Diabetic Retinopathy is human eye disease which causes damage to retina of eye and it may eventually lead to complete blindness. Detection of diabetic retinopathy in early stage is essential to avoid complete blindness. Many physical tests like visual acuity test, pupil dilation, optical coherence tomography can be used to detect diabetic retinopathy but they are very time consuming and costly.There are many features present in retina but the exudates feature which is one of the primary signs of diabetic retinopathy and which is a main cause of blindness that could be prevented with the help of this automatic detection process. In feature extraction Pupil dilation is important step in the normal screening process but this affects Diabetes vision. The automatic detection process reduces examination time, and increase accuracy. In this paper we provide review on many techniques and algorithms that helps to diagnose Diabetic Retinopathy in retinal fundus images. This paper also reviews, classifies and compares the algorithms and techniques previously proposed in order to develop better and more effective algorithms.

Keywords: Diabetic Retinopathy, Machine Learning, SVM ,Neural Networks , CNN ,KNN.

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This paper explains the prediction of probabilities of rainfall by stochastic process and magnitude of rainfall using Linear Regression Models. Using Markov chain techniques, a two state and four state first order transition probability matrices were developed for the daily and yearly analysis respectively. For daily rainfall analysis, the transition states classified as rainy and non-rainy days.In yearly rainfall analysis, the transition sequences were established based on rainfall intensities. For long term rainfall analysis,limiting probabilities were calculated with steady state transition matrix and initial state probability matrix. Linear regression models are used for prediction of the magnitude of annual rainfall for 5 years, with the help of previous 15 years rainfall data and the predicted rainfall is compared to actual rainfall data. The average error is estimated by calculating the difference in the actual and predicted rainfall values. All the models were developed using the previous 30 years (1989-2018) rainfall of Kolar region.

Keywords: Markov chain, stochastic process, Transition Probabilities, Initial State Probabilities, Linear Regression, Coefficient of correlation and Coefficient of determination

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In this study, cost optimization model has been developed to minimize the costs associated with oil spill cleanup subject to some constraints. The model would also be used in estimating the anticipated cleanup cost of any given spill with respect to the amount of spilled oil in tonnes. The model developed using updated cost data collected from case studies of some selected spills and from the current prices of cleanup chemicals and technologies was developed using the Linear Optimization Software (LiPS). The optimization model result gave $4400/ton as the per-unit cost of oil spilled per tonne. To validate the model, the result of the model ($4400/ton) was compared to the available data of the average per-unit costs of the numerous previous spill incidents including average costs of crude Oil Spills..........

Keywords: Offshore Oil-spill, Clean-up Technologies, Cost optimization.

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The Smart Board is another piece of technology that enriches student-teacher science learning and provides teacher educator with the skills necessary to adapt to a highly technological society. This specific device can be used in the classroom as a gateway to new technologies and its enhancement to ones learning of teacher education. A Smart Classroom is a learning environment that contains all course materials of education. The conception of the smart classroom has made it possible for students to tackle the features of the internet to create a meaningful and constructivist learning environment of School education. Information and Communication Technology (ICT) is playing an important role in the teaching-learning process of the smart classroom. It increases the flexibility of delivery of education so that student-teacher can access knowledge anytime and anywhere easily.......

Keywords: Primary teacher training students, Smart board technology, Teaching of science and Technology.

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This paper study the importance of primary Evaluation criteria and attributes for selecting the Cloud service providers in the Market. The study was conducted to produce empirical data on the reliability and validity of the Cloud selection Attribute questionnaire. A survey was conducted and the reliability, validity of the questionnaire were tested with the Cronbach's alpha. The Cronbach's alpha test conducted shows that the overall score was 0.92 indicating high reliability of the items for cloud service provider. Principal component analysis is performed to test the dimensionality of variables used in this study.

Keywords: cloud servers, Cronbach alpha, reliability, factor analysis, computing, dimensionality.

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The aim of the present paper is to propose a framework, for swarm drones or in other words unmanned aerial vehicles (UAVs), with IoT applications for monitoring a wide agriculture fields in economy perspective, we propose to send the collected data to centre station which can analysing the current data, after process that can pass information to Robots or other involved machine .We are interested in building algorithms in collecting data from cultivated areas accurately and in a relatively short time and also help farmers to eliminate harmful pests and spread fertilizer in a timely manner. According to the design scenarios, UAVs they carry out specific actions such as transporting signals from the field to the main station and also spraying pesticides and fertilizers based on a GPS map. In other hand,the central station also sends some orders to the robots to carry out certain tasks such as regulating irrigation, cleaning irrigation canals and cutting grass. So all operations controlled from one place the central station...........

Keywords: IoT, Algorithms, GPS, Robot, and swarm drones.

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Where else but Quora can physicist help chef with math problem and get cooking tips in return? ―Quora‖ is a place to gain and share knowledge—about anything. It's a platform to ask questions and connect with people who contribute unique insights and quality answers. This empowers people to learn from each other and to better understand the world. Over 100 million people visit Quora every month, so it's no surprise that many people ask similarly worded questions. Multiple questions with the same intent can cause seekers to spend more time finding the best answer to their question, and make writers feel they need to answer multiple versions of the same question. Quora values canonical questions because they provide a better experience to active seekers and writers, and offer more value to both of these groups in the long term. Doing so will make it easier to find high quality answers to questions resulting in an improved experience for Quora writers, seekers, and readers.

Keywords: Quora, R programming, Keras, Tensor Flow.

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