Applies various scheduling algorithms to processes and produces the corresponding Gant Chart.

In this Respository, The trend Project OpenCV project has been made, basically OpenCV Projects mostly code in Python, JAVA, C++, C. Otherwise OpenCV (Open Source Computer Vision Library) is an open source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code. The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, stitch images together to produce a high resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery and establish markers to overlay it with augmented reality, etc. OpenCV has more than 47 thousand people of user community and estimated number of downloads exceeding 18 million. The library is used extensively in companies, research groups and by governmental bodies.

. Topic Detection using keyword Clustering To find prominent topic in a collection of documents. We here propose a system to detect topic from a collection of document. We use an efficient method to discover topic in a collection of documents known as topic model. A topic model is a type of statistical model for discoveringtopics from collection of documents. One would expect particular words to appear in thedocument more or less frequently: “dog” and “bone” will appear more often in documentsabout dogs, “cat” and “meow” will appear in documents about cats, and “the” and “is” willappear equally in both. A document typically concerns multiple topics in differentproportions; thus, in a document that is 10% about cats and 90% about dogs, there wouldprobably be about 9 times more dog words than cat words. Our proposed system capturesthis intuition in a mathematical framework and will examine topic of particular set ofdocuments. Here the system will extract keywords and will use clustering algorithm in orderto discover topic from particular set of documents. System will extract keywords which occuroften and will cluster this keywords using clustering algorithm and will detect topic from acollection of documents. This system takes co occurrence of terms into account which givesbest result. This system can be useful for web crawlers and for web users. This system willhelp the web users to easily search information for particular topic. When the user will searchfor particular topic, system will extract various keywords from the set of documents whichwill match topic name mentioned by the web user and will cluster the keywords and willprovide topic related information to the user. Web users will get information quickly forrespective topic they are searching for. Advantages  This system takes co occurrence of terms into account which gives best result.  This system will help the web users to easily search information for particular topic.  Web users will get information quickly for respective topic they are searching for. Feasibility Study This system will extract keywords which occur often from collection of documents and will cluster the words using clustering algorithm and system will detect topic from a collection of documents.  Economic Feasibility This system will help the web users to easily search information for particular topic. This system will be useful for web crawlers. This system will provide economic benefits for many websites. It includes quantification and identification of all the benefits expected.  Operational Feasibility This system is more reliable, maintainable, affordable and producible. These are the parameters which are considered during design and development of this project. During design and development phase of this project there was appropriate and timely application of engineering and management efforts to meet the previously mentioned parameters.  Technical Feasibility The back end of this project is PHP Wamp server which stores parameters related to this project. There are basic requirement of hardware to run this application. This application will be online so this application can be accessed by using any device like (Personal Computers, Laptop and with some hand held devices). Module Description : This project is “Topic Detection Using Keyword Clustring” .The Website is named as “ GO DETECTCTION : SEARCH ON THE BRINK” . This project is basically a web tool which will help the users to detect the Topic of the paragraph or the lines which will be entered by the user . Our Website starts with a basic introduction about what it will do and how it is going to work. It gives the information to the users about some basic things that are used to make the topic detection tool like data mining, Knowledge Management and Business Intelligence. All the pages are designed with the help of HTML , CSS and Bootstrap. The validations are done in the website using Java Script. The data connectivity is mainly used for Sign Up and Sign In which is done by PHP using Wamp Server. With the help of tools such was web crawlers and Java Script ,when the user will enter the paragraph in the text box , the tool will detect the possible topics of the paragraph and will display all the results to he user . The user may choose any of the topic among them.