High Power, Continuous-wave Supercontinuum Generation in Highly Nonlinear Fibers Pumped with High Order, Cascaded Raman Fiber Amplifiers

A novel method for efficient generation of high power, equalized continuous-wave supercontinuum source in an all conventional silica fiber architecture is demonstrated. Highly nonlinear fiber (HNLF) is pumped in its anomalous dispersion region using a novel, high power, L-band laser. The L-band laser encompasses a 6th order cascaded Raman amplifier which is pumped with a high power Ytterbium doped fiber laser and amplifies a low-power, tunable L-band seed source. The supercontinuum generated 35W of power with ~40% efficiency. The Supercontinuum spectrum was measured to have a high degree of flatness of better than 5 dB over 400 nm of bandwidth (1.3 - 1.7 micron, limited by spectrum analyzer range) and a power spectral density in this region of >50 mW/nm. The extent of the SC spectrum is estimated to be upto 2 micronComment: 6 pages, 5 figure

AN EFFICIENT METHOD TO FEED HIGH RESOLUTION IMAGES TO FACIAL ANALYSIS SYSTEMS

Image Processing is any form of signal processing for which the image is an input such as a photograph or video frame. The output of image processing may be either an image or a set of characteristics or parameters related to the image. In many facial analysis systems like Face Recognition face is used as an important biometric. Facial analysis systems need High Resolution images for their processing. The video obtained from inexpensive surveillance cameras are of poor quality. Processing of poor quality images leads to unexpected results. To detect face images from a video captured by inexpensive surveillance cameras, we will use AdaBoost algorithm. If we feed those detected face images having low resolution and low quality to face recognition systems they will produce some unstable and erroneous results. Because these systems have problem working with low resolution images. Hence we need a method to bridge the gap between on one hand low- resolution and low-quality images and on the other hand facial analysis systems. Our approach is to use a Reconstruction Based Super Resolution method. In Reconstruction Based Super Resolution method we will generate a face-log containing images of similar frontal faces of the highest possible quality using head pose estimation technique. Then, we use a Learning Based Super-Resolution algorithm applied to the result of the reconstruction-based part to improve the quality by another factor of two. Hence the total system quality factor will be improved by four

Design and analysis of multiple read port techniques using bank division with XOR method for multi-ported-memory on FPGA platform

The multiple read and write operations are performed simultaneously by multi-ported memories and are used in advanced digital design applications on reprogrammable field-programmable gate arrays (FPGAs) to achieve higher bandwidth. The Memory modules are configured by block RAM (BRAMs), which utilizes more area and power on FPGA. In this manuscript, the techniques to increase the read ports for multi-ported memory modules are designed using the bank division with XOR (BDX) approach. The read port techniques like two read-one write (2R1W) memory, hybrid mode approach either 2R1W or 4R memory, and hierarchical BDX (HBDX) Approach using 2R1W/4R memory are designed on FPGA platform. The Proposed work utilizes only slices and look-up table (LUT's) rather than BRAMs while designing the memory modules on FPGA, which reduces the computational complexity and improves the system performance.  The experimental results are analyzed on Artix-7 FPGA. The performance parameters like slices, LUT utilization, maximum frequency (Fmax), and hardware efficiency are analyzed by concerning different memory depths. The 4R1W memory design using the HBDX approach utilizes 4% slices and works at 449.697 MHz operating frequency on Artix-7 FPGA. The proposed work provides a better platform to choose the proper read port technique to design an efficient modular multiport memory architecture

Automated ECG Analysis for Localizing Thrombus in Culprit Artery Using Rule Based Information Fuzzy Network

Cardio-vascular diseases are one of the foremost causes of mortality in today’s world. The prognosis for cardiovascular diseases is usually done by ECG signal, which is a simple 12-lead Electrocardiogram (ECG) that gives complete information about the function of the heart including the amplitude and time interval of P-QRST-U segment. This article recommends a novel approach to identify the location of thrombus in culprit artery using the Information Fuzzy Network (IFN). Information Fuzzy Network, being a supervised machine learning technique, takes known evidences based on rules to create a predicted classification model with thrombus location obtained from the vast input ECG data. These rules are well-defined procedures for selecting hypothesis that best fits a set of observations. Results illustrate that the recommended approach yields an accurateness of 92.30%. This novel approach is shown to be a viable ECG analysis approach for identifying the culprit artery and thus localizing the thrombus

No longer diseases of the wealthy : prevalence and health-seeking for self-reported chronic conditions among urban poor in Southern India

Background: The burden of chronic conditions is high in low-and middle-income countries and poses a significant challenge to already weak healthcare delivery systems in these countries. Studies investigating chronic conditions among the urban poor remain few and focused on specific chronic conditions rather than providing overall profile of chronic conditions in a given community, which is critical for planning and managing services within local health systems. We aimed to assess the prevalence and health-seeking behaviour for self-reported chronic conditions in a poor neighbourhood of a metropolitan city in India. Methods: We conducted a house-to-house survey covering 9299 households (44514 individuals) using a structured questionnaire. We relied on self-report by respondents to assess presence of any chronic conditions, including diabetes and hypertension. Multivariable logistic regression was used to analyse the prevalence and health-seeking behaviour for self-reported chronic conditions in general as well as for diabetes and hypertension in particular. The predictor variables included age, sex, income, religion, household poverty status, presence of comorbid chronic conditions, and tiers in the local health care system. Results: Overall, the prevalence of self-reported chronic conditions was 13.8% (95% CI = 13.4, 14.2) among adults, with hypertension (10%) and diabetes (6.4%) being the most commonly reported conditions. Older people and women were more likely to report chronic conditions. We found reversal of socioeconomic gradient with people living below the poverty line at significantly greater odds of reporting chronic conditions than people living above the poverty line (OR = 3, 95% CI = 1.5, 5.8). Private healthcare providers managed over 80% of patients. A majority of patients were managed at the clinic/health centre level (42.9%), followed by the referral hospital (38.9%) and the super-specialty hospital (18.2%) level. An increase in income was positively associated with the use of private facilities. However, elderly people, people below the poverty line, and those seeking care from hospitals were more likely to use government services. Conclusions: Our findings provide further evidence of the urgent need to improve care for chronic conditions for urban poor, with a preferential focus on improving service delivery in government health facilities

Named Cells and Bodies in Oral Pathology - Part II: A Ready Reckoner

It is important for the Oral pathologist to be familiar with the different pathological cells and bodies as they very often tend to appear in various diseases and conditions. In spite of most of these inclusions not being pathognomic, they inevitably help the pathologist in making a diagnosis. Besides assisting in recognition of a lesion, this article will also be of immense help to the student population. This article is split into two parts for the ease of the reader. Part I provided  an overview of  various pathological cells and bodies pertaining to diseases, metabolic disorders and neoplasms. Part II will brief about those associated with cysts, tumors and infections

Proofs for Integrity of Data in Cloud Storage

data is moved to a remotely located cloud server in cloud computing. The cloud stores the data and return back to the owner whenever it is needed. But there is no guarantee that data stored in the cloud is secured and not altered by the cloud or Third Party. In order to overcome the problem of integrity of data, the user must be able to use the assist of a third party. The third party has experience in checking integrity of data, that cloud users does not have, and that is difficult for the owner to check. The data in the cloud should be correct, consistent, accessible and high quality. The aim of this research is to ensure the integrity of data and provides the proof that data is in secured manner and to provide cryptographic key to secure the data in the cloud. The proposed approach has been implemented

Named Cells and Bodies in Oral Pathology - Part I: A Ready Reckoner

Oral pathology is a visual speciality which navigates a pathologist in the arena of micro details amidst complex tissues. At times we get stuck or entrapped in a state of flux when we come across certain pathological cells or bodies as our eyes are more conditioned viewing at normal morphology of cell & structures. Although they may be deceptive in their appearance, at the same time aids the pathologist in diagnosis as they are pathognomonic of certain diseases & conditions.  For the ease of description, this article has been split into two parts. Part I provides an overview of various pathological cells and bodies pertaining to diseases, metabolic disorders and neoplasm’s reflecting its significance in Oral Pathology. Besides being an instant reckoner to the student population, it aids in diagnosing different pathological conditions