Edge Detection Algorithm

This paper proposes an improved detection algorithm for LTE Random Access preamble detection and evaluates the performance of the algorithm with respect to the performance of algorithms proposed in the literature using MDP metric. Keywords— detection algorithm; LTE; Random access; preamble; MDP I. INTRODUCTION The 3 rd Generation Partnership Project (3GPP) mandates a certain access procedure for achieving synchronization between the evolved base station (eNodeB) and the mobile User Equipment (UE) in the Long Term Evolution (LTE) Standard. This Access Procedure consists of three parts, cell search which enables the UE to assess the reception quality of the current and neighbouring cells so as to conclude if a handover is necessary; transfer of system information; and Random Access. A detailed description of this access procedure is discussed in the standard [1][2][3].This Random Access procedure consists of four steps executed by the UE and eNodeB [5] that helps the network identify the UE and establish timing synchronization [Fig. 1]. The following are the four steps of Random Access, Step 1: The UE selects one of the 64 available preambles generated from a root sequence and transmits it to the eNodeB. This preamble identifies the UE and provides Timing Advance (TA) information to the network. Step 2: The eNodeB replies with a Random access response message that consists of a temporary identity assigned to the UE, TA information and Uplink Grant resource. Step 3: The UE transmits a Terminal Identification message based on the temporary identity received in the previous step as part of Radio Resource Control (RRC) signaling. Step 4: The eNodeB replies with a contention resolution message completing the RRC signaling between the network and the UE.

The authentication of a person using tongue is voting for the greater accuracy. Tongue the least gullible organ considered as an efficient candidature for person identification and authentication. Tongue print of every Human is different and unique. Besides being unique it the least manipulated organ it enhances the security for identification and authentication of a person avoiding mostly occurring forgery cases. The paper introduces the feature extraction using sharpening and edge detection for acquiring tongue for authentication. The methodology for the study of person identification using tongue print uses MSE.

Brain-Computer Interfaces (BCIs) allow users to control applications by brain activity. Among their possible applications for non-disabled people, games are promising candidates. BCIs can enrich game play by the mental and affective state information they contain. During the eNTERFACE’09 workshop we developed the Bacteria Hunt game which can be played by keyboard and BCI, using SSVEP and relative alpha power. We conducted experiments in order to investigate what difference positive vs. negative neurofeedback would have on subjects’ relaxation states and how well the different BCI paradigms can be used together. We observed no significant difference in mean alpha band power, thus relaxation, and in user experience between the games applying positive and negative feedback. We also found that alpha power before SSVEP stimulation was significantly higher than alpha power during SSVEP stimulation indicating that there is some interference between the two BCI paradigms.