USE OF LIBRARY AND INFORMATION RESOURCES IN SELECTED PHARMACY COLLEGES OF KARNATAKA

The purpose of this paper is to analyse the use of library resources by students and faculty members in selected pharmacy colleges of Karnataka. This study adopted survey method and questionnaire tool used to collect primary data from the respondents. A well-structured questionnaire has been circulated among 691 faculty members and students whereas 686 respondents were responded. Based on the findings, this study recommended that, libraries need to take necessary steps in order to visit users on daily basis; library should attract users to use variety of resources other than books and periodicals. Library should promote the use of documents such as Audio-visual material, e-resources and theses and dissertations etc. The study also recommended that, the library need to procure relevant documents in order to support their curriculum, and need to arrange the documents in a helpful manner. Libraries need to purchase sufficient numbers of multiple copies; library professionals should assist the users and need to give proper orientation to use various resources and services. Further, this study suggested the college authority should change their policy to keep the library in open access and must provide state- of- art ICT tools to the library

Chip equalized adaptive rake receiver for DS-CDMA UWB systems

Conventional Rake receiver is a popular and effective method of utilizing the diversity offered by a DS-CDMA and multipath communication channel. The proposed Rake receiver is useful for suppression of multiple access interference in a multipath channel. The receiver works on chip level equalization on each Rake finger to cancel multi-access interference. Simulation results show that the convergence, diversity gain and bit error probability performance of the proposed receiver is much better than conventional adaptive Rake receiver in multipath channels

Frequency and time hopping PPM UWB multiple access communication scheme

In this paper we propose frequency and time hopping pulse position modulation (FTH-PPM) ultra wideband (UWB) for multiple access communications.We have derived and investigated the bit error probability for the multi-user synchronous transmitter case in multipath channels with Additive White Gaussian Noise (AWGN). Simulation results show that bit error probability performance of FTH-PPM UWB out performs the time hopping pulse position modulated (TH-PPM) UWB system. It also show that multiuser capacity of FTH-PPM UWB system is much better than TH-PPM UWB system

Medicine Research in India: A Scientometric Assessment of Publications during 2009 – 2018

The purpose of this paper is to qualitative analyse of medicine research output using select scientometric indicators with the aim of identifying top preparing countries, subject subthemes, organisations, authors and journals in the area. The present study has examined 29153 publications in medicine research, the present study deals with the Assessment of Indian medicine research output as reflected in Web of Science (WOS) database for the period 2009 to 2018 for identifying the research output in the field of medicine literature. It also provides a comparative evaluation and performance of different types of scientometric indicators, such as number of publications, number of citations, relative growth, doubling time, activity index and collaboration from India. The Indian medicine research has increased exponentially over the last decade

Pregnancy with pancytopenia: an observational study

Background: Pancytopenia is the reduction in all three major cellular elements of blood; hence it is the simultaneous presence of anaemia, leukopenia and thrombocytopenia. Pancytopenia is associated with many maternal and foetal complications during pregnancy like maternal sepsis, postpartum haemorrhage, pre-eclampsia and preterm labour, IUGR and intrauterine foetal demise.Methods: The study was conducted at BLDE (Deemed to be) University, Shri B. M. Patil Medical College Hospital and Research Centre. It’s an observational study done from November 2019-April 2020. The participants enrolled in the study were subjected for further clinical and laboratory evaluation and followed for feto-maternal outcome.Results: The incidence of pancytopenia with pregnancy in this study was 3% and all the patients were vegetarian by diet along with vitamin B12 and folic acid deficiency. They were associated with different maternal and foetal complications.Conclusions: Proper dietary counselling and well-balanced dietary plans even with plant originate food can prevent the micronutrients deficiency and avoid the deleterious consequences like pancytopenia

Abnormality Detection in Diverse Network Utilizing Machine Learning

It exhibits a versatile framework for high-throughput ongoing investigation of heterogeneous information streams. The engineering empowers incremental advancement of models for prescient investigation and inconsistency recognition as information touches base into the framework. Interestingly with cluster information handling frameworks, for example, Hadoop that can have high expectancy, the design considers ingest and investigation of information on the fly, in this way distinguishing and reacting to strange conduct in close ongoing. This convenience is imperative for applications, for example, insider danger, monetary extortion, and system interruptions. It exhibit a use of this framework to the issue of identifying insider dangers, to be specific, the abuse of an association's assets by clients of the framework and present after effects of the investigations on an openly accessible insider risk dataset

Classification of Diabetic Retinopathy using Convolutional Neural Network

Diabetic Retinopathy is a scenario in medical field which leads to the rise of damage of blood vessels in the retina which is due to diabetes mellitus. The suitable detection for this kind of problems and care to be done immediately in order to prohibit loss of sight in a person. Presently, diagnosing Diabetic Retinopathy manually is a time- consuming process where they require experienced clinicians to examine the digital-colored fundus images. Here, we have proposed a machine learning technology using Convolutional Neural Network (CNN) approach which has emerged as an operative productive tool in medical image examination for the classification and detection of Diabetic Retinopathy (DR) in real-world. The different layers which are used to detect the brain tumor are conv2D, Activation, MaxPooling2D, Dense and Flatten. The set used here considers 750 retinal images, with 600 training images and the test set considers 150 images with the accuracy of 82.75% which ran for 80 epochs