An advent of data mining to prognosticate users' successive questions using association rules V S Chandana, C Anitha 2017 International Conference on Energy Communication Data Analytics and Soft Computing Icecds 2017, 2018 In this paper regarding to question answering system, the user herein submits the question and will be waiting for the answer as the response. If the respective system is potential at prognosticating the interest of the users as the successive questions, its performance does ameliorate greatly. This paper does predict the user's multiple future questions, which is reckoned on the previous interaction records of the user with those of the system. Their current interactions are managed in the form of the log of questions from, which the respective user in the sessions is actually extracted. Multiple administrations are created for different types of questions. For an instance, like Finance and Sports like wise. Reckoned on the user which may become interested in the near future. A sample questions as log is chosen as required for the purpose of the performing at the explorations. The model of this association rule at the mining is actually applied primarily to predict the multiple future question of the user.
Motion sensing and image capturing based smart door system on android platform Faiz Aman, C Anitha 2017 International Conference on Energy Communication Data Analytics and Soft Computing Icecds 2017, 2018 A smart door system which can be controlled by the android application installed on smart phone is proposed in this paper. Earlier, smart locks were used which enhanced the security features of the house. The proposed model can eliminate the concept of lock system as here the security is provided to the door itself. This would result in a safe and secure door with no locks! Controlling the movement of the door is enabled by Raspberry pi and its related embedded software. Also merging IOT with android is has many advantages in terms of security. The motion sensors are used to detect any movement in front of the door. If any person comes in front of the door, a motion is triggered; the image is captured and notified to the owner. Thus in overall proposed system, two technologies are concentrated on, one is motion sensing in the front of the door in real time even if there is no one at home and the second is to control the movement of the door by the smart phone. Thus by connecting a mobile phone to a door, the owner get notified whenever any visitor visits his home and looking up to the images, the owner of the home can send the open door signal for only the trusted visitors.
Android application based gas leakage notifier R Aishwarya, Akshath R Hegde, N Ashwini, A R Mohammed Thavaf, C Anitha 2017 International Conference on Energy Communication Data Analytics and Soft Computing Icecds 2017, 2018 Gas leakage is a phenomenon which can possibly dispense significant harms to lives and property. Detection of gas leakage and informing the concerned individuals is frequently the first and the most imperative stride in keeping away from any casualties. Already accessible products in the market neglect to convey the notice to clients who are situated elsewhere, and, offer next to zero flexibility. The best answer for this is to use the capacity of the idea called “Internet of Things”, which means whereby remote sensors, cloud storage, and convenient terminal gadgets can be utilized to alarm the client with respect to a gas leakage. This paper introduces such a method, wherein the client is kept mindful of the leakage status through an Android application and cellular network based SMS. The proposed solution is highly flexible and cost effective.
Real time detection and tracking of mouth region of single human face C. Anitha, M.K. Venkatesha, B. Suryanarayana Adiga Proceedings Aims 2015 3rd International Conference on Artificial Intelligence Modelling and Simulation, 2016 For any real-time application, detection and tracking of features becomes very important. The detection and tracking algorithms have to be very robust and efficient with least or zero false positives and false negatives. We use a novel combination for detection and tracking purpose. In this paper we propose a robust mouth region extraction and tracking algorithm that works in real-time. The region of interest for our application requires the face and mouth regions. We propose a novel technique for extracting the mouth region automatically. The proposed technique detects and tracks the mouth in either closed or opened state. We use the color components for skin tone and lips extraction.
A Two Fold Expert System for Yawning Detection C. Anitha, M.K. Venkatesha, B. Suryanarayana Adiga Procedia Computer Science, 2016 One of the prominent indicators of drowsiness is yawning. The main intention for a real-time application such as detecting the driver's yawning is that the response of the detector must be as quick as possible. A novel yawning detection system is proposed which is based on a two agent expert system. The features of the face have to be extracted to detect yawning in the driver's face. In the proposed system, as the first part of detection we use the face detection algorithm's skin detection part. The skin region is extracted. For all the skin region blocks detected, their boundaries are defined. Then segmented face is divided into two halves. The lower half of the face is considered for the mouth region extraction. The presence of yawning would be indicated by a black blob in the mouth region of the binary image. But, there may be multiple blobs present in the image which may be due to the presence non-skin like regions around the driver's face. So, identifying the exact position of the mouth and checking for its containment inside the face is necessary. The features extracted for yawning detection are the histogram values taken from the vertical projection of the lower part of the face.
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