Author(s): Sudeesh S, M. Suresh
Institute: SELVAM COLLEGE OF TECHNOLOGY
Keywords: Clustering, Data Stream, High Dimensionality
Abstract
This paper presents a novel high-speed clustering scheme for high dimensional data streams. Data stream clustering has gained importance in different applications, for example, in network monitoring, intrusion detection, and real-time sensing are few of those. High dimensional stream data is inherently more complex when used for clustering because the evolving nature of the stream data and high dimensionality make it non-trivial. In order to tackle this problem, projected subspace within the high dimensions and limited window sized data per unit of time are used for clustering purpose. We propose a High Speed and Dimensions data stream clustering scheme (HSD Stream) which employs exponential moving averages to reduce the size of the memory and speed up the processing of projected subspace data stream. The proposed algorithm has been tested against HDD Stream for cluster purity, memory usage, and the cluster sensitivity. Experimental results have been obtained for corrected KDD intrusion detection dataset. These results show that HSDStream outperforms the HDDStream in performance metrics, especially the memory usage and the processing speed.
Paper ID: IJSRDV5I10658
Published in IJSRD Volume : 5, Issue : 1, April 2017
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Authors: Rajneesh Kumar, Abhinav Kumar Yadav, Sh Nishant Tripathi,
Institute: NIELIT Gorakhpur, UP
Keywords: GSM/GPRS Enabled Embedded Server, Internet of Things based Controlling
Abstract:
The internet has initially started as the “Internet Of Computers”, a global network enabling services that now include the World Wide Web(WWW), File Transfer Protocol and others allowing computers and hence users to communicate with each other and exchange information. There are several definitions for the Internet of Things (IOT) that explain what are the main functionalities of it and what we should expect from when connecting “Things” with each other and with the internet. Internet of Things (IoT) is an ideal emerging technology to influence the internet and communication technologies. Simply “Internet of Things” connects living and non living things through internet. The main aim of this project to enable the users to control and monitor smart devices through internet. In this an interface between users and smart home by using GSM and internet technologies, or simply creating GSM based wireless communication from the web server into the smart home.
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After buying GitHub, four gaming companies and an educational video-discussion vendor, Redmond purchased on June 20 another artificial intelligence (AI) vendor.
Microsoft officials announced the company had signed an agreement to acquire Bonsai. Bonsai, based in Berkeley, Calif., is one of the companies that Microsoft’s Ventures unit (now known as M12) had invested.Bonsai officials describe the company as delivering “the world’s first deep reinforcement learning platform for the enterprise.”
Bonsai officials said the company has been integrating machine-learning and developer tools from Microsoft, Uber, Google and Apple to build its software and services to build AI for industrial applications, according to Bonsai’s web site. (Cue Microsoft’s “intelligent edge” campaign.)
Bonsai uses machine learning to “abstract the low-level mechanics of machine learning” to enable subject matter experts to specify and train autonomous systems to accomplish certain tasks. The training takes place inside a simulated environment, Microsoft officials said in a blog post published today about the acquisition.
Microsoft plans to combine Bonsai’s platform with Azure Machine Learning running on Azure with GPUs and Brainwave, its AI-on-FPGA (field programmable gate array) work. Models built using Brainwave will be deployed and managed in Azure IoT, “giving Microsoft an end-to-end solution for building, operating and enhancing ‘brains’ for autonomous systems,” the Microsoft blog post says.
Source: https://www.zdnet.com/article/microsoft-buys-machine-learning-startup-bonsai/
Author(s):
Indus Institute of Technology & Engineering, Indus University, Ahmedabad, Gujarat
Keywords:
Energy Generation, Renewable Energy, Vertical Axis Wind Turbine, Wind Energy
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