A study to assess the effectiveness of infrared radiation therapy on pain perception and wound healing among primi postnatal women with episiotomy
Motherhood has true nobility and unique capacities. Pregnancy and childbirth are special events in women’s lives. This study aimed to assess the effectiveness of Infrared radiation therapy on pain perception and wound healing among prime postnatal women with episiotomy in Christian mission hospital, Madurai. The study was conducted among 60 postnatal women, 30 in experimental group and 30 in control group, who were selected by using purposive sampling technique. Data collection was done as planned 6 weeks were taken for data collection procedure. The data gathered were analyzed and the interpretation was made on the study objectives. The paired‘t’ test and independent‘t’ test were used to find out the effectiveness of infrared radiation therapy. Comparison of pain perception and wound healing status values between pre-test and post-test, experimental and control group showed the significant difference at 0.05 levels. The study concluded that the infrared radiation therapy was effective in reducing episiotomy pain and wound healing. Therefore, infrared radiation therapy should be used to augment the therapy of episiotomy.
Published by: Elizebeth Rani
Author: Elizebeth Rani
Paper ID: V4I3-1344
Paper Status: published
Published: May 10, 2018
Face spoofing detection using LBP descriptor and ensemble subspace discriminant classifier
Recently, automatic face recognition has become a realistic target of biometrics research. Face fake attacks are truly a threat to face recognition systems. Exploration on non-invasive software based face spoofing detection schemes have been mainly concentrated on the analysis of the luminance information of the face images, accordingly discarding the chroma component, which can be very useful for discriminating fake faces from genuine ones. In this paper, we present a novel approach based on analyzing joint color-texture information of the facial image from the luminance and the chrominance channels using color local binary pattern (LBP) descriptor. Particularly the feature histograms are extracted from each image band separately. The resulting feature histograms are concatenated into an enhanced feature histogram in order to obtain an overall reproduction of the facial color texture. The final feature vector is fed to an ensemble subspace discriminant classifier and it describes whether there is a live person in front of the camera or a fake one. Also, we determine the performance measures of an ensemble classifier and compare with SVM.
Published by: Shahna J. S, Minnu Jayan C
Author: Shahna J. S
Paper ID: V4I3-1311
Paper Status: published
Published: May 9, 2018
Smart agriculture by monitoring moisture pH levels in soil
Agriculture plays the major role in economics and survival of people in India. Even today, traditional methods and backward techniques are being used by different countries in the agriculture sector. In India, the agriculture techniques are labor intensive, whereas the modern agriculture technology is mainly capital intensive. Production efficiency has been increased significantly with the technological advancement in agriculture. With the help of internet of things, a novel design approach to smart farming is framed that increases the productivity. IoT will play a major role in meeting this need. IoT when combined with cloud and big data, it can improve the efficient use of inputs like fertilizers, soil, and pesticides. It also helps in scanning storage capacities like water tanks, predicting related diseases, monitoring livestock, and making sure the crops are watered well. Farmers need the variety of data and services to improve crop production based on land, crop, climate conditions, finance availability, irrigation facilities etc.. Cloud computing has been used by Government and other private agencies to store agricultural data. Cloud support various services to farmers to interact with the cloud by using any cheaper ways like sensors, mobile devices, scanners etc. Smart farming becomes an emerging concept, IoT sensors are capable of providing information about their respective agricultural fields. This proposed approach aims at making use of evolving technologies like IoT and smart agriculture using automation. The major factor that aids in improving the yield of efficient crops is by monitoring environmental factors. To monitor various agricultural activities like cutting, weeding and spraying, a remote-controlled vehicle is operated that works both in automatic and manual modes. A controller is mounted on this vehicle that monitors the temperature, soil condition, temperature and accordingly water is supplied to the field.
Published by: Gaddam Sanjeeva Reddy, C M Anuja, Manjunath C R, Sahana Shetty
Author: Gaddam Sanjeeva Reddy
Paper ID: V4I3-1314
Paper Status: published
Published: May 9, 2018
Real-time human skin color detection using OTSU thresholding
Skin color is a robust cue in human skin detection. In the development of Human-Computer Interface (HCI) applications, information that are relative to skin color is extensively utilized. Human skin color shows resemblance with non-skin materials like wood, wall paint etc. So an accurate human-computer interaction system is required to be designed which can distinguish between them. Although several methods have been proposed, skin color detection still remains a challenge mainly due to problems such as illumination conditions, camera characteristics, and ethnicity.
Published by: Dujana Nuzra A K, Minnu Jayan C
Author: Dujana Nuzra A K
Paper ID: V4I3-1336
Paper Status: published
Published: May 9, 2018
Classification of hyperspectral images using PPI and LMM
Hyperspectral images are the treasure of information since it contains hundreds of spectral bands. Classification of Hyperspectral images is the process of identifying the components in each pixel. For this purpose, the pure and mixed pixels of the image should be identified and the endmember signatures and components are identified with the help of spectral libraries. In this paper, it is attempted to identify the minerals in the hyperspectral data ‘Cuprite’, that covers the Cuprite mines in Las Vegas, Nevada, the U.S. The pure pixels are identified by using PPI algorithm and their endmember signatures are obtained. The abundance maps of mixed pixels are obtained by using LMM. The total variation based regularization and joint sparsity of abundance maps are exploited in this paper.
Published by: Pavithra Sukumar, Sreena V G
Author: Pavithra Sukumar
Paper ID: V4I3-1303
Paper Status: published
Published: May 9, 2018
Smart metro train
The proposed system is driverless train which is preprogrammed to run between two stations. For this, ARM 7 microcontroller is used. It exterminates need any driver. Thus, the human blunder is ruled out. The prototype provides detection of passengers at the platform. RFID module is used when the passenger is entering the station, a passenger will swipe the card and if it is valid then the passenger can enter into the train. Passenger count is displayed on the ThingSpeak webpage for future use.
Published by: Madhura Suresh Punde, Monali Sarade, Shatataraka Ulhalkar, Aparna More
Author: Madhura Suresh Punde
Paper ID: V4I3-1181
Paper Status: published
Published: May 9, 2018
