Design and Implementation of Real Time Wireless Biomedical System Based on ZigBee-GSM interactive module:

We present a framework for a wireless health monitoring system using ZigBee technology. It has the capability to monitor vital signals from multiple biosensors. Biomedical signals are collected and processed using 2-tiered subsystems. The first stage is the mobile device carried on the body that runs a number of biosensors (internal subsystem). At the second stage, further processing is performed by a local base station (external subsystem) using the raw data transmitted on-request by the mobile device. The raw data is also stored at this base station. The processed data as well as the analysis results are then monitored and diagnosed through

Numerical Model of a Variable-Combined-Cycle Engine for Dual Subsonic and Supersonic Cruise

Efficient high speed propulsion requires exploiting the cooling capability of the cryogenic fuel in the propulsion cycle. This paper presents the numerical model of a combined cycle engine while in air turbo-rocket configuration. Specific models of the various heat exchanger modules and the turbomachinery elements were developed to represent the physical behavior at off-design operation. The dynamic nature of the model allows the introduction of the engine control logic that limits the operation of certain subcomponents and extends the overall engine operational envelope. The specific impulse and uninstalled thrust are detailed while flying a determined trajectory between Mach 2.5 and 5 for varying throttling levels throughout the operational envelope

On the influence of the cosmological constant on gravitational lensing in small systems

The cosmological constant Lambda affects gravitational lensing phenomena. The contribution of Lambda to the observable angular positions of multiple images and to their amplification and time delay is here computed through a study in the weak deflection limit of the equations of motion in the Schwarzschild-de Sitter metric. Due to Lambda the unresolved images are slightly demagnified, the radius of the Einstein ring decreases and the time delay increases. The effect is however negligible for near lenses. In the case of null cosmological constant, we provide some updated results on lensing by a Schwarzschild black hole.Comment: 8 pages, 1 figure; v2: extended discussion on the lens equation, references added, results unchanged, in press on PR

TICO: a tool for postprocessing the predictions of prokaryotic translation initiation sites

Exact localization of the translation initiation sites (TIS) in prokaryotic genomes is difficult to achieve using conventional gene finders. We recently introduced the program TICO for postprocessing TIS predictions based on a completely unsupervised learning algorithm. The program can be utilized through our web interface at and it is also freely available as a commandline version for Linux and Windows. The latest version of our program provides a tool for visualization of the resulting TIS model. Although the underlying method is not based on any specific assumptions about characteristic sequence features of prokaryotic TIS the prediction rates of our tool are competitive on experimentally verified test data

BI APPLICATION IN FINANCIAL SECTOR -CREDIT SCORING OF RETAIL LOANS USING A HYBRID MODELING APPROACH

Retail Loans now-a-days form a major proportion of Loan Portfolio. Broadly they can be classified as (i) Loans for Small and medium Sector and (ii) Loans for Individuals. The objective of Credit Scoring is that we use enough of precaution before the sanction of the loan so that the loans do not go bad after disbursement. This will increase to the bottom line of the financial institution and also reduce the Credit Risk.Techniques used to perform Credit Scoring Varies for the above two classes of loans. In this paper, we concentrate on the application of Credit Scoring for individual or so called personal loans like – Auto loan, buying goods like Televisions, Refrigerators etc. Large numbers of loans are being disbursed in these areas. Though the size of the loan may be small, when compared to Small/Medium Scale Industry, if one does not control the defaults, the consequences will be disastrous.From the characteristics of borrower, product characteristics a Credit Score is computed for each applicant. If the Score exceeds a given threshold loan is sanctioned. If it is below the threshold, loan is sanctioned. If it is below the threshold, loan is rejected. In practice a buffer zone is created near the threshold so that those Credit Scores that fall in buffer zone, detailed investigation will be done before a decision is taken.Two broad classes of Scoring Model exists (i) Subjective Scoring and (ii) Statistical Scoring.Subjective Scoring is based on intuitive judgement. Subjective Scoring works but there is scope for improvement one limitation is prediction of risk is person dependent and focuses on few characteristics and may be mistakenly focusing on wrong characteristics.Statistical Scoring uses hardcore data of borrower characteristics, product characteristics and uses mathematical models to predict the risk. The relation is expressed in the form of an equation which finally gets converted to a score. Subjectivity will be reduced and variable(s) that are important to scoring are identified based on strong mathematical foundation.Different Models have been used in Credit Scoring like Regression, Decision Tree, Discriminate Analysis and Logistic Regression. Most of the times, a single model is used to compute the Credit Score. This method works well when the underlying decision rule is simple and when the rule becomes complex, the accuracy of the model diminishes very fast.In this Research Paper, a combination of Decision Tree and Logistic Regression is used to determine the weights that are to be assigned to different characteristics of the borrower. Decision Tree is used at first level of analysis to narrow down the importance of Variables and overall weights that needs to be assigned. It is also used for optimum groupings of numeric and non-numeric Variables. At second level, Logistic Regression is used to compute odd ratios a variant of probability, which in turn is used to assign weights for an attribute and to individual levels in an attribute.This has been tested on real life data and found to work better compared to methods using a single stage models. An accuracy of around 80% in decision is obtained which is good for any modeling study as there is no model which gives 100% accuracy.The next Section explains the Methodology, Data Used and Results.SPSS Software has been used for Model Building and Data Analysi