Archives-September 2011

To evaluate the effectiveness and clinical significance of pattern visual evoked potential (P-VEP) as a predictor of occlusion therapy for patients with strabismic and amblyopia(squint eye).Methods: A total of 34 consecutive children with anisometropic squint were included in this study. All patients underwent a full initial ophthalmologic and orthoptic evaluation. P-VEP test was performed in all cases and binocular vision was tested and recorded Part-time occlusion therapy was performed by using adhesive patches. Results: The mean (±SEM) cycloplegic refractive error was +5.6 ± 0.6 diopters (D) in the squint eyes and +1.8 ± 0.2 D in the normal eye. The mean levels of best-corrected visual acuity were statistically differed between each measurement for occlusion therapy (for each, p < 0.05). The ratio of the patients with binocular vision increased after 6 months occlusion therapy and the difference was statistically significant (p<0.05). In addition, P100 amplitude improved at each visit and the difference was significant when compared with baseline values (for each, p < 0.05). Conclusions: P100 amplitude of the P-VEP test parallels the improvement in subjective visual acuity in squint eyes under occlusion therapy. Therefore, this test may be useful in monitoring the visual acuity in the preverbal or non-verbal patched patients.

Geospatial information gathered through different sensors and geographic objects is generally indistinct, vague and uncertain. The ambiguity turns out to be obvious due to the multi-granular formation of the multisensory satellite images and that directs to error accumulation at every stage. The main aim of this paper is to compare the K-Means and Fuzzy C-Means classification algorithm and find out the change detection in glacier classification by processing images taken over different time frames. The LANDSAT images correspond to the Himachal Pradesh region, one dated June 2005 and the other dated June 2010. To estimate the quality of remote sensing data the non-linear objective assessment parameters are used. Though the classification of glacier cover calculation, by improving the accurate geological classification, might be in a crude form but when projected on a larger scale, it can act as a great tool for research and analysis on a particular geographical location. The environment related bodies around the globe are deeply benefited from the valuable images provided by satellite imagery and their analysis help strategize different methods for environment protection in general and curb global warming in specific.

Fingerprint recognition is one of the most prominent biometric identification techniques. The features of fingerprint are broadly classified into three categories namely level 1, level 2 and level 3 features. In order to increase the recognition rate here the hierarchical matching technique is used which allows us to use all levels of features hierarchically. The level 3 features can be observed only in 1000 dpi images. So the matching is performed on a 1000 dpi fingerprint database captured using Hamster IV fingerprint scanner. At the first level of hierarchical matching the agreement between two orientation images is tested using dot product of the images. If an image is accepted at the first level it is brought to the second level of matching where minutiae details are tested. If an image crosses this stage as accepted then the decision will be taken as genuine otherwise the image will be given to the third level. The third level extracts the level 3 features such as pores and ridge contour points using Dynamic Anisotropic Pore Model (DAPM) and Mexican hat wavelet transform respectively. For each matched minutiae the pores and ridge contour points within the associated region of that minutiae will be matched. Based on the third level of matching a person is accepted as genuine or rejected as imposter.

Security threats for the network services have been constantly increasing day by day. Distributed denial of service (DDoS) attack is one such kind of security threat which involves multiple systems generating a large amount of traffic towards a target machine and thereby making any service from that target machine or server unavailable to its clients. This threat by nature needs no control over the target system. Traditional methods of detecting DDoS attacks are mostly centralized in nature and highly disadvantageous. To overcome the disadvantages of those schemes, we propose a distributed methodology which involves installing the attack detectors at various parts of the network. Each router in the network will monitor the traffic flowing through it and if any anomaly in the traffic pattern is detected, it will raise an alarm to the nearby routers. The alarm propagates to all the routers through which the attack flows. By this way a tree like construct is made, which will have information about number of alarms raised and the path of the attack flow. If the construct shows any converging pattern then it is declared as DDoS attack.

The present study describes degradation of Lacosamide under various conditions like, oxidation, hydrolysis, and thermal stress conditions. The drug was found to hydrolyse in acidic and alkaline conditions and no degradation was found in thermal stress condition and oxidation. The separation of the drug and degradation product was successfully achieved on a C18 column utilizing water (0.1 % triethylamine and pH 3.0±0.05 was adjusted using Orthophosphoric acid 85%v/v) and methanol in the ratio of 70:30 v/v. The detection wavelength was 215 nm. The method was validated with respect to linearity, precision, accuracy, and specificity. The response was linear in concentration range of 1 - 20 µg/mL. The value of slope and correlation coefficient found to be 42506 and 0.9996 respectively. The R.S.D value for intra- and inter- day precision studies were <1.169 and <1.263, respectively. The recovery of the drug ranged between 98.81 and 101.76% from a mixture of degradation sample.

Introduction: 103Pd brachytherapy sources are used normally in prostate and breast cancer therapy. For calculating the effect of source shield or applicators and dose distribution usually Monte Carlo codes such as MCNP and GEANT are applied. The aim of this work is to determine the dosimetric parameters of a 103Pd source in soft tissue phantom. Method: In this present work, we have used MCNP4C code to calculate relative dose in soft tissue phantom. We have calculated the dose distribution in soft tissue phantom with 1.04 g/cm3 density which is more accurate than water phantom for human tissue. Results: We have determined the isodose curves and anisotropy function, F(r,?), and radial dose function, g(r), which are important dosimetric parameters. Our result are in good agreement with others result. Conclusion: Dose deposition in high gradient region, near the source, can only be calculated accurately by Monte Carlo method. The obtained value of g(r) and F(1 cm, ?) as the TG-43 parameters for the source, are agree quite well with the result of others.

People affected with Diabetes Mellitus use Continuous Glucose Monitoring (CGM) devices for monitoring of their blood glucose level. The currently available CGM devices show the current glycemic level of the user and produce alarm whenever the glycemic level exceeds the normal range or is in increasing or decreasing trend. Some devices do prediction of the glucose value some time slots ahead and give an alarm of the impending Hypo/ Hyper glycemia situation. But the true scenario is that the success is only 50% due to false alarms or missing alarms. With the understanding that CGM data do have errors when the rate of change is high, in our study, we have tried the prediction of glucose levels ahead in time without intervention through Auto Regressive Integrated Moving Average (ARIMA) Model with its parameters optimized with Differential Evolution. The Method is validated with Simulated data obtained from the web based Diabetes Educator. First half of the data set is used for training and the remaining half is used for testing. Mean Absolute Difference (MAD) between the predicted and actual glucose values is used as the performance metric. The experiments conducted showed promising results with MAD in the range of 6 to 10.3. The prediction accuracy can be improved by increasing the number of iterations and the optimum selection of scaling factor.

This study attempts to investigate the change, if any, in the volatility observed in the Indian stock market due to the introduction of futures trading. The change in the volatility is compared in terms of the structure of the volatility. This is done to give insights into the way the futures market is influencing the Indian spot market’s volatility. The main objective of the study is to investigate whether there has been significant change in relative volatility of the underlying spot return and futures return. The period of study is from 1st January 2000 to 31st December 2010 for the spot prices. The study used three stock indices of NSE namely Nifty, CNX IT and CNX Bank. The index futures time series analyzed here uses data on the near month contract as they are most heavily traded. The study has used four measures of volatility. The study finds that for the three NSE indices, the study rejects the null hypothesis of ‘no significant change in relative inter-day volatility between spot prices and futures prices’ over the entire period 2000-2010, but cannot reject the hypothesis fully for all the individual years. There is significant change in relative intra-day volatility between spot prices and futures prices for all the three NSE indices.

A study is conducted to investigate the effects of socio economic factors on agricultural land use in Malaysia. Relevant socio – economic variables (from 1965 to 2007) were aggregated from the databases of various international and national agencies. These data include agricultural and non agricultural land uses, Gross Domestic Product (GDP) & Gross National Product (GNI); labour force, population age distribution, numbers of cars per 1000 people; road density. GDP/capita & GNI/capita, labour efficiencies ie (ha/worker in agricultural subsectors), percentage of male and female in the agricultural labour force and % change in outputs of major crops were derived from relevant data. Data were then subjected to multiple linear regression analysis using SPSS version 18. Findings indicated that, relevant socio – economic factors in agricultural land use in Malaysia are available workforce of the population, percentage of workers engaged in plantation farming, female workforce in agriculture, farm size and the workers condition of service in non - agricultural sector. This study has revealed that labour supply and their conditions of service are major factors in agricultural land use. This study further underscores the need for technology – driven - agricultural practices in the face of better posited industries competing for available labour.

In this paper, we present a novel algorithm for time series ARMA parameter estimation, namely, artificial neural network with trust region strategy. It combines the merit of neural network which has the capacity of highly parallel computing with the global convergence of trust region algorithm. The convergence of the algorithm is proved under certain conditions. It offers high accuracy for the parameter value of the ARMA model and makes the model is more superior. Numerical experiment shows that the new method is effective and attractive.