N. S. Rajput

Performance and analysis of propagation models for efficient handoff in high altitude platform system to sustain QoS

In wireless environment, one of the key ingredients to provide efficient ubiquitous computing with guaranteed quality and continuity of service is the design of intelligent handoff algorithms. A handoff process can be the handoff used in order that the service can be continued uninterrupted. Efficient hand off algorithms enhance the capacity and Quality of Service (QoS) of cellular systems. QoS is the measure which defines the performance in any system. In this paper, the different path loss models have been used and then the received signal strength is calculated to determine the model that can be adopted to minimize the number of handoff. Estimation of path loss is very important in initial deployment of wireless network and cell planning. Handoff process enables a cellular system to provide such a facility by transferring an active call from one cell to another. Different approaches are proposed and applied in order to achieve better handoff service. HAP system can be considered as complementary to terrestrial cellular system being in an obstacle position. The key parameters and mathematical model is important for predicting signal coverage. Path loss models for macro cells such as Hata, Walfish-Ikegami and lee models are analysed.

HAP antenna radiation pattern for providing coverage and service characteristics

The purpose of this paper is to show the most important technique in wireless communication networks that is an antenna radiation pattern. The antenna radiation pattern represents features of the antenna radiation shape in the space. The antenna radiation patterns used for determine the shape of cell size so that the difference cell sizes have difference antenna radiation patterns. The quality of coverage is depending on the cell size and QoS is depending on the coverage area which can provide via HAPs. Therefore, the antenna radiation pattern plays the most important role for HAPs coverage. The study focuses on the manner of cells or tier provided via HAP and the probability of services. If the distance between cells decreases, the number of cells increases that means the large number of tiers are used as well as the network performance will be affected by decreasing the distance between cells. Using steerable antenna is able to vary for providing constant coverage and improve the QoS. Since a steerable antenna is used on the HAP for allowance HAPs to be deployed in the different parts of the sky while the antennas boresight are still pointing at the desired coverage area. For each antenna pattern result is shown when Single HAP is considered in this study.

Computational scalability with Apache Flume and Mahout for large scale round the clock analysis of sensor network data

In this paper, a typical scenario has been considered wherein gas sensor array responses from a WAN deployed sensor network are being received hourly, 24×7. From every sensor node, we are retrieving Static as well as Dynamic Responses with 16 sensing elements generating a .csv file of 9 MB size. Considering 1000 sensor nodes, the data received at the Hadoop Cluster at our Data Centre would be about 9 GB, which can be even more if more number of nodes, over larger geographical area and/or higher density of nodes is considered. Hence, (i) to receive and store such a huge data from a sensor network and (ii) to analyse the received data, we explored the suitability of Apache Flume and Apache Mahout to deliver high performance computational scalability on Hadoop Distributed File System. In this work, an implementation methodology for realization of such a scalable system has been presented by considering a sensor network for air pollution observation over a large geographical area, as an example.

Crop parameter estimation of Lady finger by using different neural network training algorithms

Now a days ANN has became an important tool in crop yield prediction and crop parameter estimation. But very few reported work is available to estimate the crop parameters by using suitable ANN Training algorithms. In the present study the crop parameters of interest are soil moisture, leaf area index and biomass were estimated using ground truth microwave scatterometer data and ANN. Two training algorithms Levenberg-Marquardt (TRAINLM) and Scaled conjugate gradient training algorithm (TRAINSCG) were used to estimate the crop parameters. The estimation of parameters with minimal error obtained with the test data confirms the usefulness of our work. Training algorithm TRAINLM shows better result in comparison to TRAINSCG. This work suggests that the ANN model with training function TRAINLM and transfer function PURELIN is a promising alternative to estimate the crop parameters. The main advantage of ANN approach as estimator is that it has the potential for world wide coverage.

Tethered balloon technology for telecommunication, coverage and path loss

The Tethered balloon is new technology for telecommunication that can overcome the limitation of terrestrial system and satellite system due to demand for high capacity in telecommunication. Tethered balloon provides large coverage area with line of sight, which needs large number of base stations for coverage with terrestrial system; also reduce the delay time of the transmission compared to satellite system. Tethered balloon technology is studied in this paper for mobile communication purposes and some calculations are performed to show how path loss, coverage area and height of Tethered balloon are related. The propagation model Hata model is used.

Disaster Coverage Predication for the Emerging Tethered Balloon Technology: Capability for Preparedness, Detection, Mitigation, and Response

OBJECTIVE A disaster is a consequence of natural hazards and terrorist acts, which have significant potential to disrupt the entire wireless communication infrastructure. Therefore, the essential rescue squads and recovery operations during a catastrophic event will be severely debilitated. To provide efficient communication services, and to reduce casualty mortality and morbidity during the catastrophic events, we proposed the Tethered Balloon technology for disaster preparedness, detection, mitigation, and recovery assessment. METHODS The proposed Tethered Balloon is applicable to any type of disaster except for storms. The Tethered Balloon is being actively researched and developed as a simple solution to improve the performance of rescues, facilities, and services of emergency medical communication in the disaster area. The most important requirement for rescue and relief teams during or after the disaster is a high quality of service of delivery communication services to save peoples lives. RESULTS Using our proposed technology, we report that the Tethered Balloon has a large disaster coverage area. Therefore, the rescue and research teams are given higher priority, and their performance significantly improved in the particular coverage area. CONCLUSIONS Tethered Balloon features made it suitable for disaster preparedness, mitigation, and recovery. The performance of rescue and relief teams was effective and efficient before and after the disaster as well as can be continued to coordinate the relief teams until disaster recovery. (Disaster Med Public Health Preparedness. 2018;12:222-231).

Development of electromagnetic approach for early breast tumor detection

Survival from breast cancer strongly linked to the size of the tumor at the detection stage. Thus, the early stage detection of tumor of size as minimum as 1.0 mm radius is of great research interest. Currently used techniques for breast cancer detection fails in 10-30% cases and it gives any positive results when the tumor grows in to a size more than 10.0 mm, this reduces the possibility for an early stage detection and thus the survival rate. Thus, in this paper an alternate method of breast cancer detection through microwave imaging is studied. A dielectric mixing model is used to compute the dielectric constant of the breast tissue with and without the malignant tissue and the proposed model is verified through the simulation in CST. Free space transmission and metal back method are used for the measurement of dielectric constant of the phantom containing one, two, three and four tumors of radius 1.0 mm each. The proposed dielectric mixing model can be applied to detect the changes in the dielectric constant of the tumor affected tissue of radius 1.0 mm which is not possible through any other existing methods.

Class wise optimal feature selection for land cover classification using SAR data

Conventional methods for classifying SAR data, such as H-α decomposition, Wishart classifier etc. are quite complex and classifies data only on the basis of polarimetric information. With the advent of distinct feature types, their role in land cover classification using SAR data could be analysed. For the sake of classification, researchers are extracting and combining several features in order to obtain the best attainable accuracy. But the usage of several feature type is not only increasing the computational complexity, but also the salience of each of the feature type remains unhighlighted. Hence, it became difficult to analyse that which feature type are best suitable for classification and selection of suitable features for land cover classification is challenging as each feature has its own significance level. Therefore, in this paper class wise, optimal feature selection for land cover classification has been performed using SAR data. For optimal feature selection, four types of feature set polarimetric features, texture features, color features and wavelet features have been examined. For class wise feature subset selection separability index criteria and classification results obtained using Naive Bayes classifier has been utilized. With the proposed methodology overall 10 features has been selected among the total 37 feature analysed with fine land cover classification accuracy of 91%.

Pattern analysis of MiniSAR data for differentiation of icy craters in lunar surface

Classification of water ice region on lunar surface with Mini-SAR data is quite challenging. Therefore, a probability density function (pdf) based pattern analysis approach has been applied to classify lunar surface. This paper represents the pattern analysis approach to fit data points to a distribution function for understanding the distribution behaviour of Mini-SAR data which helps in developing a method based on density functions to differentiate two types of craters namely icy (type-I) and non-icy (type-II) craters. Circular polarization ratio (CPR) is a very important parameter in study of lunar surface. More specifically, the criterion CPR>1 is used to determine possible presence of water-ice deposits on lunar surface So, its important to study distribution behaviour of CPR pixels and to determine best fitted distribution function representing this behaviour. Therefore, in this paper, pattern analysis techniques have been applied to differentiate two crater types based on the distribution behaviour of CPR. The best fitted function for CPR has been obtained as Generalized Extreme Value function which clearly differentiate type-I and type-II craters.

Critical analysis of deorientation effect on various land covers: An application of POLSAR data

The aim of model based decomposition is to express coherency matrix in terms of various scattering components (like, volume, surface, double bounce, and helix). In spite of this decomposition, ambiguity occurs in scattering response from various land covers, like urban and vegetation. Deorientation process is believed to remove this ambiguity. However, there is a need to check whether decomposition methods and deorientation helps in identification of different land covers in terms of scattering mechanisms. To fulfil this task, in this paper, a study of four D decomposition methods with and without deorientation has been performed. The purpose of this study is to visualize the effect of deorientation on various land covers like, urban, vegetation, bare soil, water, and subsidence, in Jharia region, one of the major coal fields of India. Both visual and quantitative analysis have been performed for comprehensive evaluation of deorientation effect.