Mining software development process variations

Process tailoring aims to customize a software process to better suit the specific needs of an organization when executing a software project or due to a social context in which the process is inserted. Tailoring happens, in general, through variations in the process elements, such as activities, artifacts, and control flows. This paper aims to introduce a technique that uses process mining to uncover elements from the software process that are candidates for tailoring. The proposed approach analyzes the execution logs from several process instances that share a common standard process. As a result, execution traces that differ from the standard process flow are identified and assessed to uncover their variable elements. The proposed technique was evaluated with data extracted from a real software development scenario when a large system was under development for a set of Brazilian Federal Institutes of Education, Science and Technology.info:eu-repo/semantics/acceptedVersio

Using Process Mining to Assess the Fidelity of a Home Visiting Program

Background: The Maternal, Infant, and Early Childhood Home Visiting (MIECHV) program is a federal public health initiative which supports at-risk families through evidence-based programs and promising approaches for pregnant women, and childhood development for children aged 0 to 5. These public health program funding mechanisms commonly include process evaluation mandates. Purpose: The use of process mining was explored as a methodology to assess the fidelity of the MIECHV programs’ actual workflow to that of their intended models. Methods: Research Electronic Data Capture (REDCap) data files that were populated with program process data elements from the local implementing agencies were mined. The focus was on three main variables: participant identification, activity labels, and timestamps. These variables were imported into the Disco process-mining software. Disco was used to develop process maps to track process pathways and compare the actual workflow against the intended model. Results: Using process mining as a diagnostic tool, fidelity to the MIECHV process model was assessed, identifying a total of 262 different process variations. The 15 most frequent variations represent 60.7% of the total pool of process variations, 13 of which were deemed to have fidelity to the intended model. Analysis of the variations indicated that many activities in the intended process were skipped or implemented out of sequence. Implications: Process mining is a useful tool for organizations to visually display, track, understand, compare, and improve their workflow processes. This method should be considered by programs as complex as MIECHV to improve the data reporting and the identification of opportunities to strengthen programs

Assessing the freshwater quality of a large-scale mining watershed : the need for integrated approaches

Water quality assessments provide essential information for protecting aquatic habitats and stakeholders downstream of mining sites. Moreover, mining companies must comply with environmental quality standards and include public participation in water quality monitoring (WQM) practices. However, overarching challenges beyond corporate environmental responsibility are the scientific soundness, political relevance and harmonization of WQM practices. In this study, a mountainous watershed supporting large-scale gold mining in the headwaters, besides urban and agricultural landuses at lower altitudes, is assessed in the dry season. Conventional physicochemical and biological (Biological Monitoring Water Party-Colombia index) freshwater quality parameters were evaluated, including hydromorphological and land-use characteristics. According to the indicators used, water quality deterioration by mining was absent, in contrast to the effects of urban economic activities, hydromorphological alterations and (less important) agricultural pollutants. We argue that mining impacts are hardly captured due to the limited ecological knowledge of high-mountain freshwaters, including uncharacterized mining-specific bioindicators, environmental baselines and groundwater processes, as well as ecotoxicological and microbial freshwater quality components. Lessons for overcoming scientific and operational challenges are drawn from joint efforts among governments, academia and green economy competitiveness. Facing a rapid development of extractive industries, interinstitutional and multidisciplinary collaborations are urgently needed to implement more integrated freshwater quality indicators of complex mining impacts

Energy Efficiency and Economic Aspects of Mining Wastes Utilization within the Closed Cycle of Underground Gas Generator

Energy efficiency of coal gasification with possible utilization of mining wastes within ecologically closed gas generator cycle has been considered. Technical and technological performance of such gas generator and mechanism of material and heat balance on the basis of the available analytical methods and practices as well as the developed author software have been proposed. Heat carrier formed in the process of coal gasification has been used for the utilization. Temperature of the utilization process within the industrially expedient limits being supported with the help of either activation or attenuation of the gasification process. After specific treatment, organogenic waste and domestic wastes are utilized by means of thermal decomposition within a gas generator. Economic evaluation of the proposed means confirms the expediency of their implementation in mines with industrial and balanced coal reserves as well as within the areas where this energetic source has already been already mined out. Results of this investigation were partially presented on international scientific and practical conference “Forum of Miners - 2017”. They contain the researches, which were conducted within the project GP – 489, financed by Ministry of Education and Science of Ukrain

WormBase: A modern Model Organism Information Resource

WormBase (https://wormbase.org/) is a mature Model Organism Information Resource supporting researchers using the nematode Caenorhabditis elegans as a model system for studies across a broad range of basic biological processes. Toward this mission, WormBase efforts are arranged in three primary facets: curation, user interface and architecture. In this update, we describe progress in each of these three areas. In particular, we discuss the status of literature curation and recently added data, detail new features of the web interface and options for users wishing to conduct data mining workflows, and discuss our efforts to build a robust and scalable architecture by leveraging commercial cloud offerings. We conclude with a description of WormBase\u27s role as a founding member of the nascent Alliance of Genome Resources

Mining developer communication data streams

This paper explores the concepts of modelling a software development project as a process that results in the creation of a continuous stream of data. In terms of the Jazz repository used in this research, one aspect of that stream of data would be developer communication. Such data can be used to create an evolving social network characterized by a range of metrics. This paper presents the application of data stream mining techniques to identify the most useful metrics for predicting build outcomes. Results are presented from applying the Hoeffding Tree classification method used in conjunction with the Adaptive Sliding Window (ADWIN) method for detecting concept drift. The results indicate that only a small number of the available metrics considered have any significance for predicting the outcome of a build