Neythal Land Worship and Beliefs found in Natrinai

Sangam literature is a mirror of the times which shows the lives of the people of the Sangam age. Among the land divisions such as Kurinji, Mullai, Marutham, Neithal, and Palai, Neithal Thinai is the sea and the land around the sea. They help us know the customs of the people of Neithal Land. We are able to understand the great labour and methods of worship of the people of the land through the Natrinai Neithal Thinai. Moreover, it is possible to know the customs of the Bharatas, the sun, the moon, nature, the wind, the rain, the trees, the fasting, and the rituals of worshipping the deity. The Etthutthokai and the Pathuppaattu songs greatly help to understand their unchanging way of life. Moreover, worship and beliefs prevail in the songs found in the Neithal Thinai. In this article, we are also amazed at the brave tide-sea journey of the people of Neithal, the devoted way of life of the woman-head of the family, and the ability to cope with the hardships caused by natural calamities. In today's time, the sea's condition is compassionate. It is not an exaggeration to say that if the songs of Natrinai Neithal Thinai are closely looked at, it is their faith and worship that give creativity and encouragement to everyone and teach them to face life with courage

Banana Leaf Disease Identification Technique

There is no machine learning techniques have been used in an attempt to detect diseases in the banana plant such as banana bacterial wilt (BBW) and banana black sigatoka (BBS) that have caused a huge loss to many banana growers. The study investigated various computer vision techniques which led to the development of an approach that consists of four main phases. In phase one, images of Banana leaves were acquired using a standard digital camera. Phase two is the preprocessing phase where resizing and morphological operations occur. Next phase is the segmentation phase which translates RGB(Red Green Blue) image to YCbCr (Luminance Chrominance) color space which is then converted to a gray scale image and finally to a binarized image using Adaptive Contrast Map method. Next is the feature extraction phase where extraction of leaf features like color, texture and, shape occurs. Then comes the prominent phase were classification done Using Support Vector Machine classifier as classifier. Lastly, the performance of the classifier is evaluated to determine whether a leaf is diseased or not

Status of Growth Monitoring in Anganwadi Centres of a Primary Health Centre, Thirubhuvanai, Puducherry

Purpose: To assess the status of growth monitoring activities and difficulties faced by anganwadi workers (AWWs) at the anganwadi centres (AWCs). Methodology: A survey was conducted among AWWs under a rural Primary Health Centre. Structured observations on weight measurement were made using a check list. Secondary data on record keeping and maintenance was collected. Findings: Study participants (n=20) had a 24 (± 10.25) years of experience in Integrated Child Development Services and underwent training once in two years. For advising mothers of malnourished children, deworming and immunization was not mentioned by majority AWWs. In AWCs, children less than 6 month were weighed on bathroom scale and not by Salter’s scale. Unclothing the child before weighing was practiced by only 10% AWWs. Nonfunctional weighing machine was the major problem reported by AWWs. Conclusion: There were gaps in the growth monitoring activities in AWCs of a PHC, Thirubhuvanai which needs to be tackled

A LITERATURE SURVEY ON VARIOUS ILLUMINATION NORMALIZATION TECHNIQUES FOR FACE RECOGNITION WITH FUZZY K NEAREST NEIGHBOUR CLASSIFIER

The face recognition is popular in video surveillance, social networks and criminal identifications nowadays. The performance of face recognition would be affected by variations in illumination, pose, aging and partial occlusion of face by Wearing Hats, scarves and glasses etc. The illumination variations are still the challenging problem in face recognition. The aim is to compare the various illumination normalization techniques. The illumination normalization techniques include: Log transformations, Power Law transformations, Histogram equalization, Adaptive histogram equalization, Contrast stretching, Retinex, Multi scale Retinex, Difference of Gaussian, DCT, DCT Normalization, DWT, Gradient face, Self Quotient, Multi scale Self Quotient and Homomorphic filter. The proposed work consists of three steps. First step is to preprocess the face image with the above illumination normalization techniques; second step is to create the train and test database from the preprocessed face images and third step is to recognize the face images using Fuzzy K nearest neighbor classifier. The face recognition accuracy of all preprocessing techniques is compared using the AR face database of color images

AN ILLUMINATION INVARIANT FACE RECOGNITION BY ENHANCED CONTRAST LIMITED ADAPTIVE HISTOGRAM EQUALIZATION

Face recognition system is gaining more importance in social networks and surveillance. The face recognition task is complex due to the variations in illumination, expression, occlusion, aging and pose. The illumination variations in image are due to changes in lighting conditions, poor illumination, low contrast or increased brightness. The variations in illumination adversely affect the quality of image and recognition accuracy. The illumination variations in face image have to be pre-processed prior to face recognition. The Contrast Limited Adaptive Histogram Equalization (CLAHE) is an image enhancement technique popular in enhancing medical images. The proposed work is to create illumination invariant face recognition system by enhancing Contrast Limited Adaptive Histogram Equalization technique. This method is termed as “Enhanced CLAHE”. The efficiency of Enhanced CLAHE is tested using Fuzzy K Nearest Neighbour classifier and fisher face subspace projection method. The face recognition accuracy percentage rate, Equal Error Rate and False Acceptance Rate at 1% are calculated. The performance of CLAHE and Enhanced CLAHE methods is compared. The efficiency of the Enhanced CLAHE method is tested with three public face databases AR, Yale and ORL. The Enhanced CLAHE has very high recognition accuracy percentage rate when compared to CLAHE

Indirect electrochemical oxidation of o-chloro toluene to 0-chloro benzaldehyde using ceric methane sulphonate

O-chloro benzaldehyde finds wide applications as chemical intermediates, pharmaceuticals, optical brighteners etc. It is nomlally produced by acid hydrolysis, but the process generates chlorinated by-products and has poor selectivity. Indirect electrochemical oxidation of o-chloro toluene using ceric mediators otTers a facile and clean route for the production of the aldehyde. In this paper results are reported for the oxidation of o-chloro toluene to o-chloro benzaldehyde using eerie methane sulphonate followed by electrochemical regeneration of eerie from cerous thereby making the process cyclic. 60-70% selectivities have been achieved for the chemical oxidation of o· chloro toluene to o-ehloro benzaldehyde while the electrochemical regeneration of eerie from cerous proceeds with 70-80% current efficiencies

Using Graph Theory Concepts to Determine Boiling Point Formulae for Choloalkanes

Abstract—The applications of graph theory are not restricted only to mathematics. Graph theory and mathematical modeling can be combined to study various chemical phenomena like characterization and identification of chemical compounds. Given a chemical substance and some of its properties a chemist would like to be able to determine whether the substance is a known compound or not. Properties of substances depend not only on their chemical composition but also on the shape of the molecules. Index Terms — Graph theory, chemical property, structure, boiling point