Location Prediction in Twitter using Machine learning Techniques

Locations, e.g., Countries, states, cities, and point-of-interests, are central to news, emergency events, and people‚Äôs daily lives. Automatic identification of locations associated with or mentioned in documents has been explored for decades. As one of the most popular online social network platforms, Twitter has attracted a large number of users who send millions of tweets on daily basis. Due to the world-wide coverage of its users and real-time freshness of tweets, location prediction on Twitter has gained significant attention in recent years. Research efforts are spent on dealing with new…

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Diagnosis of liver diseases using machine learning

Diagnosis of liver diseases using machine learning Liver Diseases account for over 2.4% of Indian deaths per annum. Liver disease is also difficult to diagnose in the early stages owing to subtle symptoms. Often the symptoms become apparent when it is too late. This paper aims to improve diagnosis of liver diseases by exploring 2 methods of identification patient parameters and genome expression. The paper also discusses the computational algorithms that can be used in the aforementioned methodology and lists demerits. It proposes methods to improve the efficiency of these…

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Trustworthy Data Collection Approach in Sensor-Cloud Systems

sensor-cloud systems have received wide attention from both academia and industry. Sensor-cloud system not only improves performances of wireless sensor networks (WSNs), but also combines different functional WSNs together to provide comprehensive services. However, a variety of malicious attacks threaten the sensor-cloud security, such as integrity, authenticity, availability and so on. Traditional available security mechanisms (e.g. cryptography and authentication) are still vulnerable. Although there are schemes to provide security by trust evaluation, the evaluation considers whether or not a sensor is credible only by checking the communication behaviors. Furthermore, when…

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Three Dimensional Tagcloud visualization for tourism

Three Dimensional Tagcloud visualization for tourism Metadata creation along with growth of social bookmarking emerged an approach named tagging. Often people look for location along with its route and detailed information about its surrounding. Mobile users may opt for current event that is taking place in the current location along with historical background of their surroundings and events that happen over time. They are provided with information on spatial context of location which harvests context information from freely available source and tag cloud visualization is created for this data. Firstly,…

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Rainfall prediction using Lasso and Decision Tree alogrithm on Python

Implementation Details: ———————– We are taking dataset X Train & Test is from ID to Oct-Dec (NOT ANNUAL Column) Y Train & Test is the Annual column We are taking dataset and Analysing dataset & plotted all graphs. Using Train set of X & Y we are applying ML algorithm Lasso and Decision Tree For X testset, we are arriving results and stored as resultLasso & resultDecisionTree   Python Demo

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Secret Image parts Sharing on Multiple images

Secret Image parts Sharing on Multiple images Implementation Details: ———————— Sender takes secret image, Hidimg image1 and Hiding image 2 Secret image is split into 2 parts img0, img1 The part of sercret image is taken and encoded and converted to string value then hidden in Hiding image 1, simialarly second part also done The above secret create hideimage1 and hideimage2 Then this image is sent to receiver Receiver receives receivedimage1 and receivedimage2 These images are loaded to extract secret image the image is read and string value is separated…

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