An empirical analysis of the twin deficits evidence from Sri Lanka

This paper explores the empirical relationship between budget and current account deficits in the case of a small developing country, Sri Lanka for the period of 1960-2010. The data are collected from annual reports, Centra! Bank, Sri Lanka. The econometric methods used in this study are cointegration technique, Error correction modeling and Granger causality analysis. The empirical results are consistent with conventional view. Our empirical results clearly suggest that there exist statistically significant long-run positive relationship between the trade deficit and the budget deficit in Sri Lanka. The Granger causality test shows that the direction of causality runs from the budget deficit to the trade deficit and the relationship is positive and statistically significant. '••The empirical analysis in this study partially supports the Keynesian view that there is a linkage between the trade deficit and the budget deficit and the direction of causality is correct but the Ricardian equivalence hypothesis is not valid for Sri Lankan economy during the study period

Empirical investigation of the dynamic relationship between government expenditure and Economic growth in Sri Lanka

This study examines the long run dynamic relationship between government expenditures and economic growth for Sri Lankan economy during the period from 1977-2009. The study tests the validity of the Keynesian view and Wagner's law in the case of Sri Lankan economy. The empirical evidence has been acquired through the co-integration, error correction model and the Granger causality tests. The empirical findings clearly suggest that there is a statistically significant positive long run relationship between government expenditure and economic growth in Sri Lanka during the sample period. The Granger causality test shows that causality runs from government expenditure to economic growth and vice versa, the relationship is positive and statistically significant. The empiridcal results of this study support the Keynesian view and Wagnerian law and the direction of causality is valid for Sri Lankan economy during the study period. These results have important policy implications for both domestic policy makers and the development partners working in Sri Lanka

Performance Analysis of Classifier Models to Predict Diabetes Mellitus

AbstractDiabetes is one of the common and growing diseases in several countries and all of them are working to prevent this disease at early stage by predicting the symptoms of diabetes using several methods. The main aim of this study is to compare the performance of algorithms those are used to predict diabetes using data mining techniques. In this paper we compare machine learning classifiers (J48 Decision Tree, K-Nearest Neighbors, and Random Forest, Support Vector Machines) to classify patients with diabetes mellitus. These approaches have been tested with data samples downloaded from UCI machine learning data repository. The performances of the algorithms have been measured in both the cases i.e dataset with noisy data (before pre-processing) and dataset set without noisy data (after pre-processing) and compared in terms of Accuracy, Sensitivity, and Specificity

Design of SkSP-R Plan for Popular Statistical Distributions

The design of a Skip-lot sampling plan of type SkSP-R is presented for time truncated life test for the Weibull, Exponentiated Weibull, and Birnbaum-Saunders lifetime distributions. The plan parameters of the SkSP-R plan under these three distributions are determined through a nonlinear optimization problem. Tables are also constructed for each distribution. The advantages of the proposed plan over the existing sampling schemes are discussed. Application of the proposed plan is explained with the help of an example. The Birnbaum-Saunders distribution is economically superior to other two distributions in terms of minimum average sample number

A study on Blunt injury abdomen solid organ injuries

INTRODUCTION: Blunt Abdominal trauma is most commonly caused by road traffic accidents. The rapid increase in number of motor vehicles and its aftermath has caused rapid increase in number of victims to blunt abdominal trauma. Motor vehicle accidents account for 75 to 80 % of blunt abdominal trauma. 2 Blunt injury of abdomen is also a result of fall from height, assault with blunt objects, industrial mishaps, sport injuries, bomb blast and fall from riding bicycle. Blunt abdominal trauma is usually not obvious. Hence, often missed, unless, repeatedly looked for. Due to the delay in diagnosis and inadequate treatment of the abdominal injuries, most of the cases are fatal. Investigative modality can only supplement the clinical evaluation and cannot replace it in the diagnosis of blunt abdominal trauma. In spite of the best techniques and advances in diagnostic and supportive care, the morbidity and mortality remains at large. The reason for this could be due to the interval between trauma and hospitalization, inadequate and lack of appropriate surgical treatment, delay in diagnosis, post operative complications and associated trauma especially to head, thorax. In view of increasing number of vehicles and consequently road traffic accidents, this dissertation has been chosen to study the cases of blunt abdominal trauma. AIM OF THE STUDY: The objectives of the study are: 1. To evaluate the incidence of blunt abdominal trauma on solid viscera. 2. To evaluate etiology and various modes of presentation. 3. To evaluate various available investigations for the detection of solid organ injuries. 4. To evaluate various modalities of treatment available with aim to reduce the mortality and morbidity. 5. To evaluate common complications of solid organ injury in blunt trauma abdomen. MATERIALS AND METHOD : Patients admitted in Governtment Rajaji hospital, Madurai from April 2011 to May 2012 and study includes 40 cases. This is a prospective study conducted over 1 year. Methods of collection of data: After admission data for my study was collected by: 1. Direct interview with the patient or patient relatives accompanying the patient and obtaining a detailed history. 2. Thorough clinical examination. 3. Clinical findings and relevant diagnostic investigations performed over the patient. After initial resuscitation of the patients, thorough assessments for injuries were carried out in all the patients. Documentation of patients, which included, identification, history, clinical findings, diagnostic test, operative findings, operative procedures, complications during the stay in the hospital and during subsequent follow-up period, were all recorded on a Proforma specially prepared. Demographic data collected included the age, sex, occupation and nature and time of accident leading to the injury. CONCLUSION: Following conclusions can be drawn from our study: Blunt injury abdomen with solid organ injury forms considerable load of patients in our society. Most common age group involved is 21-30 years. Predominantly males are affected in large proportions. Road traffic accident forms the most common mode of injury. So efforts should be made to bring road traffic regulations into strict action and traffic norms regulated. Well established trauma care centres should be established at every Taluk hospital. Measures for early transport of the patients from the accident site to the trauma centres should be undertaken. Significant number of cases will have associated injuries with blunt injury abdomen like head injury, thoracic injury, extremity fractures. Clinical presentation is varied, sometimes confusing. Blunt injury abdomen is usually less obvious. Hence, repeated examination by multispecialty personnel in a specialized trauma centre is required. Erect abdomen X ray is a useful investigation to identify associated hollow viscus injury. Falling tires in serial hematocrit value indicates ongoing bleeding. With the advent of high resolution ultrasonography (FAST), DPL and FQA investigations are becoming less opted. CECT forms the core investigation of choice in dealing with blunt injury abdomen patients, and becomes more important in deciding operative versus conservative management. Early diagnosis and repeated clinical examination and use of appropriate investigations forms the key in managing BIA injuries. Associated extra abdominal injuries like head, thoracic and orthopedic injuries influenced the morbidity and mortality of the patients

A context based deep learning approach for unbalanced medical image segmentation

Automated medical image segmentation is an important step in many medical procedures. Recently, deep learning networks have been widely used for various medical image segmentation tasks, with U-Net and generative adversarial nets (GANs) being some of the commonly used ones. Foreground-background class imbalance is a common occurrence in medical images, and U-Net has difficulty in handling class imbalance because of its cross entropy (CE) objective function. Similarly, GAN also suffers from class imbalance because the discriminator looks at the entire image to classify it as real or fake. Since the discriminator is essentially a deep learning classifier, it is incapable of correctly identifying minor changes in small structures. To address these issues, we propose a novel context based CE loss function for U-Net, and a novel architecture Seg-GLGAN. The context based CE is a linear combination of CE obtained over the entire image and its region of interest (ROI). In Seg-GLGAN, we introduce a novel context discriminator to which the entire image and its ROI are fed as input, thus enforcing local context. We conduct extensive experiments using two challenging unbalanced datasets: PROMISE12 and ACDC. We observe that segmentation results obtained from our methods give better segmentation metrics as compared to various baseline methods.Comment: Accepted in ISBI 202