Sumant Kumar Mohapatra

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.

A Novel Efficient Design of Intelligent Street Lighting Monitoring System Using ZigBee Network of Devices and Sensors on Embedded Internet Technology

The proposed system can optimize the management and efficiency of street lighting systems. It uses ZigBee-based wireless devices. It also uses a sensor combination to control and guarantee the desired system parameters. A monitoring system based on the embedded Internet technology for street light is designed and implemented. The mode adopted in this monitoring system is the Browser/Server mode. The realization technologies of an embedded Web server are used. The results of system performance testing show that the system can meet most of the embedded Internet applications demands and the purposes of online access, control and management of the street lighting using a standard Web browser over the Internet.

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 effective quality inspection system using image processing techniques

An Inspection is a study of methods and techniques that can be suitably employed in practical applications. In this paper, a new activity is proposed and analysis framework to facilitate the inspection of a cylindrical object using coordinate conversion technique along with pattern matching which is again verified by machine vision technique in which maximum efficiency can be achieved. By using LABVIEW software and vision builder software the quality of an object in terms of linearity can be investigated by using different image processing techniques such as image compression, image restoration etc. along with the various image processing functions like special filters and classifiers to compute the optimum results. Using smart camera in the inspection system the static as well as the dynamic object is captured in fraction of seconds without any blurs; as a result the optimum image quality without any distortion is obtained for better analysis. The proposed system is very precise, accurate and flexible with reasonable development cost compared to other model. With the aid of an Industrial robotic system with simulation software the object is replaced immediately when the same is rejected by the machine vision model. Apart from this, the proposed model can be implemented for any type of manufacturing unit.

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.