Comparative Evaluation of WOFOST and CERES-Rice Models in Simulating Yield of Rice Cultivars at Navari
Nilesh J. Hadiya1, Neeraj Kumar1, B. M. Mote1, Chiragkumar. M. Thumar2 and D. D. Patil1
A field experiment was conducted during kharif season of 2015 to assess the prediction performance of CERES-Rice and WOFOST model for grain and straw yield of three rice cultivars viz., (V1:Jaya, V2: Gurjari and V3: GNR-2) sown under four different environments viz., (D1: 10/07/2015, D2: 25/07/2015, D3: 09/08/2015 and D4: 24/08/2015) with two nitrogen levels N1:75 and N2:100 kg NPK/ha-1.Results showed that the prediction of WOFOST model forgrain yield of rice cultivars under different treatments more close to the corresponding observed value with percent error PE between (18.66%)as camper to CERES-rice model with PE (28.56%), but for straw yield CERES-rice model give more close prediction than WOFOST model with PE (20.99%) and (27.33%) between predicted and observed value.
S. Sebastian and R. S. Chouhan
It is essential to maintain a ratio between privacy protection and knowledge discovery. Internet users depend daily on SSL/HTPS for secure communication on internet.
Over the years, many attacks on the certificate trust model it uses have been evolved. Mutual SSL authentication shared verification alludes to two parties validating each other through checking the digital certificate so that both sides are guaranteed of the other’s identity.
In technical terms, it alludes to a client (web program or client application) authenticate themselves to the server (server application) and that server likewise confirming itself to the client through checking the general public key certificate issued by trusted Certificate Authorities (CA). Since confirmation depends on computerized Certificate, certification authorities, for example, Verisign or Microsoft Declaration Server are a critical part of mutual authentication process.
From an abnormal state perspective, the way toward authenticating and setting up an encrypted channel using certificate-based mutual SSL authentication.
M. S. Vaishnavi* and A. Vijayalakshmi
Aging face recognition poses as a key difficulty in facial recognition. It refers to identification of a person face over varied ages. It includes issues like age estimation, progression and verification. Non-availability of facial aging databases make it harder for any system to achieve good accuracy as there are no good training sets available. Age estimation when done correctly has a varied number of real life applications like age detailed vending machines, age specific access control and finding missing children. This paper implements age estimation using Park Aging Mind laboratory - Face database that contains metadata and 293 unique images of 293 individuals. Ages range from 19 to 45 with a median age of 32. Race is classified into two categories : African-American and Caucasian giving an accuracy of 98%. Sobel edge detection and Orthogonal locality preservation projection were used as the dominant features for the training and testing of age estimation. A Multi-stage binary classification using support vector machine was used to classify images into an age group thereafter predicting an individual’s age. The effectiveness of this method can be increased by using a large dataset with a wider age range.
Alan J. George and Deepa V. Jose
Energy efficiency has always remained a pressing matter in the world of Wireless Sensor Networks. Irrespective of the number of routing protocols that exist for Wireless Sensor Networks, only a handful can be named as efficient. Yet above all these routing protocols stands the emblematic one, the LEACH protocol. This research work is aimed at bringing forth a new routing strategy based on the LEACH protocol, which aims at improving the energy efficiency in Wireless Sensor Networks and applying the given clustering technique, in randomly deployed and fixed sensor network simulation environment using MATLAB. In depth simulations have proven that the proposed clustering strategy gives better performance compared to LEACH based on the lifetime of the Nodes. A comparative analysis of the rate of energy consumed on various node deployment strategies has also been carried out.
Tenzin Dawa1 and N. Vijayalakshmi2
Face Recognition is a biometric system which can be used to identify or verify a person from digital image by using the facial features that are unique to each other. There are many techniques which can be used in a face recognition system. In this paper we review some of the algorithms and compare them to see which technique is better compared to one another. Techniques that are compared in this technique are Non-negative matrix factorization (NMF) with Support Vector Machine (SVM), Partial Least Squares (PLS) with Hidden Markov Model (HMM) and Local Ternary Pattern (LTP) with Booth’s Algorithm.