Sparse Matrix Representation for Web Opinions

Due to the advancement of Web 2.0 technologies, a large volume of Web opinions is available on social media sites such as Web forums and Weblogs. These technologies provide a platform for Internet users around the world to communicate with each other and express their opinions. Web opinions are short and sparse text messages with noisy content. In this paper, we are using a sparse matrix representation for web opinions and defining a preprocess way for it. Here, we are proposing an algorithm for matrix generation from vector of thread2019;s. Due to this representation, we use opinions in efficient way

Feto-maternal outcome in subject undergoing epidural labour analgesia with Ripovacaine and Fentanyl

Background: Epidural anaesthesia is regional anaesthesia that blocks pain in particular region of the body. The present study was done to observe the effect of epidural analgesia and active management of labour on duration of labour and mode of delivery.Methods: Main source of data were Primigravida inpatients from hospitals attached to JJM Medical College, Davangere from October 2016 to September 2017. It was a clinical cross-sectional study.Results: It was observed that duration of labour was comparatively less in epidural group than control group. There was no significant increase in duration of II stage of labour in epidural group. There was no increase in both the instrumental delivery rate and caesarean section rate and also noted higher newborn APGAR score rate in parturient who received epidural analgesia.Conclusions: The present study showed that there is no increase in the duration of labour or any increase in the rate of instrumental delivery or caesarean section in parturient receiving epidural analgesia, instead, there is a downward trend in all the above outcomes

A Coupled Compressive Sensing Scheme for Unsourced Multiple Access

This article introduces a novel paradigm for the unsourced multiple-access communication problem. This divide-and-conquer approach leverages recent advances in compressive sensing and forward error correction to produce a computationally efficient algorithm. Within the proposed framework, every active device first partitions its data into several sub-blocks, and subsequently adds redundancy using a systematic linear block code. Compressive sensing techniques are then employed to recover sub-blocks, and the original messages are obtained by connecting pieces together using a low-complexity tree-based algorithm. Numerical results suggest that the proposed scheme outperforms other existing practical coding schemes. Measured performance lies approximately $4.3$~dB away from the Polyanskiy achievability limit, which is obtained in the absence of complexity constraints

ANTIMYCOBACTERIAL ACTIVITY OF CRUDE EXTRACTS PRODUCED BY BACILLUS SP. ASSOCIATED WITH ENTOMOPATHOGENIC NEMATODE

Objective: The World Health Organization estimates that about 8 to 10 million new Tuberculosis (TB) cases occur annually worldwide and its incidence is currently increasing. There are two million deaths from TB each year. The global threat of tuberculosis demands the search for alternative antimycobacterial drugs. The aim of the present study was to determine the antimycobacterial activity of nine crude extracts from a Bacillus sp. N strain associated with entomopathogenic nematode Rhabditis (Oscheius) sp. Methods: The liquid media for fermentation was prepared in TSB alone, LB alone and TSB + LB (1:1) supplemented with six different carbon sources (fructose, maltose, dextrose, mannitol, sucrose and lactose) and after fermentation crude extract was extracted using ethyl acetate. The minimum inhibitory concentration (MIC) of extracts was determined using the broth dilution method on middle brook 7H11 against M. tuberculosis H37Rv. The cytotoxicity of the extracts was determined by 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) assay against VERO cell line. Results: Out of nine extract tested only two recorded activity and significant activity was recorded by TSB+LB+lactose, followed by TSB+LB+fructose. These two extracts were nontoxic to the normal cell line. Conclusion: Purification of these extract will get pure compounds with antimycobacterial activity in future

Machine Learning Approach for Prediction of the Online User Intention for a Product Purchase

The deployment of self-learning computer algorithms that can automatically enhance their performance via experience is referred to as machine learning in ecommerce and is a crucial trend of the retail digital transformation. Machine learning algorithms can be unambiguously trained by analysing big datasets, identifying repeating patterns, relationships, and anomalies among all of this data, and creating mathematical models resembling such associations. These models are improved when the algorithms analyse ever-increasing amounts of data, providing us with useful insights into specific ecommerce-related events and the links between all the variables that underlie them. A tool that has been quite effective in studying current affairs, predicting future trends, and making data-driven decisions. The present work investigates the implementation of machine learning algorithms to predict the user intention for purchasing a product on a specific store's website. An Online Shoppers Purchasing Intention data set from the UC Irvine Machine Learning Repository was used for this investigation. In this study, two classification-based machine learning algorithms i.e. Stochastic Gradient Descent (SGD) algorithm and Random Forest algorithm were used. SGD algorithm was used for first time in prediction of the online user intention. The results showed that the Random Forest resulted in the highest F1-Score of 0.90 in contrast to the Stochastic Gradient Descent algorithm

Assessment of water quality and the related instrumental techniques

To assess and monitor the quality of water/water bodies. required observations range from simple colour. odour. presence of suspended matter to complicated physical analysis of spectral image for surface mapping of natural water bodies for colour and temperature and chemical analysis for natural and man-made organics, inorganics and radio nuclides. The routine instruments to meet the above requirement comprise of pH meters for acidity and alkalinity measurements, nephelometers fur turbidity, conductivity meters for salt content, spectrophotometers for nutrients and major elements, atomic absorption spectrophotometers for metals including toxic ones. ion selective electrodes for oxygen and halides; gas chromatography for organic contaminants/traces. scintillation and Geiger-Mueller counters for radio nuclides measurements, Analytical methods pertaining to the water quality analysis and the instruments employed were briefed