Skip to main content

Tenneti Madhu

Followers

5

Following

1

Public Views

The University of Sydney

De La Salle University

Albert Bastardas-Boada

Universitat de Barcelona

Armando Marques-Guedes

UNL - New University of Lisbon

Arizona State University

Zhisheng Wen (Edward)

Hong Kong Shue Yan University

Gülsüm Killi Yılmaz

Ankara University

Willy A Renandya

Nanyang Technological University

Christine Sleeter

California State University, Monterey Bay

Andrea Graziosi

Università degli Studi di Napoli "Federico II"

Interests

Uploads

Papers by Tenneti Madhu

Fault Diagnosis in the Brushless Direct Current Drive Using Hybrid Machine Learning Models

ECTI Transactions on Electrical Engineering, Electronics, and Communications

The brushless direct current (BLDC) motor drive is gaining popularity due to its excellent contro... more The brushless direct current (BLDC) motor drive is gaining popularity due to its excellent controllability and high efficiency. This paper introduces a fault diagnosis method for open circuit (OC) and short circuit (SC) BLDC motor drives using a hybrid classifier with hybrid optimization. Features such as current, voltage, speed, and torque are considered as the training data. The features are extracted by discrete wavelet transform (DWT) and then employed to train the classifiers to distinguish between fault types and values of response parameters using the support vector machine and Naive Bayes classifier (SVM-NB). To further improve the performance of the system, hybrid chaotic particle swarm optimization (CPSO) algorithms and teaching-learning-based optimization (TLBO) are used. This method is capable of detecting and recognizing the type of faults in the BLDC motor. The developed approach is implemented on the MATLAB/SIMULINK for OC, SC, and no-fault conditions. These hybrid al...

Improved Switching Performance Analysis of Space Vector Pulse width Modulation on Field Programmable Gate Array

Nowadays VLSI (Very Large Scale Integration) technology is being successfully implemented by usin... more Nowadays VLSI (Very Large Scale Integration) technology is being successfully implemented by using Pulse Width Modulation (PWM) in applications like power electronics and drives. The main problems in PWM viz. harmonic distortion and switching speed are overcome by implementing the Space-Vector PWM (SVPWM) technique by using the Xilinx tool VHDL (Verilog High Speed Integrated Circuit (VHSIC) Hardware Description Language) and tested in programmable Integrated Circuits of Field Programmable Gate Array (FPGA). The results are provided along with simulation analysis in terms of hardware utilization and schematic, power report, computing time and usage of memory.

Ultra low voltage and low power Static Random Access Memory design using average 6 . 5 T technique

Power Stringent Static Random Access Memory (SRAM) design is very much essential in embedded syst... more Power Stringent Static Random Access Memory (SRAM) design is very much essential in embedded systems such as biomedical implants, automotive electronics and energy harvesting devices in which battery life, input power and execution delay are of main concern. With reduced supply voltage, SRAM cell design will go through severe stability issues. In this paper, we present a highly stable average nT SRAM cell for ultra-low power in 125nm technology. The distinct difference between the proposed technique and other conventional methods is about the data independent leakage in the read bit line which is achieved by newly introduced block mask transistors. An average 6.5T SRAM and average 8T SRAM are designed and compared with 6T SRAM, 8T SRAM, 9T SRAM, 10T SRAM and 14T SRAM cells. The result indicates that there is an appreciable decrease in power consumption and delay.

Brain Tumor Detection and Its Area Estimation in Mri Images Using Pillar K-Means Algorithm

Generally, CT or MRI scan, when directed into intracranial cavity, produces a complete image of t... more Generally, CT or MRI scan, when directed into intracranial cavity, produces a complete image of the brain. This image can be examined visually by the physician or fed to a computer for detection & diagnosis of brain tumor. A new approach is proposed to detect the Brain tumor based on segmentation by applying Pillar K-means algorithm. At the end of the process the tumor is extracted from the MR image and its exact position and shape are determined. The stage of the tumor is displayed based on the amount of area (size and shape) calculated from the cluster.

Image resolution and contrast enhancement with optimal brightness compensation using wavelet transforms and particle swarm optimization

IET Image Processing, 2021

Optimized Wavelet Decomposition and Gaussian interpolation based Satellite Image Enhancement

International Journal of Innovative Technology and Exploring Engineering, 2020

Satellite images (SI) play a vital role in various remote sensing applications like geoscience, g... more Satellite images (SI) play a vital role in various remote sensing applications like geoscience, geographical studies, observing the earth's atmosphere, monitoring natural disasters, etc. The SI are used in these applications require high-resolution. The performance of the wavelet transforms based resolution enhancement methods depends on the type of the mother wavelet used and it varies with image to image. The novel robust SI resolution enhancement technique including Optimized wavelet transform based image decomposition and Gaussian interpolation is proposed in this paper. Optimized wavelet decomposition is obtained using the Stochastic Diffusion Search algorithm and the Gaussian distribution function is used for interpolation. The proposed method is compared with the Discrete wavelet decomposition and Gaussian interpolation resolution enhancement method and proved that the proposed method gives the best results for any image.

Satellite Image Enhancement using Optimized Wavelet Decomposition and Bicubic Interpolation

International journal of recent technology and engineering, Jan 30, 2020

Satellite Images (SI) play a vital role in various civilian and military applications for weather... more Satellite Images (SI) play a vital role in various civilian and military applications for weather forecasting, monitoring of resources of the earth, environmental studies, observing natural disasters and natural calamities, etc. When these SI are used in military applications and almost all other applications for efficient study, the big challenge is its resolution. In wavelet transforms based satellite image enhancement techniques, choosing a proper wavelet transform plays a key role and vary with the image to image. To improve the resolution, a novel robust optimized wavelet decomposition and a bicubic interpolation-based satellite image enhancement method is proposed. In this method, the Stochastic Diffusion Search (SDS) algorithm is used to get the optimized wavelet decomposition of the image into different subbands and bicubic interpolation is used to improve the resolution. Image is decomposed using the optimized wavelet filter bank based on the SDS algorithm, decomposed sub-bands are interpolated with bicubic interpolation and inverse wavelet transform is applied to compose the interpolated sub-bands into a high-resolution image. The proposed method is tested on satellite images and other images also. Compared to the proposed method with the existing methods and proved that the proposed method is superior to existing methods and applicable to any type of image.

Prognosis Of BLDC Drive Faults Using Autoregressive Integrated Moving Average Algorithm

Generally, Brushless DC (BLDC) machines attract many industrialists due to their unique character... more Generally, Brushless DC (BLDC) machines attract many industrialists due to their unique characteristics like better output, stabilized performance, and high torque to current ratio. BLDC drive has a long life, and they do not need maintenance; however, the drive has low starting torque and high cost. Thus, Non-stop monitoring and future prediction methods can reduce fault occurrence and improve system performance. In this paper, we have proposed the prognosis of BLDC drive faults using the Autoregressive Integrated Moving Average (ARIMA) Algorithm. Here, we consider the open circuit (OC) and short circuit (SC) faults in BLDC drive to prognosis by ARIMA technique. The ARIMA has a fixed structure, and it is particularly built for time series data. By data acquisition system, the drive parameters such as current, torque, and speed will be continuously obtained. Filtering out the high-frequency noise present in the data is the main principle of the ARIMA model. Matlab/Simulink platform ...

VHDL Design and Hardware Realization of Hybridartificial Intelligence Architecture

American Journal of Applied Sciences, Feb 24, 2014

Evolutionary Algorithms (EA) use Genetic Algorithm (GA) in many optimization problems to efficien... more Evolutionary Algorithms (EA) use Genetic Algorithm (GA) in many optimization problems to efficiently compute the function value in less time. In this study the weight optimization of the Artificial Neural Network (ANN), using the Back Propagation Network (BPN), is tested and presented with GA. The combined architecture of Neuro-Genetic (Hybrid Artificial Intelligence) approach is proposed and simulated results are provided along with device Utilization, Simulation time, Timing analysis and power analysis by using very high speed integrated circuits Hardware Description Language (HDL).

Investigation of suitability of grid-based ionospheric models for GAGAN

Electronics Letters, 2006

ABSTRACT

Quantitative Analysis of Metastasis Brain Tumor and its Area Estimation in MR Images

International Journal of Computer Applications

Metastasis brain tumor develops multiple tumors at asymmetrical location of the human brain. MRI ... more Metastasis brain tumor develops multiple tumors at asymmetrical location of the human brain. MRI Imaging is one of the prudent mechanisms to extract the tumor regions and to map the brain for diagnosing. For the better diagnosis, one must detect the tumor accurately and need to calculate the area and volume of the tumor exactly. Here in this letter, we proposed a novel resolution enhancement technique to improve the quality of MR brain image and optimized hybrid clustering with region split and merge algorithm to detect the tumor cells from the original MR images and to estimate the tumors from different locations. Simulation results show that the proposed algorithm has performed superior to conventional clustering algorithms such as Fuzzy C-means (FCM), K-Means and even optimized pillar algorithm.

Characterization and Area Estimation of MR Brain Tumor Images

International Journal of Computer Applications, 2015

Brain Tumors are detected efficiently by using the Magnetic Resonance Imaging (MRI) techniques. T... more Brain Tumors are detected efficiently by using the Magnetic Resonance Imaging (MRI) techniques. The extracted MRI image is sensitive to noise which limits the visibility of certain characteristics of the image. This unwanted noise can be disintegrated and curtailed from the original Image by using the non linear digital median filter. The intensification is achieved by using the combination of discrete wavelet transform (DWT) and stationary wavelet transform (SWT) augmented with Bi-cubic interpolation algorithm. The quality of the resolute image is analyzed with the possible static parameters. Segmentation and clustering approaches are applied on the resultant sharpened high resolution image to estimate the tumor area. The results obtained with the proposed Optimized Hybrid Clustering (OHC) algorithm are compared with the existing K-Means, Pillar K-Means and Fuzzy C-means (FCM) approaches. The tumor sensitivity and accuracy of the test parameters with the OHC approach are estimated. In-order to deliver the drug to kill the aberrant tissue, the number of tumor cells is estimated against its radius.

Fault analysis for field programmable gate array (FPGA) using phase path method

IET-UK International Conference on Information and Communication Technology in Electrical Sciences (ICTES 2007), 2007

ABSTRACT

Fault Diagnosis of VLSI Circuits Using FPGA Technology

Modelling of foF2 using neural networks at an equatorial anomaly station

The critical frequency of the F 2-layer (foF 2) is an important parameter in estimating the total... more The critical frequency of the F 2-layer (foF 2) is an important parameter in estimating the total electron content (TEC) of the ionosphere, which is necessary for predicting the ionospheric time delay in GPS applications. The foF 2 data from Ahmedabad, which is in the equatorial anomaly region, are modelled using a multilayer neural network trained with back-propagation algorithm. The IRI-2001 model together with this neural network model can be used for predicting/forecasting of the foF 2 parameter within the Indian subcontinent. The foF 2 values thus predicted can be used to estimate the critical TEC parameter.

Analysis of secure fast roaming techniques with coexistence of 802.1x

2011 2nd International Conference on Wireless Communication, Vehicular Technology, Information Theory and Aerospace & Electronic Systems Technology (Wireless VITAE), 2011

i defines the Robust Security Network Association (RSNA) establishment procedure to provide stron... more i defines the Robust Security Network Association (RSNA) establishment procedure to provide strong mutual authentications and generate fresh Transient keys (TKs) for the data confidentiality protocols. 802.11i RSNA establishment procedure consists of 802.1X, which provides high security by using dynamic Authentication and Key Management. It introduces latency due to the addition of extra messages thereby increasing the roam time. Long

A Primitive Solution of Video Super Resolution

Communications in Computer and Information Science, 2012

Implementation of Multi-hop Cluster based Routing Protocol for Wireless Sensor Networks

International Journal of Computer Applications, 2012

Clustering routing protocol provides an effective method for prolonging the lifetime of a wireles... more Clustering routing protocol provides an effective method for prolonging the lifetime of a wireless sensor network. But most of the researches care less about the communication between Cluster Head (CH) nodes [4] and Base Station (BS). This paper proposed a Multi-hop Cluster based Routing Protocol for long range transmission in wireless sensor network. The protocol consists of two parts, one is with respect to cluster management in sensor area, and the other is about the data transmission between base station and the sensor area. Simulation results show that the protocol offers a better performance than single-hop clustering routing protocols in terms of network lifetime and energy consumption when the base station is located far away from the sensing area.

Ionospheric Time Delay Variations Over a Low Latitude Station at Hyderabad

Satellite-Based Augmentation Systems (SBASs) such as the Indian GPS Aided GEO Augmented Navigatio... more Satellite-Based Augmentation Systems (SBASs) such as the Indian GPS Aided GEO Augmented Navigation (GAGAN) are being developed to aid the civil aviation in precision approach and in other operations. Accurate information on local TEC morphology is essential for developing region specific models. GPS data used in the statistical TEC variability study was recorded at NERTU, Osmania University, Hyderabad using an

Modeling of Indian foF2 data using analysis of variance

Ionosonde foF2 data of 8 stations, spread all over India, for a period of one solar cycle (1966-1... more Ionosonde foF2 data of 8 stations, spread all over India, for a period of one solar cycle (1966-1976) are used for modeling. A technique known as "Analysis of Variance(ANOVA)" is used for m deling the hourly median values of foF2. The foF2 data corresponding to a selected month for the 8 stations and for 11 years is arranged in a

Fault Diagnosis in the Brushless Direct Current Drive Using Hybrid Machine Learning Models

ECTI Transactions on Electrical Engineering, Electronics, and Communications

The brushless direct current (BLDC) motor drive is gaining popularity due to its excellent contro... more The brushless direct current (BLDC) motor drive is gaining popularity due to its excellent controllability and high efficiency. This paper introduces a fault diagnosis method for open circuit (OC) and short circuit (SC) BLDC motor drives using a hybrid classifier with hybrid optimization. Features such as current, voltage, speed, and torque are considered as the training data. The features are extracted by discrete wavelet transform (DWT) and then employed to train the classifiers to distinguish between fault types and values of response parameters using the support vector machine and Naive Bayes classifier (SVM-NB). To further improve the performance of the system, hybrid chaotic particle swarm optimization (CPSO) algorithms and teaching-learning-based optimization (TLBO) are used. This method is capable of detecting and recognizing the type of faults in the BLDC motor. The developed approach is implemented on the MATLAB/SIMULINK for OC, SC, and no-fault conditions. These hybrid al...

Improved Switching Performance Analysis of Space Vector Pulse width Modulation on Field Programmable Gate Array

Nowadays VLSI (Very Large Scale Integration) technology is being successfully implemented by usin... more Nowadays VLSI (Very Large Scale Integration) technology is being successfully implemented by using Pulse Width Modulation (PWM) in applications like power electronics and drives. The main problems in PWM viz. harmonic distortion and switching speed are overcome by implementing the Space-Vector PWM (SVPWM) technique by using the Xilinx tool VHDL (Verilog High Speed Integrated Circuit (VHSIC) Hardware Description Language) and tested in programmable Integrated Circuits of Field Programmable Gate Array (FPGA). The results are provided along with simulation analysis in terms of hardware utilization and schematic, power report, computing time and usage of memory.

Ultra low voltage and low power Static Random Access Memory design using average 6 . 5 T technique

Power Stringent Static Random Access Memory (SRAM) design is very much essential in embedded syst... more Power Stringent Static Random Access Memory (SRAM) design is very much essential in embedded systems such as biomedical implants, automotive electronics and energy harvesting devices in which battery life, input power and execution delay are of main concern. With reduced supply voltage, SRAM cell design will go through severe stability issues. In this paper, we present a highly stable average nT SRAM cell for ultra-low power in 125nm technology. The distinct difference between the proposed technique and other conventional methods is about the data independent leakage in the read bit line which is achieved by newly introduced block mask transistors. An average 6.5T SRAM and average 8T SRAM are designed and compared with 6T SRAM, 8T SRAM, 9T SRAM, 10T SRAM and 14T SRAM cells. The result indicates that there is an appreciable decrease in power consumption and delay.

Brain Tumor Detection and Its Area Estimation in Mri Images Using Pillar K-Means Algorithm

Generally, CT or MRI scan, when directed into intracranial cavity, produces a complete image of t... more Generally, CT or MRI scan, when directed into intracranial cavity, produces a complete image of the brain. This image can be examined visually by the physician or fed to a computer for detection & diagnosis of brain tumor. A new approach is proposed to detect the Brain tumor based on segmentation by applying Pillar K-means algorithm. At the end of the process the tumor is extracted from the MR image and its exact position and shape are determined. The stage of the tumor is displayed based on the amount of area (size and shape) calculated from the cluster.

Image resolution and contrast enhancement with optimal brightness compensation using wavelet transforms and particle swarm optimization

IET Image Processing, 2021

Optimized Wavelet Decomposition and Gaussian interpolation based Satellite Image Enhancement

International Journal of Innovative Technology and Exploring Engineering, 2020

Satellite images (SI) play a vital role in various remote sensing applications like geoscience, g... more Satellite images (SI) play a vital role in various remote sensing applications like geoscience, geographical studies, observing the earth's atmosphere, monitoring natural disasters, etc. The SI are used in these applications require high-resolution. The performance of the wavelet transforms based resolution enhancement methods depends on the type of the mother wavelet used and it varies with image to image. The novel robust SI resolution enhancement technique including Optimized wavelet transform based image decomposition and Gaussian interpolation is proposed in this paper. Optimized wavelet decomposition is obtained using the Stochastic Diffusion Search algorithm and the Gaussian distribution function is used for interpolation. The proposed method is compared with the Discrete wavelet decomposition and Gaussian interpolation resolution enhancement method and proved that the proposed method gives the best results for any image.

Satellite Image Enhancement using Optimized Wavelet Decomposition and Bicubic Interpolation

International journal of recent technology and engineering, Jan 30, 2020

Satellite Images (SI) play a vital role in various civilian and military applications for weather... more Satellite Images (SI) play a vital role in various civilian and military applications for weather forecasting, monitoring of resources of the earth, environmental studies, observing natural disasters and natural calamities, etc. When these SI are used in military applications and almost all other applications for efficient study, the big challenge is its resolution. In wavelet transforms based satellite image enhancement techniques, choosing a proper wavelet transform plays a key role and vary with the image to image. To improve the resolution, a novel robust optimized wavelet decomposition and a bicubic interpolation-based satellite image enhancement method is proposed. In this method, the Stochastic Diffusion Search (SDS) algorithm is used to get the optimized wavelet decomposition of the image into different subbands and bicubic interpolation is used to improve the resolution. Image is decomposed using the optimized wavelet filter bank based on the SDS algorithm, decomposed sub-bands are interpolated with bicubic interpolation and inverse wavelet transform is applied to compose the interpolated sub-bands into a high-resolution image. The proposed method is tested on satellite images and other images also. Compared to the proposed method with the existing methods and proved that the proposed method is superior to existing methods and applicable to any type of image.

Prognosis Of BLDC Drive Faults Using Autoregressive Integrated Moving Average Algorithm

Generally, Brushless DC (BLDC) machines attract many industrialists due to their unique character... more Generally, Brushless DC (BLDC) machines attract many industrialists due to their unique characteristics like better output, stabilized performance, and high torque to current ratio. BLDC drive has a long life, and they do not need maintenance; however, the drive has low starting torque and high cost. Thus, Non-stop monitoring and future prediction methods can reduce fault occurrence and improve system performance. In this paper, we have proposed the prognosis of BLDC drive faults using the Autoregressive Integrated Moving Average (ARIMA) Algorithm. Here, we consider the open circuit (OC) and short circuit (SC) faults in BLDC drive to prognosis by ARIMA technique. The ARIMA has a fixed structure, and it is particularly built for time series data. By data acquisition system, the drive parameters such as current, torque, and speed will be continuously obtained. Filtering out the high-frequency noise present in the data is the main principle of the ARIMA model. Matlab/Simulink platform ...

VHDL Design and Hardware Realization of Hybridartificial Intelligence Architecture

American Journal of Applied Sciences, Feb 24, 2014

Evolutionary Algorithms (EA) use Genetic Algorithm (GA) in many optimization problems to efficien... more Evolutionary Algorithms (EA) use Genetic Algorithm (GA) in many optimization problems to efficiently compute the function value in less time. In this study the weight optimization of the Artificial Neural Network (ANN), using the Back Propagation Network (BPN), is tested and presented with GA. The combined architecture of Neuro-Genetic (Hybrid Artificial Intelligence) approach is proposed and simulated results are provided along with device Utilization, Simulation time, Timing analysis and power analysis by using very high speed integrated circuits Hardware Description Language (HDL).

Investigation of suitability of grid-based ionospheric models for GAGAN

Electronics Letters, 2006

ABSTRACT

Quantitative Analysis of Metastasis Brain Tumor and its Area Estimation in MR Images

International Journal of Computer Applications

Metastasis brain tumor develops multiple tumors at asymmetrical location of the human brain. MRI ... more Metastasis brain tumor develops multiple tumors at asymmetrical location of the human brain. MRI Imaging is one of the prudent mechanisms to extract the tumor regions and to map the brain for diagnosing. For the better diagnosis, one must detect the tumor accurately and need to calculate the area and volume of the tumor exactly. Here in this letter, we proposed a novel resolution enhancement technique to improve the quality of MR brain image and optimized hybrid clustering with region split and merge algorithm to detect the tumor cells from the original MR images and to estimate the tumors from different locations. Simulation results show that the proposed algorithm has performed superior to conventional clustering algorithms such as Fuzzy C-means (FCM), K-Means and even optimized pillar algorithm.

Characterization and Area Estimation of MR Brain Tumor Images

International Journal of Computer Applications, 2015

Brain Tumors are detected efficiently by using the Magnetic Resonance Imaging (MRI) techniques. T... more Brain Tumors are detected efficiently by using the Magnetic Resonance Imaging (MRI) techniques. The extracted MRI image is sensitive to noise which limits the visibility of certain characteristics of the image. This unwanted noise can be disintegrated and curtailed from the original Image by using the non linear digital median filter. The intensification is achieved by using the combination of discrete wavelet transform (DWT) and stationary wavelet transform (SWT) augmented with Bi-cubic interpolation algorithm. The quality of the resolute image is analyzed with the possible static parameters. Segmentation and clustering approaches are applied on the resultant sharpened high resolution image to estimate the tumor area. The results obtained with the proposed Optimized Hybrid Clustering (OHC) algorithm are compared with the existing K-Means, Pillar K-Means and Fuzzy C-means (FCM) approaches. The tumor sensitivity and accuracy of the test parameters with the OHC approach are estimated. In-order to deliver the drug to kill the aberrant tissue, the number of tumor cells is estimated against its radius.

Fault analysis for field programmable gate array (FPGA) using phase path method

IET-UK International Conference on Information and Communication Technology in Electrical Sciences (ICTES 2007), 2007

ABSTRACT

Fault Diagnosis of VLSI Circuits Using FPGA Technology

Modelling of foF2 using neural networks at an equatorial anomaly station

The critical frequency of the F 2-layer (foF 2) is an important parameter in estimating the total... more The critical frequency of the F 2-layer (foF 2) is an important parameter in estimating the total electron content (TEC) of the ionosphere, which is necessary for predicting the ionospheric time delay in GPS applications. The foF 2 data from Ahmedabad, which is in the equatorial anomaly region, are modelled using a multilayer neural network trained with back-propagation algorithm. The IRI-2001 model together with this neural network model can be used for predicting/forecasting of the foF 2 parameter within the Indian subcontinent. The foF 2 values thus predicted can be used to estimate the critical TEC parameter.

Analysis of secure fast roaming techniques with coexistence of 802.1x

2011 2nd International Conference on Wireless Communication, Vehicular Technology, Information Theory and Aerospace & Electronic Systems Technology (Wireless VITAE), 2011

i defines the Robust Security Network Association (RSNA) establishment procedure to provide stron... more i defines the Robust Security Network Association (RSNA) establishment procedure to provide strong mutual authentications and generate fresh Transient keys (TKs) for the data confidentiality protocols. 802.11i RSNA establishment procedure consists of 802.1X, which provides high security by using dynamic Authentication and Key Management. It introduces latency due to the addition of extra messages thereby increasing the roam time. Long

A Primitive Solution of Video Super Resolution

Communications in Computer and Information Science, 2012

Implementation of Multi-hop Cluster based Routing Protocol for Wireless Sensor Networks

International Journal of Computer Applications, 2012

Clustering routing protocol provides an effective method for prolonging the lifetime of a wireles... more Clustering routing protocol provides an effective method for prolonging the lifetime of a wireless sensor network. But most of the researches care less about the communication between Cluster Head (CH) nodes [4] and Base Station (BS). This paper proposed a Multi-hop Cluster based Routing Protocol for long range transmission in wireless sensor network. The protocol consists of two parts, one is with respect to cluster management in sensor area, and the other is about the data transmission between base station and the sensor area. Simulation results show that the protocol offers a better performance than single-hop clustering routing protocols in terms of network lifetime and energy consumption when the base station is located far away from the sensing area.

Ionospheric Time Delay Variations Over a Low Latitude Station at Hyderabad

Satellite-Based Augmentation Systems (SBASs) such as the Indian GPS Aided GEO Augmented Navigatio... more Satellite-Based Augmentation Systems (SBASs) such as the Indian GPS Aided GEO Augmented Navigation (GAGAN) are being developed to aid the civil aviation in precision approach and in other operations. Accurate information on local TEC morphology is essential for developing region specific models. GPS data used in the statistical TEC variability study was recorded at NERTU, Osmania University, Hyderabad using an

Modeling of Indian foF2 data using analysis of variance

Ionosonde foF2 data of 8 stations, spread all over India, for a period of one solar cycle (1966-1... more Ionosonde foF2 data of 8 stations, spread all over India, for a period of one solar cycle (1966-1976) are used for modeling. A technique known as "Analysis of Variance(ANOVA)" is used for m deling the hourly median values of foF2. The foF2 data corresponding to a selected month for the 8 stations and for 11 years is arranged in a