Sushil Kumar Mahapatra

Stability and energy aware reverse AODV routing protocol in MANETS

Most of the multipath on demand routing protocols are mobile Adhoc Networks suffer due to frequent changes in the network topology confined network resources such as battery capacity of nodes, security of data packets and scalability of the network. This paper has been proposed a stability and Energy Aware Reverse Adhoc On demand Distance Vector (SEAR-AODV) Routing protocol. This method is a modification of existing Reverse R-AODV routing protocol. It is based on optimization of the existing R-AODV routing protocol by computing the reliability factor (RF) of nodes that includes both energy and rout stability aware metric. SEAR-AODV uses the path with high RF value as the primary path to rout the data packets where as secondary paths are used based on the descending order of their RF values. it uses a new make-before-break route maintenance mechanism. In order to reduce the control overhead due to route recovery. a comparative study by NS2 tool signifies that the proposed protocol SEAR-AODV enhances the packet delivery fraction and reduces both the latency as well as the average consumed energy.

Optimized approach of sobel edge detection technique using Xilinx system generator

In this paper a new method is utilized in which sobel X-Y edge detection combines with Gaussian filter using histogram stretching method. In recent days, the edge detection techniques come to the picture with a very important utilization in medical industry to detect tumors and fractures in the human body[1],[2],[3]. So In this paper we firstly propose a new optimized edge detection technique which is a better edge detection technique so far in our knowledge in terms of improved mean square error(MSE) and picture signal to noise ratio (PSNR) using very limited resources used in the SPARTAN 3A DSP 3400A development platform FPGA kit.

A Proposed Multithreading Fuzzy C-Mean Algorithm for Detecting Underwater Fishes

Recently, Scientists needs to know the behavior of fish populations in underwater. Previously many algorithms are used but they are suffered in complex textures and low detection rate. This paper proposed a multi threading fuzzy c-mean (MFC mean) approach to detect multi-moving fishes in a noisy and dense condition. In this approach, we combines the multi threaded parallel (MTP) approach and kernel based approach for optical flow. A fuzzy c-mean concept provided as a supporting factor. The simulation results show that the proposed method can able to track and detect underwater fishes with high detection rate.

An Enhanced BE-GGMM-EI Algorithm for Medical Image Denoising

Now a days, brain tumor detection without losing the edge information is very vital field of research, which may save many life. So in our proposed method, we have given emphasis on minimum loss of information in brain tumor MRI image. So we propose a BE-GGMM-EI (Background Estimated-Generalized Gaussian Mixture Model with Edge Information) method for detecting different brain tumors. In our proposed method, the tumor MRI image is first processed for background subtraction then the edge is enhanced with edge maximization technique. After that the image is denoised GGMM. Experimental results authenticate our proposed GGMM method to have better edge information with good PSNR value.

Simulation-Based Detection of Lyme Disease in Blood in Rhesus Macaques Using Combined Volterra RLS-MTP Approach for Proper Antibiotic

Recently, Rhesus Macaques were infected with Borrelia Burgdor feri (Lyme disease in blood). For detection of residual organisms, various types of methods were utilized including feeding of lab-reared ticks on monkeys, culture, immunofluorescence, etc. To confirm the diagnosis of Lyme disease, usual laboratory test is totally reliable. If diagnosing rate of presence of disease Lyme then there are more possibilities or guidelines are available for treatment. This paper proposed a method for Detecting Borrelia Burgdorferi in Rhesus Macaques by using Volterra RLS Algorithm in addition with multithreading Parallel Approach (MTPA). The proposed method with MATLAB 8.0 is able to accurately detect the Lyme disease in blood with high detection rate. This results in raising certain questions about the pathogenicity of antibiotic-tolerant. From author knowledge, this is the first time to calculate the detection rate of Lyme disease in blood as in infected Rhesus Macaques.

A Comparative Framework of Probabilistic Atlas Segmentation Method for Human Organ’s MRI

Recently, different image analysis methods are used for human body parts. But the internal pectoral muscle segmentation of important body parts in a automatic way is widely used. This is also vital for multi modal image registration. Previously, breast MRI image analysis by automatic pectoral muscle segmentation is studied. In this paper, we introduce a comparative framework of probabilistic atlas segmentation method for breast with brain, chest, heart and liver MRI. For breast, brain, heart and liver and chest segmentation, the obtained DSC values are 0.76 ± 0.12, 0.71 ± 0.15, 0.66 ± 0.08, 0.77 ± 0.12 and 0.72 ± 0.13 respectively. The total overlap values for each case are 0.76 ± 0.12, 0.76 ± 0.15, 0.71 ± 0.08, 0.70 ± 0.12 and 0.70 ± 0.13 respectively.

A Novel Approach for Tracking Sperm from Human Semen Particles to Avoid Infertility

Now a days, the infertility is a big problem for human being, especially for men. The mobility of the sperm does not depend on the number of sperm present in the semen. To avoid infertility, the detection rate of the multi moving sperms is to measured. There are different algorithms are utilized for detection of sperms in the human semen, but their detection rate is not up to the mark. This article proposed a method to track and detect the human sperm with high detection rate as compared to existing approaches. The sperm candidates are tracked using Kalman filters and proposed algorithms.

Concentration of Acetone Levels in Breath for Monitoring Blood Glucose Level

Diabetes is a major problem affecting millions of people today and if left unchecked can create enormous implication on the health of the population. Among the various noninvasive methods of detection, breath analysis presents an easier, more accurate and viable method in providing comprehensive clinical care for the disease. This paper examines the concentration of acetone levels in breath for monitoring blood glucose levels and thus predicting diabetes. The analysis uses the support vector mechanism to classify the response to healthy and diabetic samples. For the analysis ten subject samples of acetone levels are taken into consideration and are classified according to three labels which are healthy, type 1 diabetic and type 2 diabetic.

7μm Core diameter fiber sensor: A solution for efficient strain measurement

In this paper the monitoring capabilities like static and dynamic nature of micro meter diameter fiber transmission lines are experimentally setup. This small diameter fiber optical lines have very less impact on mechanical performance. A 7micrometer fiber is used as strain sensor. The experimental results shows that the central axial shift linearly, without creating any displacement with strain and in different temperature environment.

Multimoving Human Sperm Tracking Using CGM-CS Approach and Comparative Analysis for Proper Diagnosis in Infertility

In this paper, we introduced an algorithm for tracking and detecting multi moving human sperm using Course Grained Multi Threading Cam Shift (CGM-CS) approach in a microscopic human sperm moving video. This method is fully based on adaptive Cam Shift algorithm using color model. This algorithm is design to track and detect the sperms by using multi threading concept. The multi threading concept is compared continuously to its mean value in the successive frame in the appropriate video. The result obtained by the proposed method is also compared with the Maximum Intensity Region (MIR) algorithm, Lukas-Kanade (LK) algorithm and Kernel Based (KB) algorithm. Experimental results demonstrate that the CGM-CS algorithm is capable of tracking the sperm with high detection rate with minimum time taken as compared to existing approaches.