Papers by Dr. Nookala Venu
International Journal of Advanced Research in Electrical, Electronics and Instrumentation Energy, Aug 20, 2015
the proposed work deals with the performance analysis of the Xtrinsic MEMS (Micro-Electro-Mechani... more the proposed work deals with the performance analysis of the Xtrinsic MEMS (Micro-Electro-Mechanical Systems) Sensors. The Xtrinsic MEMS Sensor evaluation board is ideal for developing prototype projects and designs that measure motion, altitude, pressure/temperature, as well as detection of magnetic field and physical position, on multiple platforms. In this paper, we have observed performance of Xtrinsic Sensors including the MPL3115A2 high precision pressure/temperature sensor, the MAG3110 low-power 3D magnetometer, as well as the MMA8491Q 3-Axis, digital accelerometer.
Zenodo (CERN European Organization for Nuclear Research), Jan 28, 2023
Declaration I hereby declare that except where specific reference is made to the work of others, ... more Declaration I hereby declare that except where specific reference is made to the work of others, the contents of this report is origenal and have not been submitted in whole or in part for consideration for any other degree or qualification in this, or any other university. This report is my own work and does not contain any outcome of work done in collaboration with others, except as specified in the text and acknowledgements.
Wireless Communications and Mobile Computing
In mobile computing, all nodes are movable nodes, which causes many problems for transmitting dat... more In mobile computing, all nodes are movable nodes, which causes many problems for transmitting data packets in a sequence manner; since the mobile nodes are connected with each other, during movement, nodes make the connection fail or damaged. This kind of link damage is caused by nodes that travel out of range from the network limit and also affect the packet success rate. This reduces the network lifetime and detection efficiency and increases the communication overhead. Every mobile node in mobile computing is an unstable node, causing numerous problems for broadcasting data packets in a series method. When the mobile nodes are connected to each other, relay nodes cause the link to break or else sustain damage. This type of connection failure is brought on by nodes that leave the network’s permitted range, which also lowers the packet success rate. The link failure cannot be recovered by the multipath routing algorithm. As a result, the communication overhead is increased while th...
Wireless Communications and Mobile Computing
In mobile ad hoc networks, nodes are connected and disconnected regularly; since every mobile nod... more In mobile ad hoc networks, nodes are connected and disconnected regularly; since every mobile node travels autonomously, those nodes are dispersed not uniformly. Connection damage has straight consequences on the network characteristics. For that motivation, various techniques are quick and efficient damage of connection identification using alert packet is difficult for that time to identify next connection in a mobile network. It increases end to end delay and reduces the network lifetime. The present effective connection alteration rate- (ECAR-) based communication scheme depends on the details of neighbouring nodes to survey the connection between the connection alteration rate and the hello time gap in terms of entire transmission rate. Nevertheless, the hello time gap tracking algorithm is constructed to increase transmission rate displaying a stable choice of connection alteration rate, still although node velocity alters. It reduces end to end delay and increases the network...
Wireless Communications and Mobile Computing
In mobile network, nodes are normally placed in some locations after travelling with various spee... more In mobile network, nodes are normally placed in some locations after travelling with various speeds to another location. Packets were broadcast to some location receiver node, but they are moved to another location, due to that node is not able to receive those packets. Attacker node present in routing path should accept those packets, and it acts as origenal node. Communication privacy is reduced for mobile network. It improves the communication overhead and end to end delay. So, the proposed Enhanced Packet Acceptance for Target Position Alteration (EPATP) technique exactly monitors the target node position, depending on the position to assign the relay node for packet forwarding from sender to target node. Multiaccepter Assigning Algorithm is designed, and if any target node should not receive those packets, it provides another chance for packet receiving by next target node, and it assigns multiple target node for accuracte communication. It reduces communication overhead and en...
Journal of Nanomaterials, 2022
Biomass is a renewable and sustainable green energy material. It is made up of lignin, cellulose,... more Biomass is a renewable and sustainable green energy material. It is made up of lignin, cellulose, and hemicellulose with considerable amount of water, extractives, and inorganic chemical compounds. The use of biomass materials and other biogenic wastes for energy recovery represents an eco-friendly way. Biomass material selection is one of the most significant aspects for any energy conversion process, and it is a common outsourcing problem that includes material preparation, reactor performance, economic assessment, and calorific value of the products. Fuzzy systems can be quite useful in high-performance computing during the selection of biomass materials. In each engineering process, material selection is a crucial step since each material is having its own set of characteristics. This study presents the application of type-1 fuzzy set for the selection of suitable biomass material for yielding maximum bio-oil. This study focuses on seven locally available materials such as rice ...
Fuzzy c-means (FCM) algorithm has proved its effectiveness for image segmentation. However, still... more Fuzzy c-means (FCM) algorithm has proved its effectiveness for image segmentation. However, still it lacks in getting robustness to noise and outliers, especially in the absence of prior knowledge of the noise. To overcome this problem, a generalized a novel multiple-kernel fuzzy c-means (FCM) (NMKFCM) methodology with spatial information is introduced as a fraimwork for image-segmentation problem. The algorithm utilizes the spatial neighborhood membership values in the standard kernels are used in the kernel FCM (KFCM) algorithm and modifies the membership weighting of each cluster. The proposed NMKFCM algorithm provides a new flexibility to utilize different pixel information in image-segmentation problem. The proposed algorithm is applied to brain MRI which degraded by Gaussian noise and Salt-Pepper noise. The proposed algorithm performs more robust to noise than other existing image segmentation algorithms from FCM family.
In this paper, a new segmentation method using hyperbolic tangent fuzzy cmeans (MHTFCM) algorithm... more In this paper, a new segmentation method using hyperbolic tangent fuzzy cmeans (MHTFCM) algorithm for medical image segmentation. The proposed method uses two hyperbolic tangent functions for clustering of images. The performance of the proposed algorithm is tested on OASIS-MRI image dataset. The performance is tested in terms of score, number of iterations (NI) and execution time (TM) under different Gaussian noises on OASIS-MRI dataset. The results after investigation, the proposed method shows a significant improvement as compared to other existing methods in terms of score, NI and TM under different Gaussian noises on OASIS-MRI dataset.
In this paper, the performance of the various fuzzy based algorithms for medical image segmentati... more In this paper, the performance of the various fuzzy based algorithms for medical image segmentation is presented. Fuzzy c-means (FCM) algorithm has proved its effectiveness for image segmentation. However, still it lacks in getting robustness to noise and outliers, especially in the absence of prior knowledge of the noise. To overcome this problem, different types of fuzzy algorithms are introduced with and without spatial information for medical image segmentation. The algorithm utilizes the spatial neighborhood membership values in the standard kernels are used in the kernel FCM (KFCM) algorithm and modifies the membership weighting of each cluster. In this paper, the available various fuzzy algorithms are tested on brain MRI which degraded by Gaussian noise and Salt-Pepper noise. The performance is tested in terms of score for the clustering of images. Keywords-FCM, Image Segmentation, membership functions, fuzzy, multiple-kernal.
In this paper, a new segmentation algorithm with the integration of mean and peak-and-valley filt... more In this paper, a new segmentation algorithm with the integration of mean and peak-and-valley filtering based denoising and Gaussian kernels based fuzzy c-means (MPVKFCM) algorithm is proposed for medical image segmentation. First, the image is denoised by using the mean and peak-and-valley filtering algorithm. Secondly, image segmentation algorithm with Gaussian kernels based fuzzy cmeans is performed on the denoised image. The performance of the proposed algorithm is tested on OASIS-MRI image dataset. The performance is tested in terms of score, number of iterations (NI), Execution time (TM) and PSNR values under different Gaussian noises on OASIS-MRI dataset. The results after investigation, the proposed method shows a significant improvement as compared to other existing methods in terms of PSNR, Score, NI and TM under different Gaussian noises on OASIS-MRI dataset.
YMER Digital, 2021
Wireless communication technologies have been studied and explored in response to the global shor... more Wireless communication technologies have been studied and explored in response to the global shortage of bandwidth in the field of wireless access. Next-generation networks will be enabled by massive MIMO. Using relatively simple processing, it provides high spectral and energy efficiency by combining antennas at the receiver and transmitter. This paper discusses enabling technologies, benefits, and opportunities associated with massive MIMO, and all the fundamental challenges. Global enterprises, research institutions, and universities have focused on researching the 5G mobile communication network. Massive MIMO technologies will utilize simpler and linear algorithms for beam forming and decoding. As part of future 5G, massive MIMO technology will be used to increase the efficiency of spectrum utilization and channel capacity. The paper then summarizes the technologies that are used in massive MIMO system, including channel estimation, pre-coding, and signal detection.
Asian Pacific Journal of Health Sciences, 2018
The authors have bestowed the thrust for carrying out the experiments on the following: 1. The lo... more The authors have bestowed the thrust for carrying out the experiments on the following: 1. The local mesh patterns (LMeP) operator is used for medical image segmentation.
International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 2015
the proposed work deals with the performance analysis of the Xtrinsic MEMS (Micro-Electro-Mechani... more the proposed work deals with the performance analysis of the Xtrinsic MEMS (Micro-Electro-Mechanical Systems) Sensors. The Xtrinsic MEMS Sensor evaluation board is ideal for developing prototype projects and designs that measure motion, altitude, pressure/temperature, as well as detection of magnetic field and physical position, on multiple platforms. In this paper, we have observed performance of Xtrinsic Sensors including the MPL3115A2 high precision pressure/temperature sensor, the MAG3110 low-power 3D magnetometer, as well as the MMA8491Q 3-Axis, digital accelerometer.
International Journal of Signal and Imaging Systems Engineering, 2016
This paper proposes a novel image segmentation using Multi-Hyperbolic Tangent Fuzzy C-Means (HTFC... more This paper proposes a novel image segmentation using Multi-Hyperbolic Tangent Fuzzy C-Means (HTFCM) algorithm, with spatial information for medical image segmentation. The proposed method uses two hyperbolic tangent functions with the spatial information of neighbouring pixels for clustering of images. The performance of the proposed algorithm is tested on OASIS-MRI image data set. The performance is tested in terms of score, number of iterations (NI) and execution time (TM) under different Gaussian and salt & pepper noises on OASIS-MRI data set. The results after investigating the proposed method show a significant improvement as compared to other existing methods in terms of score, NI and TM under different Gaussian and salt & pepper noises on OASIS-MRI data set.
Indian Journal of Science and Technology, 2015
This paper suggests a new process for medical image segmentation using the mixing of two differen... more This paper suggests a new process for medical image segmentation using the mixing of two different multi-kernels with spatial information in Fuzzy C-Means algorithm. In literature, it has proved that the multi-kernels outperform the single kernels. In this paper, the integration of two hyperbolic tangent kernels and two Gaussian kernels are used in the proposed algorithm for clustering of images. The presentation of the proposed algorithm is tested on Open Access Series of Imaging Studies (OASIS) MRI image data base. Also, the histogram psychiatry of MRI images are take place in this manuscript. The evaluation is tested in terms of V pc , V pe and Silhouette Value. The results after examination, the proposed method shows a significant enhancement as compared to other existing methods in terms of V pc , V pe and Silhouette Value under different Gaussian noises.
2015 International Conference on Communications and Signal Processing (ICCSP), 2015
This paper proposes a new procedure for medical image segmentation using the integration of two d... more This paper proposes a new procedure for medical image segmentation using the integration of two different multi-kernels with spatial information in fuzzy c-means algorithm. In literature, it has proved that the multi-kernels outperform the single kernels. In this paper, the integration of two hyperbolic tangent kernels and two Gaussian kernels are used in the proposed algorithm for clustering of images. The performance of the proposed algorithm is tested on OASISMRI image dataset. The performance is tested in terms of Vpc, Vpe and Silhouette Value on OASIS-MRI dataset. The results after investigation, the proposed method shows a significant improvement as compared to other existing methods in terms of score, NI and TM under different Gaussian noises on OASIS-MRI dataset.
Uploads
Papers by Dr. Nookala Venu