851 resultados para Graph mining
Resumo:
Why do people engage in artisanal and small-scale mining (ASM) – labour-intensive mineral extraction and processing activity – across sub-Saharan Africa? This paper argues that ‘agricultural poverty’, or hardship induced by an over-dependency on farming for survival, has fuelled the recent rapid expansion of ASM operations throughout the region. The diminished viability of smallholder farming in an era of globalization and overreliance on rain-fed crop production restricted by seasonality has led hundreds of thousands of rural African families to ‘branch out’ into ASM, a move made to secure supplementary incomes. Experiences from Komana West in Southwest Mali and East Akim District in Southeast Ghana are drawn upon to illustrate how a movement into the ASM economy has impacted farm families, economically, in many rural stretches of sub-Saharan Africa.
Safeguarding livelihoods or exacerbating poverty?: Artisanal mining and formalization in West Africa
Resumo:
In recent years, policy mechanisms to support a formalized artisanal and small-scale mining (ASM) sector in sub-Saharan Africa have gained increasing currency. Proponents of formalization argue that most social and environmental problems associated with the sector stem from the fact that ASM is predominantly unregulated and operates outside the legal sphere. This paper critically examines recent efforts to formalize artisanal and small-scale mining inWest Africa, drawing upon recent fieldwork carried out in Sierra Leone, Ghana and Mali. In exploring the sector’s livelihood dimensions, the analysis suggests that bringing unregulated, informal mining activities into the legal domain remains a considerable challenge. The paper concludes by confirming the urgent need to refocus formalization strategies on the main livelihood challenges and constraints of small-scale miners themselves, if poverty is to be alleviated and more benefits are to accrue to depressed communities in mineral-rich regions.
Resumo:
The reform of previously state-owned and operated industries in many Less Developed Countries (LDCs) provide contrary experiences to those in the developed world, which have generally had more equitable distributional impacts. The economic reform policies proposed by the so-called 'Washington Consensus' state that privatisation provides governments with opportunities to raise revenues through the sale of under-performing and indebted state industries, thereby reducing significant fiscal burdens, and, at the same time, facilitating influxes of foreign capital, skills and technology, with the aim of improving operations and a "trickle-down" of benefits. However, experiences in many LDCs over the last 15-20 years suggest that reform has not solved the problem of chronic public-sector debt, and that poverty and socio-economic inequalities have increased during this period of 'neo-liberal' economics. This paper does not seek to challenge the policies themselves, but rather argues that the context in which reform has often taken place is of fundamental significance. The industry-centric policy advice provided by the IFIs typically causes a 'lock-in' of inequitably distributed 'efficiency gains', providing minimal, if any, benefits to impoverished groups. These arguments are made using case study analysis from the electricity and mining sectors.
Resumo:
Over the past 10-15 years, several governments have implemented an array of technology, support-related, sustainable livelihoods (SL) and poverty-reduction projects for artisanal and small-scale mining (ASM). In the majority of cases, however, these interventions have failed to facilitate improvements in the industry's productivity and raise the living standards of the sector's subsistence operators. This article argues that a poor understanding of the demographics of target populations has precipitated these outcomes. In order to strengthen policy and assistance in the sector, governments must determine, with greater precision, the number of people operating in ASM regions, their origins and ethnic backgrounds, ages, and educational levels. This can be achieved by carrying out basic and localized census work before promoting ambitious sector-specific projects aimed at improving working conditions in the industry.
Resumo:
Since the implementation of Ghana's national Structural Adjustment Programme (SAP), policies associated with the programme have been criticized for perpetuating poverty within the country's subsistence economy. This article brings new evidence to bear on the contention that the SAP has both fuelled the uncontrolled growth of informal, poverty-driven artisanal gold mining and further marginalized its impoverished participants. Throughout the adjustment period, it has been a central goal of the government to promote the expansion of large-scale gold mining through foreign investment. Confronted with the challenge of resuscitating a deteriorating gold mining industry, the government introduced a number of tax breaks and policies in an effort to create an attractive investment climate for foreign multinational mining companies. The rapid rise in exploration and excavation activities that has since taken place has displaced thousands of previously-undisturbed subsistence artisanal gold miners. This, along with a laissez faire land concession allocation procedure, has exacerbated conflicts between mining parties. Despite legalizing small-scale mining in 1989, the Ghanaian government continues to implement procedurally complex and bureaucratically unwieldy regulations and policies for artisanal operators which have the effect of favouring the interests of established large-scale miners.
Resumo:
Software representations of scenes, i.e. the modelling of objects in space, are used in many application domains. Current modelling and scene description standards focus on visualisation dimensions, and are intrinsically limited by their dependence upon their semantic interpretation and contextual application by humans. In this paper we propose the need for an open, extensible and semantically rich modelling language, which facilitates a machine-readable semantic structure. We critically review existing standards and techniques, and highlight a need for a semantically focussed scene description language. Based on this defined need we propose a preliminary solution, based on hypergraph theory, and reflect on application domains.
Resumo:
There is growing interest in the ways in which the location of a person can be utilized by new applications and services. Recent advances in mobile technologies have meant that the technical capability to record and transmit location data for processing is appearing in off-the-shelf handsets. This opens possibilities to profile people based on the places they visit, people they associate with, or other aspects of their complex routines determined through persistent tracking. It is possible that services offering customized information based on the results of such behavioral profiling could become commonplace. However, it may not be immediately apparent to the user that a wealth of information about them, potentially unrelated to the service, can be revealed. Further issues occur if the user agreed, while subscribing to the service, for data to be passed to third parties where it may be used to their detriment. Here, we report in detail on a short case study tracking four people, in three European member states, persistently for six weeks using mobile handsets. The GPS locations of these people have been mined to reveal places of interest and to create simple profiles. The information drawn from the profiling activity ranges from intuitive through special cases to insightful. In this paper, these results and further extensions to the technology are considered in light of European legislation to assess the privacy implications of this emerging technology.
Resumo:
Recently major processor manufacturers have announced a dramatic shift in their paradigm to increase computing power over the coming years. Instead of focusing on faster clock speeds and more powerful single core CPUs, the trend clearly goes towards multi core systems. This will also result in a paradigm shift for the development of algorithms for computationally expensive tasks, such as data mining applications. Obviously, work on parallel algorithms is not new per se but concentrated efforts in the many application domains are still missing. Multi-core systems, but also clusters of workstations and even large-scale distributed computing infrastructures provide new opportunities and pose new challenges for the design of parallel and distributed algorithms. Since data mining and machine learning systems rely on high performance computing systems, research on the corresponding algorithms must be on the forefront of parallel algorithm research in order to keep pushing data mining and machine learning applications to be more powerful and, especially for the former, interactive. To bring together researchers and practitioners working in this exciting field, a workshop on parallel data mining was organized as part of PKDD/ECML 2006 (Berlin, Germany). The six contributions selected for the program describe various aspects of data mining and machine learning approaches featuring low to high degrees of parallelism: The first contribution focuses the classic problem of distributed association rule mining and focuses on communication efficiency to improve the state of the art. After this a parallelization technique for speeding up decision tree construction by means of thread-level parallelism for shared memory systems is presented. The next paper discusses the design of a parallel approach for dis- tributed memory systems of the frequent subgraphs mining problem. This approach is based on a hierarchical communication topology to solve issues related to multi-domain computational envi- ronments. The forth paper describes the combined use and the customization of software packages to facilitate a top down parallelism in the tuning of Support Vector Machines (SVM) and the next contribution presents an interesting idea concerning parallel training of Conditional Random Fields (CRFs) and motivates their use in labeling sequential data. The last contribution finally focuses on very efficient feature selection. It describes a parallel algorithm for feature selection from random subsets. Selecting the papers included in this volume would not have been possible without the help of an international Program Committee that has provided detailed reviews for each paper. We would like to also thank Matthew Otey who helped with publicity for the workshop.
Resumo:
This paper contributes to the debate on child labor in small-scale mining communities, focusing specifically on the situation in sub-Saharan Africa. It argues that the child labor now widespread in many of the region’s small-scale mining communities is a product of a combination of cultural issues, household-level poverty and rural livelihood diversification. Experiences from Komana West, a subsistence gold panning area in Southern Mali, are drawn upon to make this case. The findings suggest that the sector’s child labor “problem” is far more nuanced than international organizations and policymakers have diagnosed.
Resumo:
This paper critically reflects on why, in many rural stretches of sub-Saharan Africa, scores of people engage in artisanal and small-scale mining (ASM) activity – low-tech, labour intensive mineral extraction – for lengthy periods of time. It argues that a large share of the region’s ASM operators have mounting debts which prevent them from pursuing alternative, less arduous, employment. The paper concludes with an analysis of findings from research carried out by the author in Talensi-Nabdam District, Northern Ghana, which captures the essence of the poverty trap now plaguing so many ASM communities in sub-Saharan Africa.
Resumo:
Artisanal and small-scale mining (ASM) is replacing smallholder farming as the principal income source in parts of rural Ghana. Structural adjustment policies have removed support for the country’s smallholders, devalued their produce substantially and stiffened competition with large-scale counterparts. Over one million people nationwide are now engaged in ASM. Findings from qualitative research in Ghana’s Eastern Region are drawn upon to improve understanding of the factors driving this pattern of rural livelihood diversification. The ASM sector and farming are shown to be complementary, contrary to common depictions in policy and academic literature.