211,930 research outputs found
Metrics for Aspect Mining Visualization
Aspect oriented programming has over the last decade become the subject of intense research within the domain of software engineering. Aspect mining, which is concerned with identification of cross cutting concerns in legacy software, is an important part of this domain. Aspect refactoring takes the identified cross cutting concerns and converts these into new software constructs called aspects. Software that have been transformed using this process becomes more modularized and easier to comprehend and maintain. The first attempts at mining for aspects were dominated by manual searching and parsing through source code using simple tools. More sophisticated techniques have since emerged including evaluation of execution traces, code clone detection, program slicing, dynamic analysis, and use of various clustering techniques. The focus of most studies has been to maximize aspect mining performance measured by various metrics including those of aspect mining precision and recall. Other metrics have been developed and used to compare the various aspect mining techniques with each other. Aspect mining automation and presentation of aspect mining results has received less attention. Automation of aspect mining and presentation of results conducive to aspect refactoring is important if this research is going to be helpful to software developers. This research showed that aspect mining can be automated. A tool was developed which performed automated aspect mining and visualization of identified cross cutting concerns. This research took a different approach to aspect mining than most aspect mining research by recognizing that many different categories of cross cutting concerns exist and by taking this into account in the mining process. Many different aspect mining techniques have been developed over time, some of which are complementary. This study was different than most aspect mining research in that multiple complementary aspect mining algorithms was used in the aspect mining and visualization process
Algorithms for Extracting Frequent Episodes in the Process of Temporal Data Mining
An important aspect in the data mining process is the discovery of patterns having a great influence on the studied problem. The purpose of this paper is to study the frequent episodes data mining through the use of parallel pattern discovery algorithms. Parallel pattern discovery algorithms offer better performance and scalability, so they are of a great interest for the data mining research community. In the following, there will be highlighted some parallel and distributed frequent pattern mining algorithms on various platforms and it will also be presented a comparative study of their main features. The study takes into account the new possibilities that arise along with the emerging novel Compute Unified Device Architecture from the latest generation of graphics processing units. Based on their high performance, low cost and the increasing number of features offered, GPU processors are viable solutions for an optimal implementation of frequent pattern mining algorithmsFrequent Pattern Mining, Parallel Computing, Dynamic Load Balancing, Temporal Data Mining, CUDA, GPU, Fermi, Thread
HAM: Cross-cutting Concerns in Eclipse
As programs evolve, newly added functionality sometimes does no
longer align with the original design, ending up scattered across the
software system. Aspect mining tries to identify such cross-cutting
concerns in a program to support maintenance, or as a first step
towards an aspect-oriented program. Previous approaches to aspect
mining applied static or dynamic program analysis techniques to a
single version of a system.We leverage all versions from a system\u27s
CVS history to mine aspect candidates with our Eclipse plug-in
HAM: when a single CVS commit adds calls to the same (small)
set of methods in many unrelated locations, these method calls are
likely to be cross-cutting. HAM employs formal concept analysis to
identify aspect candidates. Analysing one commit at a time makes
the approach scale to industrial-sized programs. In an evaluation we
mined cross-cutting concerns from Eclipse 3.2M3 and found that
up to 90% of the top-10 aspect candidates are truly cross-cutting
concerns
Entanglements and disentanglements : a posthuman approach to mercury use in artisanal and small-scale gold mining in Antioquia, Colombia : a thesis presented in partial fulfilment of the requirements for the degree of Master of Arts in Social Anthropology at Massey University, Palmerston North, New Zealand
This research uses qualitative research techniques and posthuman theories to investigate the dynamic relationship between artisanal and small-scale gold miners and mercury in the context of Antioquia, Colombia. This is done to contribute to understandings of, and inform potential solutions for, the global environmental problem that is mercury pollution from artisanal and small-scale gold mining (ASGM). Miners come to know mercury through practices, and through these practices, mercury comes to be co-constitutive of an informal ASGM industry. Mercury provides an easy yet profitable mode of gold extraction with limited capital expenditure. Eliminating the use of mercury means a re-constitution of ASGM as a formal industry with higher levels of capital investment, new actors and a shift to a more representational approach to knowing materials. The use of toxic mercury and an increase in the enforcement of mining legislation are framing miners as illegal. Formal, responsible mining is becoming a dominant reality, and informal miners who resent being labelled illegal are working to transition to this reality. Minersâ experiences of this transition vary greatly, and this variation can be explored through the lens of ecological habitus. Many miners are using mercury elimination to perform good citizenship by mining responsibly, introducing a performative aspect to formalisation. Nevertheless, miners still face significant challenges to formalisation. As a result, many miners have had to become subcontractors for large-scale mining companies, entering exploitative relationships with which mercury, through its absence, is complicit. Taking this approach towards understanding the relationship between miners and mercury has helped to resolve the conflict between material and social deterministic views of the practice of mercury use, and linked mercury to a wider political context, which is a necessary consideration for a collaborative approach with miners to eliminate mercury.
Keywords:
Artisanal and small-scale gold mining; ASGM; mercury; Colombia; anthropology; posthumanism; entanglements; politics of materiality; performativity; informality
Neoliberal governance, sustainable development and local communities in the Barents Region
There are currently high hopes in the Barents Region for economic growth, higher
employment and improved well-being, encouraged by developments in the energy industry,
tourism and mining. The article discusses these prospects from the perspective
of local communities in five locations in the region, which spans the northernmost
counties of Finland, Norway, Sweden and Northwest Russia. The communities studied
are remote, relatively small, multicultural, and dependent on natural resources. The
salient dynamic illuminated in the research is how ideas of sustainability and neoliberal
governance meet in community development. While the two governmentalities often
conflict, they sometimes also complement one another, posing a paradox that raises
concerns over the social aspect of sustainable development in particular. The article
is based on international, multidisciplinary research drawing on interviews as well as statistical and documentary analysis
Basic tasks of sentiment analysis
Subjectivity detection is the task of identifying objective and subjective
sentences. Objective sentences are those which do not exhibit any sentiment.
So, it is desired for a sentiment analysis engine to find and separate the
objective sentences for further analysis, e.g., polarity detection. In
subjective sentences, opinions can often be expressed on one or multiple
topics. Aspect extraction is a subtask of sentiment analysis that consists in
identifying opinion targets in opinionated text, i.e., in detecting the
specific aspects of a product or service the opinion holder is either praising
or complaining about
PETRA: Process Evolution using a TRAce-based system on a maintenance platform
To meet increasing needs in the field of maintenance, we studied the dynamic aspect of process and services on a maintenance platform, a major challenge in process mining and knowledge engineering. Hence, we propose a dynamic experience feedback approach to exploit maintenance process behaviors in real execution of the maintenance platform. An active learning process exploiting event log is introduced by taking into account the dynamic aspect of knowledge using trace engineering. Our proposal makes explicit the underlying knowledge of platform users by means of a trace-based system called âPETRAâ. The goal of this system is to extract new knowledge rules about transitions and activities in maintenance processes from previous platform executions as well as its user (i.e. maintenance operators) interactions. While following a Knowledge Traces Discovery process and handling the maintenance ontology IMAMO, âPETRAâ is composed of three main subsystems: tracking, learning and knowledge capitalization. The capitalized rules are shared in the platform knowledge base in order to be reused in future process executions. The feasibility of this method is proven through concrete use cases involving four maintenance processes and their simulation
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