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BACKGROUND Preterm labour is one of the most challenging obstetric complications encountered by obstetricians. Preterm delivery affects one in ten births (11%) and even greater in developing countries. In the United States, preterm birth accounts for approximately 2/3rd of infant deaths. Prematurity is the cause of 80-85% of neonatal morbidity and mortality in developing countries. In India, prematurity is associated with 75% of perinatal mortality. Maternal infections precipitate preterm labour. One of the most important aetiology of preterm labour and preterm premature rupture of membranes is maternal lower genital tract infection and this leads to increased neonatal infections. The objectives of the study were- 1) To find out the prevalence of vaginal infection in preterm labour and preterm premature rupture of membranes. 2) To find out the incidence of neonatal sepsis and its relationship with vaginal swab culture in preterm premature rupture of membranes and preterm labour. 3) To identify common organisms in high vaginal swab culture and its antimicrobial sensitivity. MATERIALS AND METHODS This is a prospective observational study conducted for 12 months from October 2016 to October 2017, in the department of Obstetrics and Gynaecology, Government Medical College, Kottayam. In a previous study by Taralekar Vaishali et al, incidence of genital tract infection in preterm labour was about 59%. For the present study, a conservative estimate of 50% is used in sample size calculation and it is n=105. Statistical analysis is done by using SPSS software. RESULTS Out of the 105 subjects included in this study, 74 were diagnosed with preterm premature rupture of membranes (70.5%), and 31 (29.5%) with spontaneous preterm labour. Majority were in the age group of less than 22 years. Regarding gestational age, 61.9% came under late preterm gestation, majority being primigravidae. Of the 20% positive cultures, most common organism isolated was E.coli (8.6%) and prevalence of genital infection in spontaneous labour and preterm premature rupture of membranes were 16.1% and 21.6% respectively. Most of the isolated organisms were resistant to Ampicillin and sensitive to Cephaperazone-Sulbactum. In this study, 34.3% had neonatal sepsis, 51.4% needed neonatal intensive care and 15.2% succumbed to neonatal death. In 21 positive swab cultures, 88% had neonatal sepsis and 47% died during neonatal period. Relation between the birth weight and neonatal sepsis was statistically significant. CONCLUSION Maternal genital tract infection is one of the causes of preterm labour and preterm premature rupture of membranes. The dictum “prevention is better than cure” applies very well to the management of preterm birth.

Natural Language Processing NLP is the one of the major filed of Natural Language Generation NLG . NLG can generate natural language from a machine representation. Generating suggestions for a sentence especially for Indian languages is much difficult. One of the major reason is that it is morphologically rich and the format is just reverse of English language. By using deep learning approach with the help of Long Short Term Memory LSTM layers we can generate a possible set of solutions for erroneous part in a sentence. To effectively generate a bunch of sentences having equivalent meaning as the original sentence using Deep Learning DL approach is to train a model on this task, e.g. we need thousands of examples of inputs and outputs with which to train a model. Veena S Nair | Amina Beevi A "Suggestion Generation for Specific Erroneous Part in a Sentence using Deep Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23842.pdf

With the popularity of social media such as Facebook and Flicker, users can easily share their registration records and photos during their travels. When planning a trip, users always have a particular preference for their trip. The system does not restrict users to limited query options such as location, activity, or time period , but rather treats any text description as a keyword for personalized needs. Previous work has elaborated on excavating and arranging existing routes from check in data. In order to meet the needs of the auto travel organization, the system claims that more POIs should be extracted. Therefore, this paper proposes an efficient keyword based representative travel route framework that uses knowledge from historical flow records and social interactions of users. Explicitly, the system designs a keyword extraction module to classify POI related tags so as to effectively match the query keywords. The system further designed a route reconstruction algorithm to build route candidates that meet the requirements. In order to provide appropriate search results, explore the representative Skyline concept, the Skyline route, which best describes the tradeoffs between different POI features. In order to evaluate the effectiveness and efficiency of the proposed algorithm, extensive experiments were conducted on location based real social network datasets. However, it does not consider the cost of travel routes. So use the minimum spanning tree to calculate cost effective travel routes. Asha Murali | Amina Beevi A "Survey: Optimal Travel Route Discovery based on Topic Interest and Image Attributes" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: https://www.ijtsrd.com/papers/ijtsrd11303.pdf

Natural disasters are an unexpected fact of life that may occur during unpredictable times and in unpredictable ways. Ability to mitigate and adapt to natural disasters after many devastating events is becoming a greater challenge to the emergency response operators. Inefficiencies in the technology during rescue operations makes the communication between the rescuers problematic. The emerging role of GPR and GSM remote cameras makes it possible to capture and process the mission-critical data for the use of first responders. Due to its portability and affordable cost, it is feasible to integrate them into environment monitoring tasks in critical care regions. A problem is that there is a need to switch between different access networks for providing effective mission critical communication. IEEE 802.21 standard provides a media independent framework that enables seamless handover between heterogeneous access technologies. We proposed a life detection framework that assists the rescue operators in detecting alive humans and thereby provides a smooth communication between them. This framework together with media independent handover scheme and real time data distribution service operates in a reliable and timely manner against unpredictable environments. Keywords: Media Independent Handover (MIH), unmanned aerial vehicles(UAVs),disaster detection, handover.