An Improved Image Segmentation System: A Cooperative Multi-agent Strategy for 2D/3D Medical Images

In this paper, we present a solution-based cooperation approach for strengthening the image segmentation.This paper proposes a cooperative method relying on Multi-Agent System. The main contribution of this work is to highlight the importance of cooperation between the contour and region growing based on Multi-Agent System (MAS). Consequently, agents’ interactions form the main part of the whole process for image segmentation. Similar works were proposed to evaluate the effectiveness of the proposed solution. The main difference is that our Multi-Agent System can perform the segmentation process ensuring efficiency. Our results show that the performance indices in the system were higher. Furthermore, the integration of thecooperation paradigm allows to speed up the segmentation process. Besides, the tests reveal the robustness of our method by proving competitive results. Our proposal achieved an accuracy of 93,51%± 0,8, a sensitivity of 93,53%± 5,08 and a specificity rate of 92,64%± 4,01

Intelligent Automated Negotiation for Medical Image Segmentation Failure using Multi-Agent Systems

International audienceImage segmentation errors can be fatal in the medical field. Sometimes even automated segmentation methods fail, they can be affected by poor image quality, artifacts or even unexpected noises. A practical task such as the segmentation of medical images is highly required for decision-making either for diagnosis or for the treatment of the patient. In this paper, we present a method based on negotiation strategies, of multi-agent systems, for the detection and correction of segmentation failures. The main advantages of our method are: 1) support for a fast negotiation strategy on a 2D view of each slice of the 3D image; 2) our approach is independent of the initial segmentation method; 3) The method is applicable to a variety of medical structures

A multi-model based microservices identification approach

Microservices are hailed for their capabilities to tackle the challenge of breaking monolithic business systems down into small, cohesive, and loosely-coupled services. Indeed, these systems are neither easy to maintain nor to replace undermining organizations’ efforts to cope with user’s changing needs and governments’ complex regulations. Microservices constitute an architectural style for developing a new generation of systems as a suite of services that, although they are separate, engage in collaborative execution and communication sessions. However, microservices success depends, among many other things, on the existence of an approach that would automatically identify the necessary microservices according to organizations’ requirements. In this paper, we present such an approach and demonstrate its technical doability in the context of a case study, Bicing, for renting bikes. Some salient features of this approach are business processes as input for the identification needs, three models known as control, data, and semantic to capture dependencies between these processes’ activities, and, finally, a collaborative clustering technique that recommends potential microservices. Conducted experiments in the context of Bicing clearly indicate that our approach outperforms similar ones for microservices identification and reinforce the important role of business processes in this identification. The approach constitutes a major milestone towards a better architectural style for future microservices systems

Reconnaissance d'objets en imagerie aerienne

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Towards an Automatic Identification of Microservices from Business Processes

© 2020 IEEE. Microservices have emerged as an alternative solution to many existing technologies allowing to break monolithic applications into \u27small\u27 fine-grained, highly-cohesive, and loosely-coupled units. However, identifying microservices remains a challenge that could undermine this migration success. This paper proposes an approach for microservices automatic-identification from a set of business processes (BP). The approach is multi-models combining different independent models that represent a BP\u27s control dependencies, data dependencies, semantic dependencies, respectively. the approach is also based on collaborative clustering. A case study about renting bikes is adopted to illustrate and demonstrate the approach. In term of precision, the results show how BPs as inputs permit to generate better microservices compared to other approaches discussed in the paper, as well

Automatic Microservices Identification from a set of Business Processes

International audienceAll organizations engage in ongoing maintenance of their information systems due to constant changes in users' needs and governments' regulations. However these systems are monolithic making this maintenance a nightmare. To address this monolithic nature different technologies like commercial-of-the-shelf, service-oriented architecture, and lately microservices are proposed. This paper focuses on microservices by discussing their automatic identification from a set of business processes. Thanks to business processes, control and data dependencies between their activities are extracted and then clustered together. Each cluster constitutes a candidate microservice. To illustrate and demonstrate microservice automatic identification, a case study about renting bikes in the city of Barcelona is adopted and then implemented. In term of precision, the results show how business processes as inputs permit to generate better microservices compared to other approaches discussed in the paper, as well