A proposed secure multiple watermarking technique based on DWT,DCT and SVD for application in medicine

Multimedia Tools and Applications - In this paper, an algorithm for multiple watermarking based on discrete wavelet transforms (DWT), discrete cosine transform (DCT) and singular value...     

Reducing code wastage in orthogonal variable spreading factor‐based wideband code division multiple access networks

Most third‐generation and beyond wideband code division multiple access networks use the orthogonal variable spreading factor code tree for channelization codes. The codes in this code tree are limited and the performance of a wireless network depends upon the code assignment for new calls. In this paper, we introduce a term called ‘wastage capacity’, which gives us the amount of wastage caused when a code (single or multiple) with a data rate higher than the rate of the incoming call is assigned to it. We suggest two methods to keep wastage capacity below an arbitrary threshold value or zero. In the first method, we devised an algorithm in which wastage up to a certain threshold would be tolerated and the minimum rakes to get this wastage capacity were identified. In the second approach, we reduced the wastage capacity to zero irrespective of the number of rakes at the expense of higher cost and complexity. Copyright © 2011 John Wiley & Sons, Ltd.     

Public perception of stroke warning signs and knowledge of potential risk factors

CONTEXT: Decreasing the time from stroke onset to hospital arrival and improving control of stroke risk factors depend on public knowledge of stroke warning signs and risk factors. OBJECTIVE: To assess current public knowledge of stroke warning signs and risk factors. DESIGN: A population-based telephone interview survey using random digit dialing conducted in 1995. SETTING: The Greater Cincinnati, Ohio, metropolitan area, the population of which is similar to that of the United States overall in age, sex, percentage of blacks, and economic status. PARTICIPANTS: Respondents with age, race, and sex that matched the population of patients with acute stroke. MAIN OUTCOME MEASURES: Knowledge of risk factors for stroke and warning signs of stroke as defined by the National Institute of Neurological Disorders and Stroke. RESULTS: Telephone calls were made to 17634 households, which yielded 2642 demographically eligible individuals. Interviews were completed by 1880 respondents (response rate, 71.2%). A total of 1066 respondents (57%) correctly listed at least 1 of the 5 established stroke warning signs, and of all respondents, 1274 (68%) correctly listed at least 1 of the established stroke risk factors. Of the respondents, 469 (57%) of 818 respondents with a history of hypertension listed hypertension, 142 (35%) of 402 respondents who were current smokers listed smoking, and 32 (13%) of 255 respondents with diabetes listed diabetes as a risk factor for stroke. Compared with those younger than 75 years, respondents 75 years or older were less likely to correctly list at least 1 stroke warning sign (60% vs 47%, respectively; P<.001) and were less likely to list at least 1 stroke risk factor (72% vs 56%, respectively; P<.001). CONCLUSION: Considerable education is needed to increase the public's awareness of the warning signs and risk factors for stroke. Respondents with self-reported risk factors for stroke are largely unaware of their increased risk. The population at greatest risk for stroke, the very elderly, are the least knowledgeable about stroke warning signs and risk factors.     

Wind Energy Conversion Systems as a Distributed Source of Generation

As a result of the worldwide energy crisis, research and development activities in the field of wind energy have been gaining momentum for the last few years in many countries. Although this technology has been greatly improved during that time, the available technical know-how is not yet adequate to develop reliable wind energy converting systems for Indian conditions at low wind speeds. In spite of a few indigenous efforts, the developments of wind energy converting systems working at low wind speeds of 2–5 m/s, which is available for a considerable period of the year in the major part of the country, remain unfulfilled. This issue continues to be a matter of great concern for the Indian researchers. This paper introduces a new concept of amplifying the wind speed before it comes in contact with the rotor blades of a Savonius turbine by using a convergent nozzle. This novel work emphasizes the improvement of the efficiency of Savonius rotors, which normally extract less than 25% of the power in the wind and have been commercially unsuccessful. A research program involving wind tunnel tests of five different nozzle models has been conducted. Some necessary modifications in the design of the turbine have been suggested and verified practically with the help of working models. Analysis of different nozzle dimensions has also been outlined. The variation of the output speed with different values of input wind speed and different lengths placed at different distances from the wind tunnel are presented in the paper.     

Introducing Locality and Softness in Subspace Classification

Subspace classifiers classify a pattern based on its distance from different vector subspaces. Earlier models of subspace classification were based on the assumption that individual classes lie in unique subspaces. In later extensions, locality was introduced into subspace classification allowing for a class to be associated with more than one sub manifold. The local subspace classifier is thus a piecewise linear classifier, and is more powerful when compared to the linear classification performed by global subspace methods. We present extensions to the basic subspace method of classification based on introducing locality and softness in the classification process. Locality is introduced by (subspace) clustering the patterns into clusters, and softness is introduced by allowing a pattern to be associated with more than one cluster. Our motivation for introducing both locality and softness is based on the premise that by introducing locality, it is possible to reduce the bias though at the cost of a possible increase in variance. By introducing softness (or aggregation), the variance can be reduced. Consequently, by introducing both locality and softness, we avoid the possibility of high variance that locality typically introduces. We derive appropriate algorithms to construct a local and soft model of subspace classifiers and present results obtained with the proposed algorithm. Received: 4 November 1998?Received in revised form: 7 December 1998?Accepted: 7 December 1998     

Failure Model for Rate-Dependent Polymer Matrix Composite Laminates under High-Velocity Impact

A modified Hashin failure model is developed to characterize different failure modes related to high-velocity impact of composite laminates. Hashin’s compressive fiber failure mode has been extended to consider the shear stress effect. Several micromechanics-based degradation rules are developed and applied to the stress and material property calculations according to different failure modes after the corresponding failure criterion is satisfied. This model has been implemented into a recently developed micromechanics model. Computational results show that this model is able to address shear failure, delamination, and tearing failure observed in the high-velocity impact of composite laminates.     

An efficient statistical approach for time synchronization in wireless sensor networks

In this paper, we propose a powerful method of estimating the model parameters for time synchronization in wireless sensor networks (WSNs). Joint estimation of clock offset and clock skew has been proposed in the literature using the standard regression framework. Here, we claim that simple regression poorly estimates the parameters because of the inherent correlation among successive time readings between two sensors. We propose an alternative autoregressive model and use generalized least squares for estimating the relative offset and skew parameters. A computationally efficient Bayesian approach is also proposed for the parameter estimation considering correlated readings between two sensors. The effectiveness of the proposed approach compared with the earlier approach has been investigated through extensive simulation studies. Copyright © 2015 John Wiley & Sons, Ltd.     

Prediction of thermal resistance of woven fabrics. Part II: Heat transfer in natural and forced convective environments

The aim of the paper is to observe the effects of convection on the total heat transfer of the fabric. Convective heat transfer through textiles can be simulated with the help of computational fluid dynamics (CFD). The first part of this paper has dealt with the mathematical model for predicting the conductive and radiative heat transfer. The second part of the paper describes the use of CFD to simulate the wind tunnel of the instrument. The fabric has been subjected to natural and forced convection. The convective heat transfer coefficients obtained from the simulation were used to find the resistance due to convection. The final values obtained from the model were compared with the values obtained from the thermal resistance measuring instrument fabricated to measure the thermal resistance in natural and forced convective modes. The mathematical model gave excellent prediction in forced as well as natural convective mode when coupled with CFD results.     

Yield and nutritional content of Pleurotus sajor caju on wheat straw supplemented with raw and detoxified mahua cake

The effect of supplementation of wheat straw (WS) with raw/detoxified mahua cake (MC) on yield and nutritional quality of Pleurotus sajor caju was studied. Raw cake significantly enhanced the yield compared to control and could be tolerated up to a 10% addition. Detoxification further improved the mushroom yield giving a maximum of 1024.7 g kg⁻¹ from WS supplemented with 20% saponin free detoxified mahua cake. Chemical analysis of fruit bodies revealed that they are rich in proteins (27.4–34.8%), soluble sugars (28.6–32.2%) and minerals. Glucose, trehalose and glutamic acid, alanine were the major sugars and amino acids detected by HPLC analysis, respectively. HPLC studies further confirmed the absence of saponins (characteristic toxins present in MC) in both fruit bodies and spent. Degradation of complex molecules in spent was monitored via FTIR. The study proved beneficial for effective management of agricultural wastes along with production of nutrient rich and saponin free fruit bodies/spent.