Microfinance and Third World Development: A Critical Analysis

Microfinance is emerging as an integral part of the new development paradigm, described by the phrase participation and development. Although the idea has become quite popular among donor agencies, development practitioners, and academicians, theoretical premises on which this idea is founded seem entirely unexamined. Accordingly, this article investigates the academic merits, as well as potential consequences, of this popular poverty alleviating model from the supply-side perspective and asks a provocative question: Do the microfinance ventures have features which suggest that the establishment of this new finance industry in the Third World countries might further complicate their pervasive poverty problems? The answer to this question appears affirmative to be affirmative. First, the microfinance idea is founded on two theoretical premises, both of which are very controversial. Second, the lack of microcredit is not the cause of the Third World\u27s deplorable poverty situation--a fact that suggests that the supply of microcredit cannot alleviate poverty in these countries. Finally, the promotion of the microfinance ventures in the Third World has potentials to create private groups, which have vested interests in perpetuating their prevailing poverty situation

Automatic time series forecasting: the forecast package for R.

Automatic forecasts of large numbers of univariate time series are often needed in business and other contexts. We describe two automatic forecasting algorithms that have been implemented in the forecast package for R. The first is based on innovations state space models that underly exponential smoothing methods. The second is a step-wise algorithm for forecasting with ARIMA models. The algorithms are applicable to both seasonal and non-seasonal data, and are compared and illustrated using four real time series. We also briefly describe some of the other functionality available in the forecast package.ARIMA models; automatic forecasting; exponential smoothing; prediction intervals; state space models; time series, R.

Automatic Time Series Forecasting: The forecast Package for R

Automatic forecasts of large numbers of univariate time series are often needed in business and other contexts. We describe two automatic forecasting algorithms that have been implemented in the forecast package for R. The first is based on innovations state space models that underly exponential smoothing methods. The second is a step-wise algorithm for forecasting with ARIMA models. The algorithms are applicable to both seasonal and non-seasonal data, and are compared and illustrated using four real time series. We also briefly describe some of the other functionality available in the forecast package.

A Novel Framework for Software Defined Wireless Body Area Network

Software Defined Networking (SDN) has gained huge popularity in replacing traditional network by offering flexible and dynamic network management. It has drawn significant attention of the researchers from both academia and industries. Particularly, incorporating SDN in Wireless Body Area Network (WBAN) applications indicates promising benefits in terms of dealing with challenges like traffic management, authentication, energy efficiency etc. while enhancing administrative control. This paper presents a novel framework for Software Defined WBAN (SDWBAN), which brings the concept of SDN technology into WBAN applications. By decoupling the control plane from data plane and having more programmatic control would assist to overcome the current lacking and challenges of WBAN. Therefore, we provide a conceptual framework for SDWBAN with packet flow model and a future direction of research pertaining to SDWBAN.Comment: Presented on 8th International Conference on Intelligent Systems, Modelling and Simulatio

Predicting Policy Violations in Policy Based Proactive Systems Management

The continuous development and advancement in networking, computing, software and web technologies have led to an explosive growth in distributed systems. To ensure better quality of service (QoS), management of large scale distributed systems is important. The increasing complexity of distributed systems requires significantly higher levels of automation in system management. The core of autonomie computing is the ability to analyze data about the distributed system and to take actions. Such autonomic management should include some ability to anticipate potential problems and take action to avoid them that is, it should be proactive. System management should be proactive in order to be able to identify possible faults before they occur and before they can result in severe degradation in performance. In this thesis, our goal is to predict policy violations and take actions ahead of time in order to achieve proactive management in a policy based system.We implemented different prediction algorithm to predict policy violations. Based on the prediction decision, proactive actions are implemented in the system. Adaptive proactive action approach is also introduced to increase the performance of the proactive management system

Coupling Mobile Technology, Position Data Mining, and Attitude toward Risk to Improve Construction Site Safety

Construction sites comprise constantly moving heterogeneous resources that interact in close proximity of each other. The sporadic nature of such interactions creates an accident prone physical space surrounding workers. Despite efforts to improve site safety using location-aware proximity sensing techniques, major scientific gaps still remain in reliably forecasting impending hazardous scenarios before they occur. In the research documented in this thesis, spatiotemporal data of workers and site hazards are fused with a quantifiable model of an individual\u27s attitude toward risk to generate proximity-based safety alerts in real time. In particular, two trajectory prediction models, namely polynomial regression (PR) and hidden Markov model (HMM) are investigated and their effectiveness in predicting a worker\u27s position given his or her past movement trajectory is evaluated. Next, HMM prediction is further improved and calibrated by factoring in a worker\u27s risk profile, a measure of his affinity for or aversion to risky behavior near hazards. Finally, a mobile application is designed and tested in a series of field experiments involving trajectories of different shape and complexity to verify the applicability and value of the designed methodology in addressing construction safety-related problems. Results demonstrate that the developed risk-calibrated HMM-based motion trajectory prediction can reliably detect unsafe movements and impending collision events

Experimental and Numerical Investigations on Aerodynamic Characteristics of Savonius Wind Turbine with Various Overlap Ratios

Savonius wind turbine is the simplest type of vertical axis rotor that has a relatively low efficiency. Operation of the Savonius wind turbine is based on the difference of the drag force on its semi-spherical blades, depending on whether the wind is striking the convex or the concave part of the blades. This turbine is being used in various countries around the world due to the simplistic design, cheap technology for construction, and a good starting torque independent of wind direction at low wind speeds. Due to its simple design and low construction cost, this rotor is mainly used for water pumping as well as wind power on small scale. The main goal of this current research is to investigate the aerodynamic performance of Savonius wind turbine. Wind tunnel investigation was carried out to find the aerodynamic characteristics like, drag coefficient, torque coefficient, and power coefficient of three blade Savonius wind turbine rotor models with and without overlap ratio (ratio of overlap distance between two adjacent blades and rotor diameter ,OR = a/D) at various Reynolds numbers. Numerical investigation was also carried out to find those aerodynamic characteristics. For numerical investigation, commercial computational fluid dynamic (CFD) software GAMBIT and FLUENT were used. Afterwards those two results were compared for verification. Three different models with different overlap ratio were designed and fabricated for the current study to find the effect of overlap ratios. The results from the experimental part of the research show a significant effect of overlap ratio and Reynolds number on the improvement of aerodynamic performance of the Savonius wind turbine. At higher Reynolds number turbine Model without overlap ratio gives better aerodynamic coefficients and at lower Reynolds number Model with moderate overlap ratio gives better results

Cities within a city : planning policies and intra-urban inequalities in Greater Sydney

Numerous research papers and reports have acknowledged Sydney’s inequalities in terms of place-based difficulties, governance, migrant settlement, displacement, gentrification, housing development, and affordability. However, that research is not specific to the urban inequalities related to urban policy applications. Considering the gap, this research investigates the urban planning practices, their impacts and outcomes in Sydney in light of case studies, secondary evidence, empirical data and critical urban philosophies. The key questions in this research are: how is Sydney transforming into an increasingly unequal city? how do influential socio-economic actors contribute to urban inequalities? what is the situation of the rights to the city in the disadvantaged geographies of Sydney? And how are the life and livelihoods of Sydney’s underprivileged residents disproportionately affected by the COVID-19 pandemic? This research employs critical theory as a crucial lens to analyse the socio-economic disparities in urban spaces. The critical analysis outlines that the NSW urban planning system, practices and outcomes influence the cities within a city divide in Sydney, supporting secondary content and empirical data. The affluent areas are prioritised in neoliberal urban growth with less housing and population targets and expanded opportunities. In contrast, the disadvantaged regions have extreme urbanisation instead of much needed urban opportunities and infrastructure support. The NSW urban planning practices are strongly influenced by socio-economic power; consequently, high socio-economics northern and eastern areas of Sydney influence the urban growth and development. They are able to prevent densification in their areas. On the other hand, the less affluent residents of low socio-economic Western Sydney areas lack the power to resist large volumes of additional dwellings leading to fast densification. The critical analysis of this research outlines Sydney’s urban policy practices, planning powers, and urban rights divide as an ‘east–west divide’. This research points out that empowered local politics, expanded communication, enhanced consultation, and improved community engagement mechanisms are needed to effectively engage Western Sydney residents in the planning process. This research develops the ‘Equal, Resilient and Sustainable Western Sydney Model’ to address the existing urban divide and build equal, sustainable and resilient cities and communities. This thesis also proposes numerous strategies to ensure Western Sydney residents’ active and robust community engagement. In addition, better and accessible education, improved human resources, innovation, technological transformation, and efficient infrastructure are vital to enhancing socio-economic development in disadvantaged Western Sydney