Collaborative method to maintain business process models updated

Business process models are often forgotten after their creation and its representation is not usually updated. This appears to be negative as processes evolve over time. This paper discusses the issue of business process models maintenance through the definition of a collaborative method that creates interaction contexts enabling business actors to discuss about business processes, sharing business knowledge. The collaboration method extends the discussion about existing process representations to all stakeholders promoting their update. This collaborative method contributes to improve business process models, allowing updates based in change proposals and discussions, using a groupware tool that was developed. Four case studies were developed in real organizational environment. We came to the conclusion that the defined method and the developed tool can help organizations to maintain a business process model updated based on the inputs and consequent discussions taken by the organizational actors who participate in the processes.info:eu-repo/semantics/publishedVersio

Atualização Colaborativa do Modelo de Processos de Negócio

O modelo de processos de negócio as-is pode ajudar a melhorar a consciência organizacional através da partilha de conhecimento dos atores organizacionais. No entanto, a dificuldade de atualização do modelo e o seu padrão típico de utilização têm evitado a sua transformação num repositório do conhecimento organizacional que suporte as atividades diárias das organizações. Para ultrapassar este problema definiu-se um método colaborativo para atualizar o modelo de processos de negócio, utilizando o mecanismo de anotação para criar contextos de interação que promovam a explicitação e comunicação do conhecimento e a discussão dos processos. Desenvolveu-se uma ferramenta de suporte ao método colaborativo de atualização que foi utilizada em casos de estudo. A abordagem proposta permitiu demonstrar que os atores organizacionais, desde que providos dum método adequado e uma ferramenta de suporte, podem atualizar ativamente o modelo de processos de negócio, comparando as atividades modeladas com as atividades que são efetivamente executadas

Extracting Dielectric Properties for MRI-based Phantoms for Axillary Microwave Imaging Device

Microwave Imaging (MWI) is an emerging medical imaging technique, which has been studied to aid breast cancer diagnosis in the frequency range from 0.5 to 30 GHz. The information about the dielectric properties of each tissue is essential to assess the viability of this type of systems. However, accurate measurements of heterogeneous tissues can be very challenging, and the current available information is still very limited. In this paper, we present a methodology for extracting dielectric properties to create anatomical models of the axillary region. These models will be used in a MWI device to aid breast cancer diagnosis through the detection of metastasised axillary lymph nodes. We apply segmentation tools to Magnetic Resonance Images (MRI) of the breast and assign dielectric properties to each tissue, extracting preliminary information about the properties of axillary lymph nodes. This study may open a way to more quickly extract dielectric properties of tissues and/or validate measurements, accelerating the development of microwave-based medical devices.The authors would like to acknowledge the study with ref. CES/44/2019/ME in Hospital da Luz Lisboa (19/09/2019).info:eu-repo/semantics/publishedVersio

Development of MRI‐based axillary numerical models and estimation of axillary lymph node dielectric properties for microwave imaging

Purpose: Microwave imaging (MWI) has been studied as a complementary imaging modality to improve sensitivity and specificity of diagnosis of axillary lymph nodes (ALNs), which can be metastasized by breast cancer. The feasibility of such a system is based on the dielectric contrast between healthy and metastasized ALNs. However, reliable information such as anatomically realistic numerical models and matching dielectric properties of the axillary region and ALNs, which are crucial to develop MWI systems, are still limited in the literature. The purpose of this work is to develop a methodology to infer dielectric properties of structures from magnetic resonance imaging (MRI), in particular, ALNs. We further use this methodology, which is tailored for structures farther away from MR coils, to create MRI- based numerical models of the axillary region and share them with the scientific community, through an open- access repository. Methods: We use a dataset of breast MRI scans of 40 patients, 15 of them with metastasized ALNs. We apply image processing techniques to minimize the artifacts in MR images and segment the tissues of interest. The background, lung cavity, and skin are segmented using thresholding techniques and the remaining tissues are segmented using a K- means clustering algorithm. The ALNs are segmented combining the clustering results of two MRI sequences. The performance of this methodology was evaluated using qualitative criteria. We then apply a piecewise linear interpolation between voxel signal intensities and known dielectric properties, which allow us to create dielectric property maps within an MRI and consequently infer ALN properties. Finally, we compare healthy and metastasized ALN dielectric properties within and between patients, and we create an open- access repository of numerical axillary region numerical models which can be used for electromagnetic simulations. Results: The proposed methodology allowed creating anatomically realistic models of the axillary region, segmenting 80 ALNs and analyzing the corresponding dielectric properties. The estimated relative permittivity of those ALNs ranged from 16.6 to 49.3 at 5 GHz. We observe there is a high variability of dielectric properties of ALNs, which can be mainly related to the ALN size and, consequently, its composition. We verified an average dielectric contrast of 29% between healthy and metastasized ALNs. Our repository comprises 10 numerical models of the axillary region, from five patients, with variable number of metastasized ALNs and body mass index. Conclusions: The observed contrast between healthy and metastasized ALNs is a good indicator for the feasibility of a MWI system aiming to diagnose ALNs. This paper presents new contributions regarding anatomical modeling and dielectric properties' characterization, in particular for axillary region applications.info:eu-repo/semantics/publishedVersio

Development of 3D MRI-Based Anatomically Realistic Models of Breast Tissues and Tumours for Microwave Imaging Diagnosis

Breast cancer diagnosis using radar-based medical MicroWave Imaging (MWI) has been studied in recent years. Realistic numerical and physical models of the breast are needed for simulation and experimental testing of MWI prototypes. We aim to provide the scientific community with an online repository of multiple accurate realistic breast tissue models derived from Magnetic Resonance Imaging (MRI), including benign and malignant tumours. Such models are suitable for 3D printing, leveraging experimental MWI testing. We propose a pre-processing pipeline, which includes image registration, bias field correction, data normalisation, background subtraction, and median filtering. We segmented the fat tissue with the region growing algorithm in fat-weighted Dixon images. Skin, fibroglandular tissue, and the chest wall boundary were segmented from water-weighted Dixon images. Then, we applied a 3D region growing and Hoshen-Kopelman algorithms for tumour segmentation. The developed semi-automatic segmentation procedure is suitable to segment tissues with a varying level of heterogeneity regarding voxel intensity. Two accurate breast models with benign and malignant tumours, with dielectric properties at 3, 6, and 9 GHz frequencies have been made available to the research community. These are suitable for microwave diagnosis, i.e., imaging and classification, and can be easily adapted to other imaging modalities.info:eu-repo/semantics/publishedVersio

Atualização Colaborativa do Modelo de Processos de Negócio

O modelo de processos de negócio as-is pode ajudar a melhorar a consciência organizacional através da partilha de conhecimento dos atores organizacionais. No entanto, a dificuldade de atualização do modelo e o seu padrão típico de utilização têm evitado a sua transformação num repositório do conhecimento organizacional que suporte as atividades diárias das organizações. Para ultrapassar este problema definiu-se um método colaborativo para atualizar o modelo de processos de negócio, utilizando o mecanismo de anotação para criar contextos de interação que promovam a explicitação e comunicação do conhecimento e a discussão dos processos. Desenvolveu-se uma ferramenta de suporte ao método colaborativo de atualização que foi utilizada em casos de estudo. A abordagem proposta permitiu demonstrar que os atores organizacionais, desde que providos dum método adequado e uma ferramenta de suporte, podem atualizar ativamente o modelo de processos de negócio, comparando as atividades modeladas com as atividades que são efetivamente executadas

As Is Organizational Modeling

In nowadays business competitive world, the organizations need to have some integrated and accurate representation of its business processes and information systems to allow fast responses to activities like business process reengineering, information systems requirements capture and quality systems implementation, etc. The frequency and importance of this kind of activities is rising up. Unfortunately, the maintenance of this representation is not a trivial question and the business model tends to be constructed to be used and then "sit on the shelf". In this paper, first is shown why frequently the As-Is model "sit on the shelf". Then, is shown who the "clients" of the As-Is model are, and how these organizational actors can contribute to maintain the As-Is model updated. In the end preliminary characteristics of a model are identified in order to became it self-sustainable. A meta-model of the As-Is model and a prototype tool are also presented

An approach using a low-code platform for retraining professionals to ICT

Information and Communications Technology is a growing area with a growing demand for employees. However, there is a shortage of professionals in this area and integrated strategies are required to foster the access of more people to these areas and provide training to develop the necessary skills. In this paper we present a short course that was designed to retrain unemployed people, mainly with already a higher education level in the area of the science technology engineering and math (STEM), to be Information and communications technology (ICT) professionals. After this training, trainees will have the opportunity to significantly increase the likelihood of being able to obtain employment in ICT areas. The course described involves public entities (including a higher education institution) and a private company, which is also a demonstration of synergies between academia and business. In the paper, the context that led to the appearance of the course, the fundamentals that supported the syllabus design, the partners involved, the objectives of the several subjects, the profile of the trainees and the results already achieved are described. To explain the fundamentals of the course syllabus we explain the most original features of the course regarding the usefulness of taking advantage of the abstraction allowed by the new low-code platforms, what seem to be appropriate and facilitator for retraining professionals from STEM to ICT. This approach, using a low code platform for retraining professionals to ICT, presents in our point of view, advantages over other approaches. In short, in the paper we intend to share the work done during the design and follow-up of the course, as well as the preliminary results obtained in the meantime.info:eu-repo/semantics/publishedVersio

Collaborative business process discovery: method and case study

Information flows across the organization are complex and procedures employed to understand, share and control organizational knowledge and experiences should be properly supported by collaborative environments. Nevertheless, few collaborative methodologies had been proposed to describe and evolve business processes. Existing tools don’t provide the right methods for business processes discovery, modeling, monitoring and improvement. In the future, business processes models should be the result of cross-team and cross-departmental collaboration, with involved business people sharing their personal knowledge and formalizing it. This paper focuses on case study applying a collaborative process discovery method. Business Alignment Methodology (BAM) is a methodology that provides guidance about how organizational practices and knowledge are gathered to contribute for business process improvement against current BPM approaches