An Approach for Effort Estimation having Reusable Components in Software Development

Estimation of the effort required for development has been researched for over 25 years now. Still there exists no concrete solution to estimate the development effort. Prior experience in similar type of projects is a key for business today. This paper proposes an Effort Estimation Model named REBEE based on the reusable matrices to effectively estimate the effort to be involved for development. A project is assumed to consist of multiple modules and the reusability factor of each module is considered in the technique described here. REBEE utilizes fuzzy logic and dynamic neural networks to achieve its goal. Based on the experimental evaluation discussed in this paper it is evident that this model accurately predicts the effort involved on heterogeneous project types

REBEE- Reusability Based Effort Estimation Technique using Dynamic Neural Network

Software Effort Estimation has been researched for over 25 years but until today no real effective model could be designed that could efficiently gauge the effort required for heterogeneous project data. Reusability factors of software development have been used to design a new effort estimation model called REBEE. This encompasses the usage of Fuzzy Logic and Dynamic Neural Networks. The experimental evaluation of the model depicts efficient effort estimation over varied project types

Sorting Technique- An Efficient Approach for Data Mining

As the new data or updates are arriving constantly, it becomes very difficult to handle data in an efficient manner. Moreover, if data is not refreshed it will soon become of no use. Hence data should be updated on regular mode so that it do not obsolete in coming future. In traditional work several other approaches or methods like page ranking, i2mapreduce( that is extension of Map Reduce) were used to enhance performance and increase computation speed as well as run-time processing. But as we have seen the performance is not up to that level which is required in current environment. So, to overcome these drawbacks, in this paper sorting technique is proposed that can enhance mean value and overall performance

Metamorphosing Indian Blockchain ecosystem

A blockchain is a decentralised database that is shared across computer network nodes. A blockchain acts as a database, storing information in a digital format. The study primarily aims to explore how in the future, block chain technology will alter several areas of the Indian economy. The current study aims to obtain a deeper understanding of blockchain technology's idea and implementation in India, as well as the technology's potential as a disruptive financial technological innovation. Secondary sources such as reports, journals, papers, and websites were used to compile all the data. Current and relevant information were utilised to help understand the research goals. All the information is rationally organised to fulfil the objectives. The current research focuses on recommendations for enhancing India's Blockchain ecosystem so that it may become one of the best in the world at utilising this new technology

Sorting Technique- An Improvement towards HDD Utilization in HADOOP

A data is tremendously increasing everyday due to updates that are updated after a particular time interval. Therefore it is very hard to handle such a large data that is updated on common basis. Ample number of techniques was proposed in order to enhance the performance and efficiency. In this paper, a technique called as “sorting technique” is implemented so as to increase the mean value. Load of hadoop cluster will decrease in steeply manner when this technique is implemented. The results clearly defines the efficiency of the technique which is used and hence it also proves to be efficient than the traditional techniques

Prevalence of psychiatric co morbidities in bronchial asthma and chronic obstructive pulmonary disease patients in north Indian population cohort

Background: Psychiatric co morbidities tend to occur quite frequently in patients of chronic respiratory diseases mainly bronchial asthma and Chronic Obstructive Pulmonary Disease (COPD) but still it is highly under diagnosed. Aim and objective of the study was to find out the prevalence of psychiatric co morbidities in asthma and COPD and to correlate them with disease severity according to Global Initiative against Obstructive Lung Disease (GOLD) and Global Initiative against Asthma (GINA) guidelines.Methods: Study was conducted in Department of TB and Chest in association with Department of Psychiatry of Punjab Institute of Medical Sciences, a secondary care medical college in north India. A total 204 patients, 68 of bronchial asthma, 68 0f COPD and 68 were controls included in the study. Diagnosis and severity of respiratory diseases was assessed by spirometry. Evaluation of psychiatric co morbidities was done using the MINI international neuropsychiatric interview questionnaire.Results: The frequency of psychiatric co morbidities in COPD patients was significantly higher (32.4%) compared to patients of bronchial asthma (20.6%). The most common co morbidity in both arms was generalized anxiety disorder (17.6% in COPD patients and 10.3% in patients of bronchial asthma.Conclusions: COPD patients have a higher frequency of psychiatric co morbidities compared to bronchial asthma patients and control population. These should be properly screened and treated.

Comparative analysis of MTP -493G/T and ABCG2 34G/A polymorphisms and theirs expression in HIV-associated lipodystrophy patients

HIV-associated lipodystrophy (HIVLD) is a metabolic condition with an irregularity in the production of lipoprotein particles, and its occurrence varies among HIV-infected patients. MTP and ABCG2 genes have a role in the transport of lipoproteins. The polymorphisms of MTP -493G/T and ABCG2 34G/A affect its expression and influence the secretion and transportation of lipoproteins. Hence, we investigated the MTP -493G/T and ABCG2 34G/A polymorphisms in 187 HIV-infected patients (64 with HIVLD and 123 without HIVLD) along with 139 healthy controls using polymerase chain reaction (PCR)-restriction fragment length polymorphism and expression analysis using real-time PCR. ABCG2 34A allele showed an insignificantly reduced risk of LDHIV severity [P = 0.07, odds ratio (OR) = 0.55]. MTP -493T allele exhibited a non-significantly reduced risk for the development of dyslipidemia (P = 0.08, OR = 0.71). In patients with HIVLD, the ABCG2 34GA genotype was linked with impaired low-density lipoprotein levels and showed a reduced risk for LDHIV severity (P = 0.04, OR = 0.17). In patients without HIVLD, the ABCG2 34GA genotype was associated with impaired triglyceride levels with marginal significance and showed an increased risk for the development of dyslipidemia (P = 0.07, OR = 2.76). The expression level of MTP gene was 1.22-fold decreased in patients without HIVLD compared with that in patients with HIVLD. ABCG2 gene was upregulated 2.16-fold in patients with HIVLD than in patients without HIVLD. In conclusion, MTP -493C/T polymorphism influences the expression level of MTP in patients without HIVLD. Individuals without HIVLD having ABCG2 34GA genotype with impaired triglyceride levels may facilitate dyslipidemia risk