BUSINESS PROCESS MODEL ANTI-PATTERNS: A BIBLIOGRAPHY AND TAXONOMY OF PUBLISHED WORK

Patterns have been proven to be useful for documenting reusable solutions to common problems. A recently published bibliography of business process model patterns shed light into the various types of patterns by providing a systematic categorization of these patterns. In this way, such classification improves the understanding of business process model patterns. Anti-patterns document a counterproductive solution to a commonly occurring problem. While a classification for the large body of literature on business process model patterns is available, a structured bibliography of anti-patterns is missing. Related work on anti-patterns discusses patterns for common modeling errors, problems in business process models as well as in the business processes. Modeling experts should be aware of all these types of anti-patterns. To fill this gap, this paper presents a bibliography of business process model anti-patterns and a taxonomy of anti-patterns that has been developed using an established approach for taxonomy development. Both are based on an literature review and are valuable for people during the design and analysis phases of business processes since knowledge about anti-patterns in business process models helps for increasing their quality. Our overview should also be useful for developers of modeling tools who wish to make the modeler aware of potential modeling problems

An overview of process model quality literature - The Comprehensive Process Model Quality Framework

The rising interest in the construction and the quality of (business) process models resulted in an abundancy of emerged research studies and different findings about process model quality. The lack of overview and the lack of consensus hinder the development of the research field. The research objective is to collect, analyse, structure, and integrate the existing knowledge in a comprehensive framework that strives to find a balance between completeness and relevance without hindering the overview. The Systematic Literature Review methodology was applied to collect the relevant studies. Because several studies exist that each partially addresses this research objective, the review was performed at a tertiary level. Based on a critical analysis of the collected papers, a comprehensive, but structured overview of the state of the art in the field was composed. The existing academic knowledge about process model quality was carefully integrated and structured into the Comprehensive Process Model Quality Framework (CPMQF). The framework summarizes 39 quality dimensions, 21 quality metrics, 28 quality (sub)drivers, 44 (sub)driver metrics, 64 realization initiatives and 15 concrete process model purposes related to 4 types of organizational benefits, as well as the relations between all of these. This overview is thus considered to form a valuable instrument for both researchers and practitioners that are concerned about process model quality. The framework is the first to address the concept of process model quality in such a comprehensive way

Методы повышения качества классификации символов при обработке текстовых изображений

Methods are in-process examined classifications, applied at the compression of file with the bi-tonal image of photo-typograph got scan-out or digital photographing. The special attention applies on the in-use here measures of distinction of two images of characters, abstracted from the image of text. These measures of distinction allow with one or another degree of confidence to count characters on the compared images or consilient, or different. For the algorithms of classification known to date, including the known algorithm of JB2 well, quantitative descriptions of classification – number of classes, got these algorithms for the image of standard page of text are resulted. What less than it is a number, quality of classification is considered that higher, because gives the best compression of file with the image of text. The methods of acceleration of algorithms, classifying the images of characters, and increases of easy-to-readness of the text recovered after the compression of image are considered also.У роботі розглядаються методи класифікації, що застосовуються при стисненні файлу з бітональний зображенням тексту, отриманим скануванням або цифровим фотографуванням. Особлива увага звертається на використовувані при цьому заходи відмінності двох зображень символів, виділених з зображення тексту. Ці заходи відмінності дозволяють з тим або іншим ступенем впевненості вважати символи на порівнюваних зображеннях або збігаються, або різними. Для відомих на сьогоднішній день алгоритмів класифікації, включаючи добре відомий алгоритм JB2, наведені кількісні характеристики класифікації – число класів, одержуваних цими алгоритмами для зображення стандартної сторінки тексту. Чим менше це число, тим якість класифікації вважається вище, так як дає краще стиснення файлу із зображенням тексту. Розглянуто також методи прискорення алгоритмів, що класифікують зображення символів, і підвищення зручності читання відновленого після стиснення зображення тексту.В работе рассматриваются методы классификации, применяемые при сжатии файла с битональным изображением текста, полученным сканированием или цифровым фотографированием. Особое внимание обращается на используемые при этом меры различия двух изображений символов, выделенных из изображения текста. Эти меры различия позволяют с той или иной степенью уверенности считать символы на сравниваемых изображениях или совпадающими, или различными. Для известных на сегодняшний день алгоритмов классификации, включая хорошо известный алгоритм JB2, приведены количественные характеристики классификации – число классов, получаемых этими алгоритмами для изображения стандартной страницы текста. Чем меньше это число, тем качество классификации считается выше, так как дает лучшее сжатие файла с изображением текста. Рассмотрены также методы ускорения алгоритмов, классифицирующих изображения символов, и повышения удобочитаемости восстановленного после сжатия изображения текста

Методы повышения качества классификации символов при обработке текстовых изображений

Methods are in-process examined classifications, applied at the compression of file with the bi-tonal image of photo-typograph got scan-out or digital photographing. The special attention applies on the in-use here measures of distinction of two images of characters, abstracted from the image of text. These measures of distinction allow with one or another degree of confidence to count characters on the compared images or consilient, or different. For the algorithms of classification known to date, including the known algorithm of JB2 well, quantitative descriptions of classification – number of classes, got these algorithms for the image of standard page of text are resulted. What less than it is a number, quality of classification is considered that higher, because gives the best compression of file with the image of text. The methods of acceleration of algorithms, classifying the images of characters, and increases of easy-to-readness of the text recovered after the compression of image are considered also.У роботі розглядаються методи класифікації, що застосовуються при стисненні файлу з бітональний зображенням тексту, отриманим скануванням або цифровим фотографуванням. Особлива увага звертається на використовувані при цьому заходи відмінності двох зображень символів, виділених з зображення тексту. Ці заходи відмінності дозволяють з тим або іншим ступенем впевненості вважати символи на порівнюваних зображеннях або збігаються, або різними. Для відомих на сьогоднішній день алгоритмів класифікації, включаючи добре відомий алгоритм JB2, наведені кількісні характеристики класифікації – число класів, одержуваних цими алгоритмами для зображення стандартної сторінки тексту. Чим менше це число, тим якість класифікації вважається вище, так як дає краще стиснення файлу із зображенням тексту. Розглянуто також методи прискорення алгоритмів, що класифікують зображення символів, і підвищення зручності читання відновленого після стиснення зображення тексту.В работе рассматриваются методы классификации, применяемые при сжатии файла с битональным изображением текста, полученным сканированием или цифровым фотографированием. Особое внимание обращается на используемые при этом меры различия двух изображений символов, выделенных из изображения текста. Эти меры различия позволяют с той или иной степенью уверенности считать символы на сравниваемых изображениях или совпадающими, или различными. Для известных на сегодняшний день алгоритмов классификации, включая хорошо известный алгоритм JB2, приведены количественные характеристики классификации – число классов, получаемых этими алгоритмами для изображения стандартной страницы текста. Чем меньше это число, тем качество классификации считается выше, так как дает лучшее сжатие файла с изображением текста. Рассмотрены также методы ускорения алгоритмов, классифицирующих изображения символов, и повышения удобочитаемости восстановленного после сжатия изображения текста

Análise das métricas de complexidade para mapeamento de processos

Trabalho de conclusão de curso (graduação)— Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia de Produção, 2016.Os projetos de mapeamento de processos são fundamentais para que os modelos dos processos de negócio das organizações possuam clareza e sejam compreendidos por seus stakeholders. Entretanto, existe uma grande dificuldade de se estimar os recursos necessários para os projetos de mapeamento de processos e este fator influencia diretamente no tempo e no custo dos projetos. Deste modo, este trabalho busca, através das métricas de complexidade em processos de negócio, oferecer medições que subsidiem a tomada de decisão em projetos de mapeamentos de processos. Para isso, foram identificadas 13 propostas de medição de complexidade em processos de negócio encontradas na literatura, das quais foram selecionadas as métricas Control-Flow Complexity (CFC) e Grau de Sequenciamento (Ξ), por satisfazerem o maior número de propriedades de Weyuker e por serem de fácil aplicabilidade em modelos mapeados com a notação BPMN. Posteriormente, foi realizada uma análise exploratória de dados de processos de uma grande organização pública, que resultou na definição de níveis de complexidade para modelos de processos baseada na estimativa do esforço empreendido em seu mapeamento, possibilitando assim, a classificação de complexidade dos modelos de processos da amostra estudada. A análise da matriz de correlação revelou uma relação de complementaridade entre as avaliações realizadas pelas métricas CFC e Grau de Sequenciamento, confirmando a vocação que estas medições possuem para compor um indicador de complexidade robusto, alicerçado em diferentes perspectivas. Assim foi verificado neste estudo que as métricas selecionadas (CFC e Grau de Sequenciamento), bem como os níveis de complexidade definidos, possuem grande capacidade para subsidiar a estimativa de recursos utilizados em projetos de mapeamento de processos, pois possuem fácil aplicabilidade e fornecem informações sob uma perspectiva interna dos processos mapeados. Isto tornará a tomada de decisão no âmbito destes projetos mais condizente com os processos de negócio de interesse dos stakeholders.Business process mapping projects are essential for organizations' business process models to be understandable by their stakeholders. However, estimating resources needed for business mapping projects can be a very difficult task and this impacts directly on time and costs of the project. Thus, this paper seeks to offer measurements that subsidize decision making in business process mapping projects, through the metrics of complexity in business processes. In order to do so, we have identified 13 proposals for measuring complexity in business processes found in the literature, from which Control-Flow Complexity (CFC) and Sequentiality (Ξ) metrics were selected. These two metrics satisfied the greatest number of Weyuker properties and are easily applicable in models mapped with BPMN. Subsequently, an exploratory analysis of process data from a large public organization was carried out, which resulted in the definition of complexity levels for process models based on the estimation of the effort undertaken in their mapping, thus enabling the classification of complexity of process models of the sample studied. The analysis of a correlation matrix revealed a complementarity relationship between the evaluations performed by CFC and Sequentiality metrics, confirming the propensity that these measurements have to compose a solid indicator for business process complexity. Thus, it was verified in this study that the selected metrics (CFC and Sequentiality), as well as the complexity levels defined, have great capacity to subsidize the estimation of resources used in process mapping projects, since they are easy to apply and provide information under an structural perspective of the process models. This will turn project decision making more consistent with business processes

Advances in business ICT

Futurists and scientists alike profess the coming of a new era in the history – the knowledge era. The notion of knowledge is as old as humans’ self-consciousness, but new challenges appear. The meaning of the word “knowledge” is changing from cognitive notion to a technical term denoting a structured economic resource to be actively managed. This contributed volume is a result of vivid and extremely valuable discussions held at 3rd International Workshop on Advances in Business ICT (ABICT) in Wrocław, Poland, September 9-12, 2012. The workshop focused on Advances in Business ICT approached from a multidisciplinary perspective. It provided an international forum for scientists/experts from academia and industry to discuss and exchange current results, applications, new ideas of ongoing research and experience on all aspects of Business Intelligence. ABICT has also been an opportunity to demonstrate different ideas and tools for developing and supporting organizational creativity, as well as advances in decision support systems. This book is of interest to researchers, widely understood business, public sector and IT professionals

Advances in Business ICT

VII, 133 p. 46 illus.online resource

Advances in ICT for business, industry and public sector

This contributed volume is a result of discussions held at ABICT’13(4th International Workshop on Advances in Business ICT) in Krakow, September 8-11, 2013. The book focuses on Advances in Business ICT approached from a multidisciplinary perspective and demonstrates different ideas and tools for developing and supporting organizational creativity, as well as advances in decision support systems.This book is an interesting resource for researchers, analysts and IT professionals including software designers. The book comprises eleven chapters presenting research results on business analytics in organization, business processes modeling, problems with processing big data, nonlinear time structures and nonlinear time ontology application, simulation profiling, signal processing (including change detection problems), text processing and risk analysis.  

Advances in business ICT: new ideas from ongoing research

This book discusses the effective use of modern ICT solutions for business needs, including the efficient use of IT resources, decision support systems, business intelligence, data mining and advanced data processing algorithms, as well as the processing of large datasets (inter alia social networking such as Twitter and Facebook, etc.). The ability to generate, record and process qualitative and quantitative data, including in the area of big data, the Internet of Things (IoT) and cloud computing offers a real prospect of significant improvements for business, as well as the operation of a company within Industry 4.0. The book presents new ideas, approaches, solutions and algorithms in the area of knowledge representation, management and processing, quantitative and qualitative data processing (including sentiment analysis), problems of simulation performance, and the use of advanced signal processing to increase the speed of computation. The solutions presented are also aimed at the effective use of business process modeling and notation (BPMN), business process semantization and investment project portfolio selection. It is a valuable resource for researchers, data analysts, entrepreneurs and IT professionals alike, and the research findings presented make it possible to reduce costs, increase the accuracy of investment, optimize resources and streamline operations and marketing