Real Time Raga Detection and Analysis Using Computer

Department of Computer Applications, Cochin University of Science and Technology

Detection and diversity of pathogenic Vibrio from Fiji

Here we investigate the diversity of pathogenic Vibrio species in marine environments close to Suva, Fiji. We use four distinct yet complementary analyses – biochemical testing, phylogenetic analyses, metagenomic analyses and molecular typing – to provide some preliminary insights into the diversity of vibrios in this region. Taken together our analyses confirmed the presence of nine Vibrio species, including three of the most important disease-causing vibrios (i.e. V. cholerae, V. parahaemolyticus and V. vulnificus), in Fijian marine environments. Furthermore, since toxigenic V. parahaemolyticus are present on fish for consumption we suggest these bacteria represent a potential public health risk. Our results from Illumina short read sequencing are encouraging in the context of microbial profiling and biomonitoring. They suggest this approach may offer an efficient and costeffective method for studying the dynamics of microbial diversity in marine environments over time.

Automatic Detection and Classification of Glioma Tumors using Statistical Features

The characterization and grading of glioma tumors, via image derived features, for diagnosis, prognosis, and treatment response has been an active research area in medical image computing. This paper presents a novel method for automatic detection and classification of glioma from conventional T2 weighted MR images. Automatic detection of the tumor was established using newly developed method called Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA).Statistical Features were extracted from the detected tumor texture using first order statistics and gray level co-occurrence matrix (GLCM) based second order statistical methods. Statistical significance of the features was determined by t-test and its corresponding p-value. A decision system was developed for the grade detection of glioma using these selected features and its p-value. The detection performance of the decision system was validated using the receiver operating characteristic (ROC) curve. The diagnosis and grading of glioma using this non-invasive method can contribute promising results in medical image computing

Ethernet Telemetry for Towed Arrays

The towed array electronics is essentially a multichannel real time data acquisition system. The major challenges involved in it are the simultaneous acquisition of data from multiple channels, telemetry of the data over tow cable (several kilometres in some systems) and synchronization with the onboard receiver for accurate reconstruction. A serial protocol is best suited to transmit the data to onboard electronics since number of wires inside the tow cable is limited. The best transmission medium for data over large distances is the optical fibre. In this a two step approach towards the realization of a reliable telemetry scheme for the sensor data using standard protocols is described. The two schemes are discussed in this paper. The first scheme is for conversion of parallel, time-multiplexed multi-sensor data to Ethernet. Existing towed arrays can be upgraded to ethernet using this scheme. Here the last lap of the transmission is by Ethernet over Fibre. For the next generation of towed arrays it is required to digitize and convert the data to ethernet close to the sensor. This is the second scheme. At the heart of this design is the Analog-to-Ethernet node. In addition to a more reliable interface, this helps in easier fault detection and firmware updates in the field for the towed arrays. The design challenges and considerations for incorporating a network of embedded devices within the array are highlighted