An intelligent approach to data extraction and task identification for process mining

2015 ◽  
Vol 17 (6) ◽  
pp. 1195-1208 ◽  
Author(s):  
Jiexun Li ◽  
Harry Jiannan Wang ◽  
Xue Bai
2020 ◽  
Vol 2 (6) ◽  
pp. 2070061
Author(s):  
Josie Hughes ◽  
Andrew Spielberg ◽  
Mark Chounlakone ◽  
Gloria Chang ◽  
Wojciech Matusik ◽  
...  

2014 ◽  
Vol 952 ◽  
pp. 351-354
Author(s):  
Hong Yu Zhai ◽  
Li Li ◽  
Hong Hua Xu

data stream management system is used to manage and query coming large, continuous, fast and flexible data stream. The system is based on the flow of data extraction, transformation, combination, which is the main content and task query execution. This paper mainly discusses the design and implementation of query execution module and query execution is composed of two parts which include query operations, query execution and scheduling.


Author(s):  
Elena Christina Schreibauer ◽  
Melina Hippler ◽  
Stephanie Burgess ◽  
Monika A. Rieger ◽  
Esther Rind

Background: Work-related psychosocial stress can cause mental and physical illnesses resulting in high costs for the individual, the economy and society. Small and medium-sized enterprises (SMEs) employ the majority of the world’s workforce and often have fewer financial and human resources compared to larger businesses. The aim of this review is to summarize current knowledge on work-related stress in SMEs according to well-established guidelines categorizing psychosocial factors at work. Methods: A systematic database search was carried out in PubMed, PsycINFO, PSYNDEX and Business Source Premiere from March to June 2019, updated in January 2020. Data of included studies were analyzed and mapped into five themes: “work content and task”, “organization of work”, “social relations”, “working environment” and “new forms of work”. Results: After full-text screening, 45 out of 116 studies were included for data extraction. Studies were very heterogeneous and of varying quality, mostly applying a cross-sectional study design. Psychosocial factors in SMEs have been researched with a focus on the work patterns “work organization” and “work content and task”. Conclusions: This review underlines the need for more and better quality research of psychosocial factors in SMEs, particularly in relation to ongoing and new challenges in the workplace, including stressors related to the process of digitalization or the development of safe working conditions during the emerge of new infectious diseases.


Author(s):  
James Alexander Hughes ◽  
Joseph Alexander Brown ◽  
Adil Mehmood Khan ◽  
Asad Masood Khattak ◽  
Mark Daley
Keyword(s):  
And Task ◽  

2020 ◽  
Vol 11 ◽  
Author(s):  
Susanne Schmidt ◽  
Olga Zlatkin-Troitschanskaia ◽  
Jochen Roeper ◽  
Verena Klose ◽  
Maruschka Weber ◽  
...  

To successfully learn using open Internet resources, students must be able to critically search, evaluate and select online information, and verify sources. Defined as critical online reasoning (COR), this construct is operationalized on two levels in our study: (1) the student level using the newly developed Critical Online Reasoning Assessment (CORA), and (2) the online information processing level using event log data, including gaze durations and fixations. The written responses of 32 students for one CORA task were scored by three independent raters. The resulting score was operationalized as “task performance,” whereas the gaze fixations and durations were defined as indicators of “process performance.” Following a person-oriented approach, we conducted a process mining (PM) analysis, as well as a latent class analysis (LCA) to test whether—following the dual-process theory—the undergraduates could be distinguished into two groups based on both their process and task performance. Using PM, the process performance of all 32 students was visualized and compared, indicating two distinct response process patterns. One group of students (11), defined as “strategic information processers,” processed online information more comprehensively, as well as more efficiently, which was also reflected in their higher task scores. In contrast, the distributions of the process performance variables for the other group (21), defined as “avoidance information processers,” indicated a poorer process performance, which was also reflected in their lower task scores. In the LCA, where two student groups were empirically distinguished by combining the process performance indicators and the task score as a joint discriminant criterion, we confirmed these two COR profiles, which were reflected in high vs. low process and task performances. The estimated parameters indicated that high-performing students were significantly more efficient at conducting strategic information processing, as reflected in their higher process performance. These findings are so far based on quantitative analyses using event log data. To enable a more differentiated analysis of students’ visual attention dynamics, more in-depth qualitative research of the identified student profiles in terms of COR will be required.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jianfei Pang ◽  
Haifeng Xu ◽  
Jun Ren ◽  
Jun Yang ◽  
Mei Li ◽  
...  

Abstract Background Acute care for critical illness requires very strict treatment timeliness. However, healthcare providers usually cannot accurately figure out the causes of low efficiency in acute care process due to the lack of effective tools. Besides, it is difficult to compare or conformance processes from different patient groups. Methods To solve these problems, we proposed a novel process mining framework with time perspective, which integrates four steps: standard activity construction, data extraction and filtering, iterative model discovery, and performance analysis. Results It can visualize the execution of actual clinical activities hierarchically, evaluate the timeliness and identify bottlenecks in the treatment process. We take the acute ischemic stroke as a case study, and retrospectively reviewed 420 patients’ data from a large hospital. Then we discovered process models with timelines, and identified the main reasons for in-hospital delay. Conclusions Experiment results demonstrate that the framework proposed could be a new way of drawing insights about hospitals’ clinical process, to help clinical institutions increase work efficiency and improve medical service.


Author(s):  
Robert Andrews ◽  
Moe Wynn ◽  
Kirsten Vallmuur ◽  
Arthur ter Hofstede ◽  
Emma Bosley ◽  
...  

While noting the importance of data quality, existing process mining methodologies (i) do not provide details on how to assess the quality of event data (ii) do not consider how the identification of data quality issues can be exploited in the planning, data extraction and log building phases of any process mining analysis, (iii) do not highlight potential impacts of poor quality data on different types of process analyses. As our key contribution, we develop a process-centric, data quality-driven approach to preparing for a process mining analysis which can be applied to any existing process mining methodology. Our approach, adapted from elements of the well known CRISP-DM data mining methodology, includes conceptual data modeling, quality assessment at both attribute and event level, and trial discovery and conformance to develop understanding of system processes and data properties to inform data extraction. We illustrate our approach in a case study involving the Queensland Ambulance Service (QAS) and Retrieval Services Queensland (RSQ). We describe the detailed preparation for a process mining analysis of retrieval and transport processes (ground and aero-medical) for road-trauma patients in Queensland. Sample datasets obtained from QAS and RSQ are utilised to show how quality metrics, data models and exploratory process mining analyses can be used to (i) identify data quality issues, (ii) anticipate and explain certain observable features in process mining analyses, (iii) distinguish between systemic and occasional quality issues, and (iv) reason about the mechanisms by which identified quality issues may have arisen in the event log. We contend that this knowledge can be used to guide the data extraction and pre-processing stages of a process mining case study to properly align the data with the case study research questions.


2020 ◽  
Vol 2 (6) ◽  
pp. 2000002 ◽  
Author(s):  
Josie Hughes ◽  
Andrew Spielberg ◽  
Mark Chounlakone ◽  
Gloria Chang ◽  
Wojciech Matusik ◽  
...  

Author(s):  
W.J. de Ruijter ◽  
M.R. McCartney ◽  
David J. Smith ◽  
J.K. Weiss

Further advances in resolution enhancement of transmission electron microscopes can be expected from digital processing of image data recorded with slow-scan CCD cameras. Image recording with these new cameras is essential because of their high sensitivity, extreme linearity and negligible geometric distortion. Furthermore, digital image acquisition allows for on-line processing which yields virtually immediate reconstruction results. At present, the most promising techniques for exit-surface wave reconstruction are electron holography and the recently proposed focal variation method. The latter method is based on image processing applied to a series of images recorded at equally spaced defocus.Exit-surface wave reconstruction using the focal variation method as proposed by Van Dyck and Op de Beeck proceeds in two stages. First, the complex image wave is retrieved by data extraction from a parabola situated in three-dimensional Fourier space. Then the objective lens spherical aberration, astigmatism and defocus are corrected by simply dividing the image wave by the wave aberration function calculated with the appropriate objective lens aberration coefficients which yields the exit-surface wave.


Author(s):  
Margreet Vogelzang ◽  
Christiane M. Thiel ◽  
Stephanie Rosemann ◽  
Jochem W. Rieger ◽  
Esther Ruigendijk

Purpose Adults with mild-to-moderate age-related hearing loss typically exhibit issues with speech understanding, but their processing of syntactically complex sentences is not well understood. We test the hypothesis that listeners with hearing loss' difficulties with comprehension and processing of syntactically complex sentences are due to the processing of degraded input interfering with the successful processing of complex sentences. Method We performed a neuroimaging study with a sentence comprehension task, varying sentence complexity (through subject–object order and verb–arguments order) and cognitive demands (presence or absence of a secondary task) within subjects. Groups of older subjects with hearing loss ( n = 20) and age-matched normal-hearing controls ( n = 20) were tested. Results The comprehension data show effects of syntactic complexity and hearing ability, with normal-hearing controls outperforming listeners with hearing loss, seemingly more so on syntactically complex sentences. The secondary task did not influence off-line comprehension. The imaging data show effects of group, sentence complexity, and task, with listeners with hearing loss showing decreased activation in typical speech processing areas, such as the inferior frontal gyrus and superior temporal gyrus. No interactions between group, sentence complexity, and task were found in the neuroimaging data. Conclusions The results suggest that listeners with hearing loss process speech differently from their normal-hearing peers, possibly due to the increased demands of processing degraded auditory input. Increased cognitive demands by means of a secondary visual shape processing task influence neural sentence processing, but no evidence was found that it does so in a different way for listeners with hearing loss and normal-hearing listeners.


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