Noise shaping Asynchronous SAR ADC based time to digital converter

Time-to-digital converters (TDCs) are key elements for the digitization of timing information in modern mixed-signal circuits such as digital PLLs, DLLs, ADCs, and on-chip jitter-monitoring circuits. Especially, high-resolution TDCs are increasingly employed in on-chip timing tests, such as jitter and clock skew measurements, as advanced fabrication technologies allow fine on-chip time resolutions. Its main purpose is to quantize the time interval of a pulse signal or the time interval between the rising edges of two clock signals. Similarly to ADCs, the performance of TDCs are also primarily characterized by Resolution, Sampling Rate, FOM, SNDR, Dynamic Range and DNL/INL. This work proposes and demonstrates 2nd order noise shaping Asynchronous SAR ADC based TDC architecture with highest resolution of 0.25 ps among current state of art designs with respect to post-layout simulation results. This circuit is a combination of low power/High Resolution 2nd Order Noise Shaped Asynchronous SAR ADC backend with simple Time to Amplitude converter (TAC) front-end and is implemented in 40nm CMOS technology. Additionally, special emphasis is given on the discussion on various current state of art TDC architectures.Electrical and Computer Engineerin

Multivariate Mixed Data Mining with Gifi System using Genetic Algorithm and Information Complexity

Statistical analysis is very much dependent on the quality and type of a data set. There are three types of data - continuous, categorical and mixed. Of these three types, statistical modeling on a mixed data had been a challenging job for a long time. This is due to the fact that most of the traditional statistical techniques are defined either for purely continuous data or for purely categorical data but not mixed data. In reality, most of the data sets are neither continuous nor categorical in a pure sense but are in mixed form which makes the statistical analysis quite difficult. For instance, in the medical sector where classification of the data is very important, presence of many categorical and continuous predictors results in a poor model. In the insurance and finance sectors, lots of categorical and continuous data are collected on customers for targeted marketing, detection of suspicious insurance claims, actuarial modeling, risk analysis, modeling of financial derivatives, detection of profitable zones etc. In this work, we bring together several relatively new developments in statistical model selection and data mining. In this work, we address two problems. The first problem is to determine the optimal number of mixtures from a multivariate Bernoulli distributed data using genetic algorithm and Bozdogan\u27s information complexity, ICOMP. We show that the results of the maximum likelihood values are not just sufficient in determining the optimal number of mixtures. We also address the issue of high dimensional binary data using a genetic algorithm to determine the optimal predictors. Finally, we show the results of our algorithm on a simulated and two real data sets. The second problem is to discovering interesting patterns from a complicated mixed data set. Since mixed data are a combination of continuous and categorical variables, we trans- form the non linear categorical variables to a linear scale by a mechanism called Gifi transformation, [Gifi, 1989]. Once the non linear variables are transformed to a linear scale (Euclidean space), we apply several classical multivariate techniques on the transformed continuous data to identify the unusual patterns. The advantage with this transformation is that it has a one-to-one mapping mechanism. Hence, the transformed set of continuous value(s) in the Gifi space can be remapped to a unique set of categorical value(s) in the original space. Once the data is transformed to the Gifi space, we implement various statistical techniques to identify interesting patterns. We also address the problem of high dimensional data using genetic algorithm for variable selection and Bozdogan\u27s information complexity (ICOMP) as our fitness function. We present details of our newly-developed Matlab toolbox, called Gifi System, that implements everything presented, and can readily be extended to add new functionality. Finally, results on both simulated and real world data sets are presented and discussed. Keywords: Gifi, homals, regression, multivariate logistic regression, fraud detection, medical diagnostics, supervised classification, unsupervised classification, variable selection, high dimensional data mining, stock market trading, detection of suspicious insurance claim estimates

Blind Multiridge Detection and Reconstruction Using Ultrasonic Signals

Time-frequency signal analysis has been widely applied in the modern radar, acoustic, sonar and ultrasonic signal processing techniques. Recently, the nondestructive testing (NDT) techniques via the ultrasonic instrumentation have shown the striking capability of the quality control for the material fabrication industry. In this thesis, we first provide a general mathematical model for the ultrasonic signals collected by pulse-echo sensors and then design a totally blind, novel, signal processing NDT technique relying on neither a priori signal information nor any manual effort. The signature signal can be blindly extracted by using the automatic optimal frame size selection for further modeling and characterization of the ultrasonic signal using Gabor analysis. This modeled signature signal is used for multiridge detection and for reconstruction of the signal. The detected ridge information can be used to estimate the transmission and attenuation coefficients, shear modulus, and Young’s modulus associated with any arbitrary material sample for fabrication quality control. Thus, our algorithm can be applied for ultrasonic signal characterization and ridge detection in non-destructive testing for new material fabrication. Experimental results show that the ridge detection performance by our proposed method is superior to that of the existing techniques

Application of state-of-the-art FEM techniques to magnetostatic NDE

A typical example of the complexities involved in the numerical modeling of electromagnetic phenomena is that of modeling the magnetic flux leakage inspection of gas transmission pipelines. The problem calls for three-dimensional modeling of motionally induced currents (using transient analysis), modeling nonlinearity of the ferromagnetic parts, and accurate modeling of the permanent magnet used in the magnetizer. Researchers, have thus far simplified the problem using several assumptions, including that of axisymmetry, and modeling velocity effects using steady-state analysis. However, there has been no attempt to quantify the errors introduced by these assumptions. Also, due to the unavailability of commercial codes to solve three-dimensional motion-related problems using transient analysis, a detailed study of the true nature of velocity effects has not been possible;This dissertation implements and evaluates state-of-the-art finite element modeling techniques applied to the specific problem of modeling magnetic flux leakage inspection of gas pipelines. This provides the basis from which conclusions can be drawn on the general problem of modeling magnetostatic phenomena. Axisymmetric and three-dimensional models are developed capable of modeling velocity effects. A detailed analysis of the differences between axisymmetric and three-dimensional geometries, based on a study of permeability variations in the vicinity of defects is presented. Also, the need for transient analysis is argued based on results generated. As part of this study, serious problems (including spurious solutions and corner singularities) associated with the traditional node-based finite-element techniques, when applied to the three-dimensional modeling, are discussed. In this work, new and efficient numerical modeling concepts, using the edge-based finite-element technique are employed to overcome these problems;This study demonstrates the need for accurate modeling of the full three-dimensional geometry, incorporating velocity effects and nonlinear permeability, for realistic predictions of flux leakage inspection tools. Major contributions of this work include: (1) detailed analysis of the physical processes associated with the magnetic flux leakage tool, (2) design ideas to improve the performance of the tool, and (3) development of an edge-based finite element code for modeling magnetostatic nondestructive testing applications in three-dimensions incorporating velocity effects. This is the first study of this nature, applied to pipeline inspection, and, many of the conclusions presented can be applied to nondestructive testing techniques in general

Reevaluating Social Media Marketing Communications

When looking for a college or university, apart from the world-class program, facility, and faculty, the students also look for a place to fit in and call home. Students can now connect with a school’s campus life 24/7 through the power of social media along with the traditional marketing of printed booklets, campus visits, and overnights. We have many websites and services that rank the universities using metrics for research income and academic impact. However, there is no metric provided by these services to measure the quality of life; Social media pages provide a means to look at the campus life and the culture. The goal of College of Business is to identify what students and their families are looking for and to use social media to share their campus culture with prospective students and their parents. College of business is sharing campus life as it happens, using Instagram photos, Facebook videos, Tweets, and more. The primary objectives of Assessments are to sample, measure, and report on strengths, identify gaps in the existing marketing strategies

Retrospective analysis of biochemical profile of dengue infection in a tertiary care hospital

Background: Dengue is an exceedingly common infection of the tropics. The aim of the research to study the biochemical parameters of serologically proven dengue cases.Methods: The study included Dengue patients admitted in PSG Hospital between January 2011and December 2012.Results: Analysis of aspartate aminotransferase results showed that 19.1% had two-fold rise, 13.3% had three-fold rise and 19.6% had more than threefold rise. Analysis of alanine aminotransferase showed that 35.7% had normal values, 14.95% had two-fold rise, 11.1% had three-fold rise and 11.5% had more than threefold rise. Serum proteins were normal in 35.7% and low in 19.6%. Analysis of serum albumin showed low values in 10.6% Serum sodium levels were low in 11.1% of patients. Albuminuria was positive in 53% of patients. Serum ionised calcium levels were low in 26.8% of patients.Conclusions: The biochemical abnormalities noted in our study included include elevated liver enzymes, low sodium and ionised calcium levels, hypoalbuminemia and increased urine albumin excretion

Large ovarian mucinous cystadenoma in premenarchal girl: a case report

Ovarian tumors are commonly seen in adults and rare in children. Incidence in children is about 2.6 cases per 1,00,000 girls. Most common ovarian mass in children is benign functional cyst. Epithelial tumors account for 8-10% of ovarian tumors. Most common epithelial tumor is Cystadenoma. Mucinous cystadenoma occurs in 3rd -6th decade of life. We report a 10-year-old Premenarchal girl presenting with abdominal distension and discomfort. On examination the entire abdomen was occupied by a firm mass. CT imaging showed a large multiloculated cystic lesion arising from the right ovary. The child underwent right salphingo-oophrectomy. The biopsy of mass was suggestive of benign mucinous cystadenoma. The child is on regular follow up. At 1 year follow up child is doing well

Retrospective analysis of ultrasound features of dengue infection

Background: Dengue infection is an extremely common infection in tropical countries. It is considered to be prevalent all-round the year. The aim of the study was to analyse the ultrasound features of serologically proven dengue cases. To correlate the platelet count with ultrasound features of dengue.Methods: Study included dengue patients admitted from January 2011 to December 2012. Dengue was diagnosed by IgM antibody test. All patients underwent ultrasound evaluation and platelet count testing.Results: most common finding was ascites in 43 cases (39.8%), splenomegaly in 41 cases (37.9%), right sided pleural effusion in 25 cases (23.4%), gall bladder wall thickening was present in 30 cases (27.7%) and hepatomegaly was present in 20 cases (18.5%). Presence of most of the features of ultrasound evaluation correlated with a platelet count of less than 40000 cells/mm3.Conclusions: The commonest sonographic findings were ascites and splenomegaly followed by pleural effusion and gall bladder wall thickening. Thus, presence of these ultrasound features in a febrile patient may be suggestive of dengue fever and presence of all the sonographic features may suggest a low platelet count