Real-Time LWD Sonic Semblance Image and the Step Change in LWD Sonic Applications - A Case Study From Latin America (Mexico)

2013 ◽  
Author(s):  
Medhat Mickael ◽  
Craig Barnett ◽  
Chris Maranuk ◽  
Rebecca Nye ◽  
Mohamed Diab ◽  
...  
Keyword(s):  
Latin America ◽  
Real Time ◽  
Step Change

ENTREPREUNERSHIP AND MICRO-FINANCE IN EXTREME POVERTY CIRCUMSTANCES — CHALLENGES AND PROSPECTS: THE CASE OF ZIMBABWE

2013 ◽  
Vol 18 (01) ◽  
pp. 1350001 ◽  
Author(s):  
TENDAI MURISA ◽  
TENDAI CHIKWECHE
Keyword(s):  
Latin America ◽  
Real Time ◽  
Poverty Reduction ◽  
Financial Inclusion ◽  
Extreme Conditions ◽  
Significant Growth ◽  
Alternative Approach ◽  
Inclusive Approach ◽  
Research Stream

Using an on-going real case study of a micro-finance project modeled on financial inclusion in Zimbabwe, a country with high levels of poverty, we provide real time insights on entrepreneurship and micro-finance in this environment focusing on the nature of challenges faced by entrepreneurs and potential solutions to these challenges. While acknowledging this is a research stream that has dominated micro-finance, our study extends the scope of research beyond Asia and Latin America to include insights from an African market where micro-finance has recorded significant growth yet very few stories are told about these experiences. Our case study provides an opportunity to reflect on emerging and previously held insights in real time using a project that is still in the process of dealing with these challenges. We then go onto illustrate how our inclusive approach to serving the unbanked segment in Zimbabwe has potential for broader contribution to poverty reduction among citizens who are exposed to extreme conditions of poverty. Our paper also outlines an alternative approach of solutions to the challenges faced by micro-finance entrepreneurs, which could be applied by entrepreneurs in environments facing similar challenges.

The Genesis and Internal Dynamics of El Salvador's People's Revolutionary Army, 1970–1976

2014 ◽  
Vol 38 (01) ◽  
pp. 102-129
Author(s):  
ALBERTO MARTÍN ÁLVAREZ ◽  
EUDALD CORTINA ORERO
Keyword(s):  
Latin America ◽  
El Salvador ◽  
Early Years ◽  
Left Wing ◽  
Internal Dynamics ◽  
Internal Coherence ◽  
The 1960S

AbstractUsing interviews with former militants and previously unpublished documents, this article traces the genesis and internal dynamics of the Ejército Revolucionario del Pueblo (People's Revolutionary Army, ERP) in El Salvador during the early years of its existence (1970–6). This period was marked by the inability of the ERP to maintain internal coherence or any consensus on revolutionary strategy, which led to a series of splits and internal fights over control of the organisation. The evidence marshalled in this case study sheds new light on the origins of the armed Salvadorean Left and thus contributes to a wider understanding of the processes of formation and internal dynamics of armed left-wing groups that emerged from the 1960s onwards in Latin America.

Pollution based real time control strategies for combined sewer systems

1997 ◽  
Vol 36 (8-9) ◽  
pp. 331-336 ◽  
Author(s):  
Gabriela Weinreich ◽  
Wolfgang Schilling ◽  
Ane Birkely ◽  
Tallak Moland
Keyword(s):  
Real Time ◽  
Control Strategies ◽  
Ammonia Nitrogen ◽  
Simple Extension ◽  
Real Time Control ◽  
Time Control ◽  
Sewer Systems ◽  
Receiving Waters ◽  
Tunnel System

This paper presents results from an application of a newly developed simulation tool for pollution based real time control (PBRTC) of urban drainage systems. The Oslo interceptor tunnel is used as a case study. The paper focuses on the reduction of total phosphorus Ptot and ammonia-nitrogen NH4-N overflow loads into the receiving waters by means of optimized operation of the tunnel system. With PBRTC the total reduction of the Ptot load is 48% and of the NH4-N load 51%. Compared to the volume based RTC scenario the reductions are 11% and 15%, respectively. These further reductions could be achieved with a relatively simple extension of the operation strategy.

scholarly journals Determinants of urban sprawl in Latin America: evidence from Santiago de Chile

2021 ◽  
Vol 1 (8) ◽  
Author(s):  
Cristian Silva ◽  
Francisco Vergara-Perucich
Keyword(s):  
Latin America ◽  
Urban Sprawl ◽  
Capital City ◽  
Design And Implementation ◽  
Policy Context ◽  
Santiago De Chile ◽  
City Regions ◽  
Policy Frameworks ◽  
Social And Environmental Impacts

AbstractUrban sprawl has been widely discussed in regard of its economic, political, social and environmental impacts. Consequently, several planning policies have been placed to stop—or at least restrain—sprawling development. However, most of these policies have not been successful at all as anti-sprawl policies partially address only a few determinants of a multifaceted phenomenon. This includes processes of extended suburbanisation, peri-urbanisation and transformation of fringe/belt areas of city-regions. Using as a case study the capital city of Chile—Santiago—thirteen determinants of urban sprawl are identified as interlinked at the point of defining Santiago's sprawling geography as a distinctive space that deserves planning and policy approaches in its own right. Unpacking these determinants and the policy context within which they operate is important to better inform the design and implementation of more comprehensive policy frameworks to manage urban sprawl and its impacts.

scholarly journals A Computer Vision-Based Occupancy and Equipment Usage Detection Approach for Reducing Building Energy Demand

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 156
Author(s):  
Paige Wenbin Tien ◽  
Shuangyu Wei ◽  
John Calautit
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Energy Demand ◽  
Energy Savings ◽  
Internal Heat ◽  
Electrical Equipment ◽  
Building Energy ◽  
Hvac Systems ◽  
Equipment Usage

Because of extensive variations in occupancy patterns around office space environments and their use of electrical equipment, accurate occupants’ behaviour detection is valuable for reducing the building energy demand and carbon emissions. Using the collected occupancy information, building energy management system can automatically adjust the operation of heating, ventilation and air-conditioning (HVAC) systems to meet the actual demands in different conditioned spaces in real-time. Existing and commonly used ‘fixed’ schedules for HVAC systems are not sufficient and cannot adjust based on the dynamic changes in building environments. This study proposes a vision-based occupancy and equipment usage detection method based on deep learning for demand-driven control systems. A model based on region-based convolutional neural network (R-CNN) was developed, trained and deployed to a camera for real-time detection of occupancy activities and equipment usage. Experiments tests within a case study office room suggested an overall accuracy of 97.32% and 80.80%. In order to predict the energy savings that can be attained using the proposed approach, the case study building was simulated. The simulation results revealed that the heat gains could be over or under predicted when using static or fixed profiles. Based on the set conditions, the equipment and occupancy gains were 65.75% and 32.74% lower when using the deep learning approach. Overall, the study showed the capabilities of the proposed approach in detecting and recognising multiple occupants’ activities and equipment usage and providing an alternative to estimate the internal heat emissions.

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