Mean Field Methods for a Special Class of Belief Networks

The chief aim of this paper is to propose mean-field approximations for a broad class of Belief networks, of which sigmoid and noisy-or networks can be seen as special cases. The approximations are based on a powerful mean-field theory suggested by Plefka. We show that Saul, Jaakkola and Jordan' s approach is the first order approximation in Plefka's approach, via a variational derivation. The application of Plefka's theory to belief networks is not computationally tractable. To tackle this problem we propose new approximations based on Taylor series. Small scale experiments show that the proposed schemes are attractive

Cloud Based Application Development for Accessing Restaurant Information on Mobile Device using LBS

Over the past couple of years, the extent of the services provided on the mobile devices has increased rapidly. A special class of service among them is the Location Based Service(LBS) which depends on the geographical position of the user to provide services to the end users. However, a mobile device is still resource constrained, and some applications usually demand more resources than a mobile device can a ord. To alleviate this, a mobile device should get resources from an external source. One of such sources is cloud computing platforms. We can predict that the mobile area will take on a boom with the advent of this new concept. The aim of this paper is to exchange messages between user and location service provider in mobile device accessing the cloud by minimizing cost, data storage and processing power. Our main goal is to provide dynamic location-based service and increase the information retrieve accuracy especially on the limited mobile screen by accessing cloud application. In this paper we present location based restaurant information retrieval system and we have developed our application in Android.Comment: 11 pages, 10 figure

A study of representations for pen based handwriting recognition of tamil characters

In this paper we study the important issue of choosing representations that are suitable for recognizing pen based handwriting of characters in Tamil, a language of India. Four different choices, based on the following set of features are considered: (1) a sequence of directions and curvature; (2) a sequence of angles; (3) Fourier transform coefficients; and (4) wavelet features. We provide arguments in support of the representation using wavelet features. A neural network designed using these features gives excellent accuracy for recognizing Tamil characters

Formal Verification of Safety Properties for Ownership Authentication Transfer Protocol

In ubiquitous computing devices, users tend to store some valuable information in their device. Even though the device can be borrowed by the other user temporarily, it is not safe for any user to borrow or lend the device as it may cause private data of the user to be public. To safeguard the user data and also to preserve user privacy we propose and model the technique of ownership authentication transfer. The user who is willing to sell the device has to transfer the ownership of the device under sale. Once the device is sold and the ownership has been transferred, the old owner will not be able to use that device at any cost. Either of the users will not be able to use the device if the process of ownership has not been carried out properly. This also takes care of the scenario when the device has been stolen or lost, avoiding the impersonation attack. The aim of this paper is to model basic process of proposed ownership authentication transfer protocol and check its safety properties by representing it using CSP and model checking approach. For model checking we have used a symbolic model checker tool called NuSMV. The safety properties of ownership transfer protocol has been modeled in terms of CTL specification and it is observed that the system satisfies all the protocol constraint and is safe to be deployed.Comment: 16 pages, 7 figures,Submitted to ADCOM 201