Volume 8 | Issue 9 |

 Abstract

In this manuscript, for the removal of Rician noises from MR images a fourth order PDE (partial differential equation) based nonlinear filter is proposed. The filter implemented contains two terms firstly, the data fidelity term and secondly, prior function term. By minimizing the negative log likelihood of Rician probability density function (pdf) we get the fidelity term. A prior function is introduced because the solution of the first term has ill-posed nature. This prior function is a nonlinear anisotropic diffusion based filter. To maintain the trade off balance between these two terms a regularization parameter is introduced. In terms of PSNR at various noise levels the comparative study and performance analysis of the suggested model with other standard methods is presented for Brain Web dataset. From the results obtained, it is clear that the method implemented is performing better noise removal as compared to other methods.

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Nonlinear fourth order PDE based filter, 2D MR images, Rician�s probability distribution function, Rician noise reduction.

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reviews, fraudsters,early reviews.

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Precision agriculture is a farming system based on the combination of detailed observations, measuring and rapid response to optimize energetic input to maximize crop production. Precision Agriculture is one of the modern farming practices that make crop production more efficient. One of the major problems in agricultural domain is earlier detection of plant diseases. Currently, manual plant disease classification and counting are very time consuming with less accuracy. Detection of various diseases of plant is very essential to prevent the damage it can make to plant as well as to the farmers and whole Agriculture ecosystem. Regarding this practical issues, this project aimed to classify and detect plant diseases especially for tomato plant. Deep Convolutional Neural Network (CNN) based architecture is proposed for leaf disease detection and classification. The experimentation is carried out using Unmanned Aerial Vehicle (UAV) images. Plant village dataset, UAV images dataset, real-time images captured through UAV and some images downloaded from the internet are used. This system detects the diseases present in plant with more accuracy.

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Precision agriculture, Deep Learning, Convolutional Neural Network (CNN), UAV images, Plant disease.

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Slums are the face of urban poverty and illiteracy. According to the census 2011, the states with highest contribution to the slum population are Maharashtra (18%), Andhra Pradesh (15.6%) and West Bengal (9.8%). Alleviation of poverty is the most important weapon of improving general health. The income for the poor increases marginally, which makes it difficult to assure a better health condition in urban slums areas. According National Health Portal (2011), the MMR for India was 212/100,000 live births. About 830 women die from pregnancy- or childbirth-related complications around the world every day. Maternal mortality ratio in developing countries in 2015 is 239 per 100 000 live births versus 12 per 100 000 live births in developed countries. The above data given by WHO gave an insight to study the present scenario of maternal health in urban slum. This study attempts to examine the socio-economic aspects and food intake of mothers dwelling in urban slums. Thus it will help to identify anomalies and aspects related to urban setting and poverty. A cross-sectional study was conducted on 150 women in the urban slums of Budge Budge, Kolkata. A pilot study was done and an interview schedule was prepared to seek information on socio economic status by using Kuppuswamy Scale. Data were also collected on health facilities and food intake which were analyzed and the results are presented in the form of tables. It was found that 66% percent of pregnant women had secondary education, followed by higher secondary (26%) and graduation (12%) level of education. Kuppuswamy scale shows that 50% of the subjects were from upper lower class and only 1.33% was from upper class. Among the 150 subjects, 45.33% had pucca house, 64.67% had toilet facility, 28 % had proper drainage system and 28% had appropriate source of drinking water at their home. The food intake depicts the actual nutritional status of the mothers.

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Keywords: Slums, maternal mortality, socioeconomic status, Kuppuswamy scale

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Objective: This work aims at studying the indications and immediate to long term results of percutaneous mitral commisurotomy during pregnancy. Methods: A retrospective study of 246 mitral valve dilations performed during pregnancy from 1997 to 2018 in the Cardiology A department, Ibn Sina Teaching hospital Rabat. We analyzed clinical, echocardiographic and hemodynamic data before and after PMC: Results: Our patients� mean age was 28 � 5.2 years and the gestational age 28.1 � 4 weeks of amenorrhea. Mitral stenosis was discovered during pregnancy in 40% of cases and all 246 patients were primiparous. 94% of our patients were symptomatic (NHYA stages III to IV). 85% of patients had sinus rhythm. On cardiac ultrasound imaging, mitral stenosis was severe in all our patients: mean surface area of 0.8cm� and ? 1cm� in 85% of our cases; 90% of our patients had Wilkins� score of 8 � 9. Mean transvalvular gradient was high (21.4mmHg) and most of our patients had pulmonary hypertension (mean Pulmonary Artery systolic pressure 71mmHg). The procedure had 98% success rate with immediate regression of symptoms to NYHA stages I to II in 95% cases. After PMC, pregnancy reached full term in 95% of our patients with low fetal morbimortality and delivery in good conditions, mostly vaginal (85% of our cases). Conclusion: PMC is the ideal treatment for severe symptomatic mitral stenosis during pregnancy, yielding excellent results with very few complications. It leads to a clear regression of symptoms and improves hemodynamic parameters as well as pregnancy and delivery conditions. When indicated, PMC should be performed in a reference centre.

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mitral stenosis � pregnancy � Percutaneous mitral commisurotomy

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Technological interventions have brought significant advances in facilitating the research outreach over the years in learning. Based on this criteria the study �Challenges in Adoption of Technology in Agricultural Education - A Critical Analysis� was carried out to identify problems faced by the students in use of technological tools, suggestions to overcome those problems and to assess capacity needs of learners in use of technological tools,. The study was descriptive and data was collected randomly from 360 students of six Agricultural and Allied Universities by using structured and open ended questionnaire. The collected data was analyzed by using Training need index, Content analysis, Frequency and Percentage. The major problems faced by the students in use of technological tools are lack of funds (86%), advanced training (84.7%), maintenance (84.1%) and technical knowledge (83.3%) in use of technological tools. Major Suggestions to overcome those problems mentioned by students are requirement of financial support (87.5%), provision of training (86.3%), non-credit course should be mandatory (86.1%), Proper maintenance of available devices (84.7%). The results revealed that the students require training in effective use of technological tools in following training areas are preparation and use of technology based learning material (89.4%), self- evaluation of learning (89.3%) and training on advance learning applications (89.1%) which have been ranked as I, II, III positions respectively. From the study it can be deduced that, the training is necessary for students in use of technological tools which leads to changes in their learning style and also enhance the learning experience.

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Technological Tools, Effective Learning, Students/learners, Capacity, Training, Problems, Suggestions

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Varjil Mahakavi barediruva mahakavya Enied. Illi Mukyavada sangatiye Adhikarada daha mattu Apaharana. kelavaru adhikarakke hatoredare matte kelavaru tamma preyasi apaharanavadaralla enba sedina prateekara teerisikollalu honchu hakuttiruttare. ENIED Kavyada maha nayaka ENIES nu tanna jeevanadalli Devanu Devategala sahaya mattu Upatalavannu sahisikonde tanna Jeevana yatreyannu kaigolluttane, Aadaru avaninda TROY Nagarada patanavannu tadeyalu sadhyavagade, Devate Mattu Tandeya maatinate Deashantara Hoguva paristiti bandodaguttade.

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MOHADA KARANAVE DWESHA, DWESHADINDU YUDDHA.

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Gas leakage and Fire breakout are a major problem in the industrial sectors. Gas-powered vehicles like CNG (compressed natural gas) buses and car emits gases. Preventive methods of stopping gas leakage are essential. By installing a gas leakage detection kit at vulnerable places for controlling it. The aim of this paper is to design a fire and gas detection system for home and industrial safety. The proposed system makes use of a microcontroller with a sensing circuit. It will detect gas leakage and fire with the help of an alarm system that gives alert about fire or gas leakage. With the installation of a GSM modem, SMS is sent to notify the user if there is fire or gas leakage and if the fire occurs then water sprinkler performs the function of sprinkles water on the affected area to reduce the effect of the fire. Fire detection can be carried out by using the IR flame sensor. It detects the fire in the working area and alert SMS is sent to the user.

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compressed natural gas (CNG), GMS, Fire detector

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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