Measuring the Influence and Intensity of Customer’s Sentiments in Facebook and Twitter

Organisations these days are actively using social media platforms to engage with potential and existing customers and monitor what they say about the organisation’s product or service. The most important area within social media monitoring lies in how to gain insight for sentiment analysis. Sentiment analysis helps in effective evaluation of customer’s sentiments in real time and takes on a special meaning in the context of online social networks like Twitter and Facebook, which collectively represent the largest online forum available for public opinion. Sentiment Analysis is not about retrieving and analyzing the analytics purely on the basis of positive, negative or neutral sentiment. It is imperative to assess the influencers of the sentiments in terms of Retweet and Share option used by them on Twitter and Facebook platform respectively. Measuring the intensity is other important aspect of sentiment analysis process. What kind of nouns, adjectives, verbs and adverbs are used in the opinion across the Twitter and Facebook platform matters as well since it exhibits the intensity of the underlying emotion in the text written. This study was conducted to propose a framework to identify and analyse the positive and negative sentiments present in Twitter and Facebook platforms and an algorithm was prepared to measure the intensity and influence of the positive, negative sentiment in particular using the document and sentence level analysis technique

Simulation of Planar Inverted F Antenna for On-Body and free space Communication

The expansion of recent wireless communications devices has put significant Compression on the antenna performance, as the size of the device has decreased in parallel to the increase in the number of communications systems supported by a single terminal. The Body Area Network (BAN) helps constant monitoring of Human health with updates of medical records through Internet. In this paper, we propose an on-body and free space performance of Planar Inverted F antenna which operates in Industrial scientific and Medical (ISM) frequency band at 2.45 GHz. The planar inverted –F antenna is popular for portable wireless devices because of its low profile, small size, and built-in structure This antenna is designed to achieve better Specific absorption rate. Other field parameters like Gain, Directivity, Return loss and Radiation have been evaluated on the body and on free space antenna with FEM based software HFSS ver. 13.0

The study of demographic profile of patients of senile mature cataract attending the eye OPD of GMC Jammu, India

Background: Age related cataract also called as senile cataract is the commonest type of acquired cataract affecting people over the age of 50 years. In developing countries like India, many times patients with cataract report to the hospitals very late, when it has become mature. Keeping this in mind this study was undertaken to study the demographic profile of patients of senile mature cataract attending the OPD of GMC Jammu and to see if there is correlation between demographic factors and time of seeking medical attention.Methods: This study was conducted on 41 patients of senile mature cataract who attended OPD of GMC Jammu from August 2019 to November 2019. All patients were subjected to detailed history taking and ocular examination. Socio-economic status and education level of all patients was assessed. All patients were admitted and underwent cataract surgery with IOL implantation.Results: In study the mean age of patients was 62.46 years with 58.53% patients being females. Majority of patients were from rural background with low socio-economic status and low education levels.Conclusions: From this study we concluded that female sex, low socio-economic status, comorbidities and lower literacy levels are associated with patients seeking medical attention for cataract at an advanced stage

Newly engineered nanoparticles as potential therapeutic agents for plants to ameliorate abiotic and biotic stress

Food scarcity is a global concern that is growing every year. Biotic stress factors like pathogenic fungi, bacteria, viruses, and nematode pests aggravate the situation by imparting detrimental effects on crops by unfavourably affecting their growth and yield. Abiotic stress factors include extreme heat and cold, drought, high salinity, floods, and heavy metal toxicity. Annually, millions of hectares of agricultural land worldwide are lost to these stress elicitors. To combat these stress factors, plants have developed strong defense mechanisms, including protective physical barriers, the overexpression of certain genes, and the production of secondary metabolites. Nanotechnology offers numerous novel and sustainable substitutes for conventional agriculture due to its potential uses in this field. Newly engineered nanoparticles (NENPs) are synthesized nanoparticles that are 1-100 nm in size and possess unique properties that help plants combat abiotic and biotic stress factors efficiently. NENPs are designed to ameliorate stress, alleviate nutrient inadequacy in soil, improve plant nutritional value, and overall boost crop productivity. This review illustrates the applications of various NENPs, which help plants cope with biotic and abiotic stresses. It highlights the effective induced changes that develop in the morphology, physiology, and biochemistry of different plants under stress and the role of NENPs. This review also highlights the toxic and deleterious effects of NENPs on the soil when used in higher doses and concludes with the prospects of NENPs in agriculture

Impact of Piriformospora indica, Pseudomonas species and Mesorhizobium cicer on growth of chickpea (Cicer arietinum L.)

The present study was conducted to examine synergistic interactions among Piriformospora indica (PI) with potential plant growth promoting rhizobacteria (PGPR) and Mesorhizobium cicer (LGR33, MR) in two chickpea (Cicer arietinum L.) varieties viz. desi PBG1 and kabuli BG1053. Different PGPR species were used viz. native isolates of Pseudomonas argentinensis (LPGPR1), Pseudomonas sp. (LPGPR2) along with national check Pseudomonas sp. (LK884). Compatibility of MR, PI and differentPseudomonas spp. was studied by streak assay method and growth of fungal pellicle in-vitro. Consortium of MR+PI+LPGPR1 (0.605 g dry weight fungal pellicle/100ml nutrient broth) was found as the best compatible treatment. In vivo the synergistic effect of consortia was studied for improving dry weight of roots, nutrient acquisition, colonization and stress tolerance ability in chickpea. Significant improvement in dry weight of root was observed with MR+PI+LPGPR1 (1.316 g plant-1) in comparison to MR alone treatment (0.980 g plant-1) at 90 days after sowing (DAS). Percentage colonization of P.indica improved significantly with consortium MR+PI+LPGPR1 (75.5 and 78.3 %) treatment at 90 DAS. All the treatments significantly improved total soluble sugar content (12.2-26.9 %); amino N content (1.36-1.80 fold) and stress tolerance ability (4-6 fold) over the MR alone treatment. Reducing sugar content significantly improved with MR+PI+LPGPR1 (0.62 and 0.79 mg mL–1) over MR alone (0.42 and 0.58 mg mL–1) treatment in desiPBG1 and kabuli BG1053 chickpea, respectively. The tripartite combination MR+LPGPR1+PI can be explored as potent biofertilizer for improvment in chickpea productivity

The Role of the District Public Health Nurses: A Study from Gujarat

The role of District Public Health Nurses (DPHN) and District Public Health Nurse Officers (DPHNOs) as supervisors of the Public Health nursing and midwifery staff in a district was investigated. Thirteen DPHNs and DPHNOs from six districts selected from six geographic zones of Gujarat were observed for one week using the time motion method. Their activities and time spent were noted and the DPHNs/DPHNOs and their supervisors were interviewed. The role of the DPHNs has reduced over the years because they have not been assigned new roles with change in programmes and policies. Most of the DPHNs have training for clinical work in hospitals. Their 10 month training to qualify for PHN is inadequate to develop knowledge and skills in public health. There is a gap between their training and posting due to delays in government procedures of promotion. The DPHN/DPHNOs spend majority of their time in the office (49%) where they have a limited role. Their supervisory role for nurses and midwives has lost its importance. They spend about 1/3rd of their time in field supervision mostly visiting centres accessible by public transport as they do not have an allotted government vehicle. As they do not submit any field report, there is no follow-up action from their visit. Nevertheless they seem to have an important role in solving problems of field workers as they are mediators between the district and peripheral facilities. To conclude the DPHNs are under utilized which affects the quality of maternal and child health services in the district.

SSOPS based Solution to Improve QoS in VANET

Vehicular Ad-hoc Networks (VANETs) is an emerging network technology derived from ad-hoc networks. This paper provides the state-of-the-art of VANETs and provides optimum proposal by improving Quality of Service (QoS.) Today, wireless systems are preferred over wired systems and these are gaining popularity as it provides wireless connectivity to the users irrespective of their geographic position, VANET is one of them. VANETs are installed to minimize the risk of road accidents and to improve passenger comfort by permitting the vehicles to exchange various types of data. In this paper, the Signal Strength based Optimum Path Selection (SSOPS) based solution on how to mitigate the QoS issues that exists while using the existing methods are discussed. Moreover, the solution has been tested using NS2 software using various parameters

N-grams Based Supervised Machine Learning Model for Mobile Agent Platform Protection against Unknown Malicious Mobile Agents

From many past years, the detection of unknown malicious mobile agents before they invade the Mobile Agent Platform has been the subject of much challenging activity. The ever-growing threat of malicious agents calls for techniques for automated malicious agent detection. In this context, the machine learning (ML) methods are acknowledged more effective than the Signature-based and Behavior-based detection methods. Therefore, in this paper, the prime contribution has been made to detect the unknown malicious mobile agents based on n-gram features and supervised ML approach, which has not been done so far in the sphere of the Mobile Agents System (MAS) security. To carry out the study, the n-grams ranging from 3 to 9 are extracted from a dataset containing 40 malicious and 40 non-malicious mobile agents. Subsequently, the classification is performed using different classifiers. A nested 5-fold cross validation scheme is employed in order to avoid the biasing in the selection of optimal parameters of classifier. The observations of extensive experiments demonstrate that the work done in this paper is suitable for the task of unknown malicious mobile agent detection in a Mobile Agent Environment, and also adds the ML in the interest list of researchers dealing with MAS security