Machine Learning Playground

Machine learning is a science that “learns” about the data by finding unique patterns and relations in the data. There are a lot of libraries or tools available for processing machine learning datasets. You can upload your dataset in seconds and quickly start using these tools to get prediction results in a few minutes. However, generating an optimal model is a time consuming and tedious task. The tunable parameters (hyper-parameters) of any machine learning model may greatly affect the accuracy metrics. While most of the tools have models with default parameter setting to provide good results, they can often fail to provide optimal results for reallife datasets. This project will be to develop a GUI application where a user could upload a dataset and dynamically visualize accuracy results based on the selected algorithm and its hyperparameters

Religious Political Groups and Democracy in Tajikistan

This paper is an attempt to develop understanding of the interplay of different actors in Tajikistan after its independence from Soviet rule Its main focus is to explore the revival role and ideals of religious groups in Tajikistan as well the status and future prospects for democracy in the republi

Economic Feasibility of Parallel Education Policies in India

As per the survey by ASSOCHAM about 87 per cent of primary school children and up to 95 per cent of high school students received private tutoring in metro cities This paper is prepared on basis of conditions and challenges a student is facing because of his educational needs and aspirations It strived to get into the causes and consequence of following two platforms i e Government Private aided or unaided schools and Private tuitions centers coaching institutions As these both supplement the learning of a student but somehow this policy is not having favorable outcomes It has found a student academic schedule prolonged and absence of proper sphere to show his creativity or to present his innovative ideas ultimately adversely affecting his overall development leading to degradation of valuable human resources This paper also focused towards the growing market of private tutors and coaching institutions to cater the demand of students who see as an option to earn livelihood or profit putting additional burden on the family budget It has further incorporated the views and opinions of school teachers parents taking note of their concer

Ground improvement for ring beam tank foundation compared between vibro replacement against combination of dynamic techniques with numerical models

Construction of large tanks are often carried out implementing a ring beam foundation. Majority of the load is transferred the ground, therefore, in areas of poor ground conditions, additional measures are taken to avoid geotechnical failure. Various methods exist for ground improvement, however, techniques such as piling and Vibro-Replacement are commonly implemented, due to their deep depth of improvement and flexibility of applicability for a wide range of soil profiles. However, alternative techniques may be implemented which could prove more efficient and even cost effective. Dynamic techniques, due to their fast rate of production, reduced operation costs and impressive efficiency prove as viable options. But since dynamic techniques have limitations with soil type and depth of improvement, for stratified geotechnical profiles, they may only be carried out in a combination with one another, which may deter engineers for opting to implement them. In the current study, the efficiency of ground improvement for a ring beam tank foundation shall be compared between Vibro-Replacement against combination of dynamic techniques with numerical models, to provide an insight between their capabilities and preliminary cost estimations shall also be carried out to a lesser extent to get an idea of the economic factors that affect decision making for ground improvement operations

Integration, decoupling and the global financial crisis: A global perspective

The recent global recession requires policy makers to identify the relative importance of shock transmission mechanisms in each region and devise counter policy measures against future idiosyncratic shocks. In the last decade, world dynamics have changed considerably due to increased openness and integration requiring considering business cycles at regional levels. This paper analyzes the business cycle movements of the EU, ASEAN+3, NAFTA, MERCOSUR and SAARC regions to investigate why the subprime mortgage crisis of 2007 did not spread globally compared to the crisis that began with the fall of Lehman Brothers in September 2008. Employing a Panel Vector Autoregressive framework (PVEC), this study finds that the subprime mortgage crisis shock originated in the real sector (falling US housing prices) and was transmitted through trade variables. Due to absence of short term trade variables transmission mechanism in all regions except the MERCOSUR and SAARC, the shock did not spread widely to other regions. Even in the MERCOSUR and SAARC, due to limited goods exports exposure to the US, the shock was not significant. Resultantly, these regions exhibited a decoupling phenomenon during the subprime mortgage crisis. In contrast, the second shock originated with the fall of Lehman Brothers in 2008 and was transmitted through financial variables. Due to the presence of the short term causal relationship of the financial variable with GDP in all regions except SAARC, the slowdown contagion spread to most regions. As a result, the slowdown triggered the trade variables shock transmission mechanism and the SAARC region was also affected. Consequently, a business cycle convergence phenomenon was observed in the regions. Therefore, business cycles decoupling and convergence phenomena in the regions depend not only on the origin of the shock but also on the relative importance of the transmission mechanisms in each region.Integration, Decoupling, Financial crisis, EU, NAFTA, ASEAN, MERCOSUR, SAARC, Business cycle, FDI, Exports, Intra industry Trade, Sub prime mortgage crisis, Lehman Brothers, Short term capital flows, Panel Cointegration, Panel stationarity, Panel Vector Error Correction (PVEC)

The burden and cost of sickness absenteeism amongst healthcare workers at a teaching hospital in South Africa. A cross-sectional study.

A high burden of sickness-related absenteeism (SRA) amongst healthcare workers (HCWs) may impact health service delivery. The burden is known in high-income settings but not well evaluated in low and middle income (LMIC) settings and absent within a South African context. To determine the prevalence, associated medical conditions and cost of SRA amongst HCWs in a LMIC setting, we evaluated Human Resource (HR) absence records from a teaching hospital in South Africa over a 3 year period. Of the 3,543 HCW employed during the study period, 78% (n = 2,748) had at least 1 SRA episode. The overall SRA prevalence was 2.63%. The mean duration of absence was 2.25 days per episode and the mean frequency was 2.65 episodes per annum. Conditions of the musculoskeletal system (40.1%) were the most commonly reported, followed by acute infections of the upper respiratory tract (13.2%) and other respiratory conditions (6.2%). The total direct cost SRA was US$5,105,061.78 over the study period and the mean direct SRA cost per person was US$1,857.74 per episode. The results demonstrate a higher SRA burden compared with studies in similar settings and prompts further research into the causative factors and targeted risk mitigation strategies