Bridging Quantitative and Qualitative of Glaucoma Detection

Glaucoma diagnosis involves extracting three features of the fundus image; optic cup, optic disc and vernacular. Present manual diagnosis is expensive, tedious and time consuming. A number of researches have been conducted to automate this process. However, the variability between the diagnostic capability of an automated system and ophthalmologist has yet to be established. This paper discusses the efficiency and variability between ophthalmologist opinion and digital technique; threshold. The efficiency and variability measures are based on image quality grading; poor, satisfactory or good. The images are separated into four channels; gray, red, green and blue. A scientific investigation was conducted on three ophthalmologists who graded the images based on the image quality. The images are threshold using multithresholding and graded as done by the ophthalmologist. A comparison of grade from the ophthalmologist and threshold is made. The results show there is a small variability between result of ophthalmologists and digital threshold.

Simultaneous HPAM/SDS Injection in Heterogeneous/Layered Models

Although lots of experiments have been done in enhanced oil recovery, the number of experiments which consider the effects of local and global heterogeneity on efficiency of enhanced oil recovery based on the polymer-surfactant flooding is low and rarely done. In this research, we have done numerous experiments of water flooding and polymer-surfactant flooding on a five spot glass micromodel in different conditions such as different positions of layers. In these experiments, five different micromodels with three different pore structures are designed. Three models with different layer orientation, one homogenous model and one heterogeneous model are designed. In order to import the effect of heterogeneity of porous media, three types of pore structures are distributed accidentally and with equal ratio throughout heterogeneous micromodel network according to random normal distribution. The results show that maximum EOR recovery factor will happen in a situation where the layers are orthogonal to the path of mainstream and the minimum EOR recovery factor will happen in a situation where the model is heterogeneous. This experiments show that in polymer-surfactant flooding, with increase of angles of layers the EOR recovery factor will increase and this recovery factor is strongly affected by local heterogeneity around the injection zone.

Efficient System for Speech Recognition using General Regression Neural Network

In this paper we present an efficient system for independent speaker speech recognition based on neural network approach. The proposed architecture comprises two phases: a preprocessing phase which consists in segmental normalization and features extraction and a classification phase which uses neural networks based on nonparametric density estimation namely the general regression neural network (GRNN). The relative performances of the proposed model are compared to the similar recognition systems based on the Multilayer Perceptron (MLP), the Recurrent Neural Network (RNN) and the well known Discrete Hidden Markov Model (HMM-VQ) that we have achieved also. Experimental results obtained with Arabic digits have shown that the use of nonparametric density estimation with an appropriate smoothing factor (spread) improves the generalization power of the neural network. The word error rate (WER) is reduced significantly over the baseline HMM method. GRNN computation is a successful alternative to the other neural network and DHMM.

The Role of Intrinsic Motivation in Explaining Students- Willingness to Use Software Applications

The present study was designed to test the influence of intrinsic ICT-motivation, perceived usefulness and ease of use on business students- willingness to use a particular software package. A questionnaire was completed by 196 business students in Norway. We found that 34% of the variance in the students- willingness to use the software could be explained by the three proposed antecedents. Intrinsic ICT-motivation seems to be the most important predictor of students- satisfaction willingness to use the software package.

Analysis of Lower Extremity Muscle Flexibility among Indian Classical Bharathnatyam Dancers

Musculoskeletal problems are common in high performance dance population. This study attempts to identify lower extremity muscle flexibility parameters prevailing among bharatanatyam dancers and analyze if there is any significant difference exist between normal and injured dancers in flexibility parameters. Four hundred and one female dancers and 17 male dancers were participated in this study. Flexibility parameters (hamstring tightness, hip internal and external rotation and tendoachilles in supine and sitting posture) were measured using goniometer. Results of our study it is evident that injured female bharathnatyam dancers had significantly (p < 0.05) high hamstring tightness on left side lower extremity compared to normal female dancers. The range of motion for left tendoachilles was significantly (p < 0.05) high for the normal female group when compared to injured dancers during supine lying posture. Majority of the injured dancers had high hamstring tightness that could be a possible reason for pain and MSDs.