Establishing a Wireless Sensor Network to Monitor the Temperature in a two storied building

The advancement in information technology and the need for large-scale communication infrastructure has triggered the era of Wireless Sensor Networks (WSNs). Sensor network is a collection of sensor nodes connected wirelessly to one another to gather information about the surrounding environment. In this paper a WSN testbed is established using Texas instruments sensor nodes to monitor the temperature in a two storied building

Link Quality Based Power Efficient Routing Protocol (LQ-PERP)

Recent years have witnessed a growing interest in deploying infrastructure-less, self configurable, distributed networks such as Mobile AdHoc Networks (MANET) and Wireless Sensor Networks (WSN) for applications like emergency management and physical variables monitoring respectively. However, nodes in these networks are susceptible to high failure rate due to battery depletion, environmental changes and malicious destruction. Since each node operates with limited sources of power, energy efficiency is an important metric to be considered for designing communication schemes for MANET and WSN. Energy consumed by nodes in MANET or WSN can be reduced by optimizing the internode transmission power which is uniform even with dynamic routing protocols like AODV. However, the transmission power required for internode communication depends on the wireless link quality which inturn depends on various factors like received signal power, propagation path loss, fading, multi-user interference and topological changes. In this paper, link quality based power efficient routing protocol (LQ-PERP) is proposed which saves the battery power of nodes by optimizing the power during data transmission. The performance of the proposed algorithm is evaluated using QualNet network simulator by considering metrics like total energy consumed in nodes, throughput, packet delivery ratio, end-to-end delay and jitter

Performance Study of Adhoc on-Demand Link Quality Aware Route Search Protocol (AO-LQARSP)

A Wireless Sensor Network (WSN) is a network with few tens to thousands of small devices called sensor nodes which are connected wirelessly and involve in communicating the data. WSNs have generated tremendous interest among researchers in recent years because of its potential usage in wide variety of applications. The sensor nodes in WSNs have scarce power; they work in harsh and unattended environments which initiates the need for a better and more reliable routing path to send data. In this paper a routing protocol is proposed to select the route based on better signal strength conditions using Link Quality Indicator of the received signal for IEEE 802.15.4 standard. The performance of the proposed routing protocol is compared with standard reactive routing protocol Adhoc On-demand Distance Vector (AODV) with metrics like total packets received, throughput, total bytes received, average end-to-end delay and average jitter and total energy consumed for various node density scenarios

Machine Learning Algorithm to Identify Hesitancy Towards Covid-19 Vaccination Among the Rural Citizens Under E-Governance Initiatives

The Indian Government has taken massive initiatives to control the pandemic virus of COVID-19. Recently, the Government has decided to begin the process of a large-scale vaccination programme to create an end to the crisis due to COVID-19. However, vaccination is found to be the major solution as suggested by various health care experts to stop the widespread of this deadly virus, hesitancy towards getting vaccinated is found to be more in the rural villages of India. The process of getting vaccinated was not made compulsory by the government, but still there exists skepticism in minds of rural citizens towards COVID-19 vaccination. Text Analytics has been implemented to identify the exact emotions among rural citizens towards COVID Vaccinations. Hence the present research study has identified the major reasons for hesitancy towards getting vaccinated for COVID-19 using machine learning techniques. The researchers of the current study have also measured the emotions and signs of sentiments of the rural citizens on COVID-19 vaccination

Evaluation of screening efficacy of IL6, IL8, CRP and salivary progesterone in predicting preterm pregnancy

Background: According to WHO preterm birth defined as births occurring before completion of 37 weeks, in a pregnancy beyond 20 weeks of gestation. As reported by W.H. O preterm birth has incidence of about 9.6% of all the live births, preterm births have high neonatal morbidity and mortality. In this review we look at association between CRP, IL6, IL8 and salivary progesterone in predicting the preterm delivery. Methods: A hospital based prospective study to be conducted in a group of 100 women of 20- 24 weeks of gestation, they were analysed for IL6, IL8, CRP and salivary progesterone and followed them till delivery. Results: On assessment of the biomarkers to predict the preterm and term pregnancy, we assessed for the blood level of CRP, IL6, IL8 and salivary progesterone among the pregnant women at 20-24 weeks of gestation and followed till the pregnancy outcomes. Among which 46% were with preterm pregnancy and 54% with term pregnancy during delivery. Among them, 20% had the previous preterm pregnancy and 80% were not. We found 70% with normal vaginal delivery, 24% with emergency LSCS and 6% with elective LSCS. Conclusions: The present study documented the significant higher efficacy of IL6, IL8, CRP and salivary progesterone in predicting the preterm pregnancy. Progesterone levels in the saliva was markedly lower among the pregnancy with preterm delivery compared to term delivery outcome. The fetal outcome among the preterm delivery was significantly with morbidity and mortality compared to term delivery. The ROC curve showed the estimation of IL6, IL8, CRP and salivary progesterone at 20-24 weeks of gestation can predict the outcome of preterm pregnancy

Automatic license plate recognition using pre-processing methods

In this paper, we present a method to automatically detect a vehiclersquos number by usingnbsp pre-processing techniques. We also include image enhancement techniques, edge detection methods, morphological methods including image filling and some techniques like image filling. This paper provides an advantage of effective detection of more number of vehicles compared to the detection using edge detection methods.nbs

Cultural and morphological studies on Ponnampet leaf and neck blast isolates of Magnaporthe grisea (Herbert) barr on rice (Oryza sativa L.)

The study was carried out to standardize the optimal growth, sporulation and production of perfect stage of pathogen on different media. Among different media used such as Potato dextrose Agar (PDA), Oat meal Agar, Ragi flour agar, yeast extract + 2% soluble starch, Host extract + 2% soluble sucrose agar, Potato dextrose agar + Biotin + Thiamine and Rice flour agar, Oat meal agar and potato dextrose agar was found to be best media for radial growth and sporulation of M. grisea. Maximum conidia length (9.46?m) and breadth (7.36?m) was recorded in Oat meal agar followed by Potato dextrose agar and least conidia length (6.15 ?m) and breadth (5.11 ?m) was recorded in ragi flour media after 20 days of inoculation. Conidial size varied in leaf and neck blast isolates, the maximum mean colony diameter of 88.00mm and 89.16mm in neck and leaf blast was recorded in Oat meal agar respectively. The maximum sporulation mean index was observed in Oat Meal agar of 3.15 ?m in leaf and 3.20 ?m in neck blast was recorded. The best growth of the pathogen was recorded at optimum pH range from 6.0 - 7.0 and temperature of 27oC. Therefore oat meal agar media was found to be best among all the media used for growth, sporulation, conidial size and colony characters of M. grisea

Prescription pattern of anti-hypertensive drugs among hypertensive patients at district hospital

Background: To conduct a prospective observational study on prescribing pattern of anti-hypertensive drug in the department of general medicine in Government District hospital, Gulbarga. In this study it was aimed to evaluate the current practice of anti-hypertensive drug by comparing with JNC-8 guidelines in population. Objectives: The objective of our study is to determine the prescription pattern of antihypertensive drugs and adherence to JNC8 guidelines and to find out the most prescribed anti-hypertensive drugs. Methods: A Prospective Observational Study of 06 months was conducted. Undertaken 174 patients data collection form of all the patients of inpatient department of age 18 ≥ years of hypertensive with or without co-morbidities. Result: The results of this analysis suggests that out of the total 174 hypertensive patients included in the study, 92 patients were males while 82 patients were females, indicating the higher prevalence of hypertension in male population than in female population, that is 10% higher prevalence in males than in females. Out of the total study subjects, 169 hypertensive patients were found to have other co morbid conditions. Considering out of the total 174 patients, majority of the patients received monotherapy (129) while remaining patients receiving the Combinational therapy are 45. However in the case of overall utilization pattern of antihypertensive agents, CCBs are the most frequently prescribed class of drugs, followed by ARBs , BBs and finally ACEIs