurately and to provide best diagnosis, many mechanisms are developed in the field of Artificial Intelligence and machine learning. This paper provides a systematic review of different machine learning algorithms like Artificial Neural Network (ANN), Decision Trees (DT), Support Vector Machine (SVM), Random Forest (RF), Voting Classifier and Bayesian Network (BN). Survey also shows that ANN and SVM are preferred by researchers to develop the predictive models

An Efficient Cross-Domain Recommendation Technique in Cold-Start Situations

Most of the recent studies on recommender systems are focused on single domain recommendation systems. In the single domain recommendation systems, the items that are used for training and test data set are belongs to within the same domain. Cross-site domains or item recommendations in multi-domain environment are available in Amazon i.e. it incorporate two or more domains. Few research studies are done on the cross-site recommendation systems. Cross-site recommendations provide the relationship between the two sets of items from various domains. They can provide the extra information about the users of a target domain and recommendations will be done based on that. In this paper, we will study cross-site recommendation model on the cold start situation, where the purchase history is not available for the new user. Cold-start is the well-known issue in the area of recommendation systems. It seriously affect the recommendations in the collaborative filtering approaches. In this paper, we propose a new solution to recommend products from e-commerce websites to users at social networking sites. a noteworthy issue is how to leverage knowledge from social networking websites when there is no purchase history for a customer especially in cold start situations.in particular we proposed the solution for cold start recommendation by linking the users across social networking sites and e-commerce websites i.e. customers who have social network identities and have purchased on e-commerce websites as a bridge to map user’s social networking features in to another feature representation which can be easier for product recommendation. Here we propose to learn by using recurrent neural networks both user’s and product’s feature representations called user embedding and product embedding from the data collected from e-commerce website and then apply a modified gradient boosting trees method to transform user’s social networking features in to user embedding. Once found, then develop a feature-based matrix factorization approach which can leverage the learnt user embedding for the cold-start product recommendation. Experimental results shows that our approach effectively works and gives the best recommended results in cold start situations

Influence of Polymer Restraint on Ballistic Performanceof Alumina Ceramic Tiles

An experimental study has been carried out to evaluate the influence of confinement ofalumina ceramic tiles through polymer restraint, on its ballistic performance. Tiles of 99.5 per centpurity alumina were subjected to ballistic impact against 7.62 mm armour piercing projectiles atvelocities of about 820 m/s. The tiles of size 75 mm x 75 mm x 7 mm were confined on both facesby effectively bonding varying numbers of layers of polymer fabrics. These were then bondedto a 10 mm thick fibre glass laminate as a backing using epoxy resin. High performance polyethyleneand aramid polymer fabrics were used in the current set of experiments for restraining the tiles.Comparative effects of confinement on energy absorption of tiles with varied number of layersof fabrics were evaluated. It was observed that by providing effective confinement to the tile,energy absorption could be doubled with increase in areal density by about 13 per cent.Photographs of the damage and the effects of restraint on improvement in energy absorptionof ceramic tiles are presented and discussed

Bulk viscosity in hyperonic star and r-mode instability

We consider a rotating neutron star with the presence of hyperons in its core, using an equation of state in an effective chiral model within the relativistic mean field approximation. We calculate the hyperonic bulk viscosity coefficient due to nonleptonic weak interactions. By estimating the damping timescales of the dissipative processes, we investigate its role in the suppression of gravitationally driven instabilities in the $r$-mode. We observe that $r$-mode instability remains very much significant for hyperon core temperature of around $10^8$K, resulting in a comparatively larger instability window. We find that such instability can reduce the angular velocity of the rapidly rotating star considerably upto $\sim0.04 \Omega_K$, with $\Omega_K$ as the Keplerian angular velocity.Comment: 10 pages including 7 figure

Chemical Constituents during the Main and Off-Season in Mango (Mangifera indica L.) Cv. Royal Special

Evaluation and quantification of fruit quality parameters like carbohydrates, phenolics, flavonoids, ascorbic acid, titrable acidity, Total Soluble Solids (TSS), carotenoids and lycopene content was done in fruits of mango cv. Royal Special, at ICAR-Indian Institute of Horticultural Research, Bengaluru, India, during the off-season (October, 2012) and main-season (June, 2013), respectively. 'Royal Special' is a typical off-season bearing cultivar, often characterized by multiple flushing and flowering under South Indian conditions. Major phytonutrients such as total sugars, reducing sugars, starch, total carotenoids, lycopene, total phenols, flavonoids, ascorbic acid, TSS, titrable acidity and average fruit yield per plant, were recorded during the off- and main- seasons. Results indicated that fruits from off-season were higher in the major chemical constituents studied compared to the main-season crop, except for fruit yield per plant. This may be attributed to poor competition for nutrients among the developing fruits which act as a sink, besides fluctuating environmental conditions during the off-season, compared to the main-season

Reversal of hepatorenal syndrome type 1 with terlipressin plus albumin vs. placebo plus albumin in a pooled analysis of the OT-0401 and REVERSE randomised clinical studies

Background The goal of hepatorenal syndrome type 1 (HRS-1) treatment is to improve renal function. Terlipressin, a synthetic vasopressin analogue, is a systemic vasoconstrictor used for the treatment of HRS-1, where it is available. Aim To compare the efficacy of terlipressin plus albumin vs. placebo plus albumin in patients with HRS-1. Methods Pooled patient-level data from two large phase 3, randomised, placebo-controlled studies were analysed for HRS reversal [serum creatinine (SCr) value ≤133 μmol/L], 90-day survival, need for renal replacement therapy and predictors of HRS reversal. Patients received intravenous terlipressin 1–2 mg every 6 hours plus albumin or placebo plus albumin up to 14 days. Results The pooled analysis comprised 308 patients (terlipressin: n = 153; placebo: n = 155). HRS reversal was significantly more frequent with terlipressin vs. placebo (27% vs. 14%; P = 0.004). Terlipressin was associated with a more significant improvement in renal function from baseline until end of treatment, with a mean between-group difference in SCr concentration of −53.0 μmol/L (P \u3c 0.0001). Lower SCr, lower mean arterial pressure and lower total bilirubin and absence of known precipitating factors for HRS were independent predictors of HRS reversal and longer survival in terlipressin-treated patients. Conclusions Terlipressin plus albumin resulted in a significantly higher rate of HRS reversal vs. albumin alone in patients with HRS-1. Terlipressin treatment is associated with improved renal function

Solar and Dynamo Powered Ev Using Fingerprint Authentication

Nonrenewable energy sources are already interfering with the availability of electricity. Today, the primary emphasis is on the generation of electricity from renewable sources. This proposal proposes a feasible design solution in the shape of a user-friendly three-wheeler. A fingerprint-accessible electric vehicle. This electric vehicle uses solar power and a self-changing dynamo to charge its battery. The battery serves as the vehicle's power source. A microcontroller serves as the system's primary controller. It is connected to a fingerprint module, a relay, the car ignition, and an LCD. The Microcontroller reads the input from the fingerprint module and, if it is legitimate, grants access to the ignition system. The status will be displayed on the LCD. In addition, we're adding three more sensors: speed, temperature, and voltage. Lithium-ion batteries can be harmful if not used within the safety-operated area (SOA). To avoid this, we calculate the temperature of the lithium-ion battery when it exceeds 49.9?. It will make a sound through the buzzer. This can prevent damage to the battery and the person driving the vehicle. Voltage Sensor is designed to monitor battery charging and discharging time, which is displayed on the LCD. A speed sensor is used to determine the speed of the vehicle