33 research outputs found
An Elaborate Preprocessing Phase (p3) in Composition and Optimization of Business Process Models
No full textBusiness process optimization (BPO) has become an increasingly attractive subject in the wider area of business process intelligence and is considered as the problem of composing feasible business process designs with optimal attribute values, such as execution time and cost. Despite the fact that many approaches have produced promising results regarding the enhancement of attribute performance, little has been done to reduce the computational complexity due to the size of the problem. The proposed approach introduces an elaborate preprocessing phase as a component to an established optimization framework (bpoF) that applies evolutionary multi-objective optimization algorithms (EMOAs) to generate a series of diverse optimized business process designs based on specific process requirements. The preprocessing phase follows a systematic rule-based algorithmic procedure for reducing the library size of candidate tasks. The experimental results on synthetic data demonstrate a considerable reduction of the library size and a positive influence on the performance of EMOAs, which is expressed with the generation of an increasing number of nondominated solutions. An important feature of the proposed phase is that the preprocessing effects are explicitly measured before the EMOAs application; thus, the effects on the library reduction size are directly correlated with the improved performance of the EMOAs in terms of average time of execution and nondominated solution generation. The work presented in this paper intends to pave the way for addressing the abiding optimization challenges related to the computational complexity of the search space of the optimization problem by working on the problem specification at an earlier stage
A Trustable and Interoperable Decentralized Solution for Citizen-Centric and Cross-Border eGovernance: A Conceptual Approach
No full textPart 5: Data Analytics, Decision Making, and Artificial IntelligenceInternational audienceAiming to support a cross-sector and cross-border eGovernance paradigm for sharing common public services, this paper introduces an AI-enhanced solution that enables beneficiaries to participate in a decentralized network for effective big data exchange and service delivery that promotes the once-only priority and is by design digital, efficient, cost-effective, interoperable and secure. The solution comprises (i) a reliable and efficient decentralized mechanism for data sharing, capable of addressing the complexity of the processes and their high demand of resources; (ii) an ecosystem for delivering mobile services tailored to the needs of stakeholders; (iii) a single sign-on Wallet mechanism to manage transactions with multiple services; and (iv) an intercommunication layer, responsible for the secure exchange of information among existing eGovernment systems with newly developed ones. An indicative application scenario showcases the potential of our approach
D1.4– Data Management Plan
No full text<p>This deliverable presents the second version of the data management action plan (DMP) an provides the general outline of the project policy for data management. The EO4EU DMP identifies the data types that will be used, collected and/or generated, and frames the overall guidelines regarding data collected and generated throughout the project implementation. <br>The DMP describes the format and support the data management life cycle of all the data collected and generated following the FAIR (Findable, Accessible, Interoperable, Reusable) Data Principles, as defined in the “Guidelines to the Rules on Open Access to Scientific Publications [1] and Open Access to Research Data in Horizon 2020 [2]” and in the “Guidelines on FAIR Data Management in Horizon 2020 [3]”. This document will present the methodology and standards to be followed, in cases where data will be shared and/or made open, and how it will be curated and stored. </p>
D1.3 – Data Management Plan
No full text<p>This deliverable presents the initial data management action plan (DMP) and provides the general outline of the project policy for data management. The EO4EU DMP identifies the data types that will be used, collected and/or generated, and frames the overall guidelines regarding data collected and generated throughout the project implementation. <br>The DMP will describe the format and support the data management life cycle of all the data collected and generated following the FAIR (Findable, Accessible, Interoperable, Reusable) Data Principles, as defined in the “Guidelines to the Rules on Open Access to Scientific Publications [1] and Open Access to Research Data in Horizon 2020 [2]” and in the “Guidelines on FAIR Data Management in Horizon <br>2020 [3]”. This document will present the methodology and standards to be followed, in cases where data will be shared and/or made open, and how it will be curated and stored. </p>
Towards a Comprehensive Business Process Optimization Framework
No full textBusiness processes are a collection of related, structured activities performed to achieve a defined business outcome. Adopting a business process perspective is an essential advantage for organizations to orchestrate and achieve continuous improvements on time and within specified resource constraints. The increased popularity of this domain, however, has resulted in a variety of interdisciplinary approaches with limited tangible, quantifiable -and thus measurable benefits. Operational Research (OR) has critically evolved during the last decades, providing businesses and organizations with problem-solving techniques and methods aiming to enhanced performance and improved efficiency. The proposed project focuses on the development, evaluation and verification of a business process optimisation framework as the central objective of the PhD Thesis. The performed optimisation is intended to use Evolutionary Computing (EC) techniques, as they have been used effectively in a variety of similar problems. The author seeks advice and feedback on the optimal theoretical foundation of the framework, the utilization methods adopted (i.e. in the area of continuous and discrete computational optimization) and the method selection for performance analysis and validation. Furthermore, guidance from experts on the field will decisively influence the PhD Thesis, through directing its orientation to current research trends and future opportunities.1291342017 IEEE 19th Conference on Business Informatics (CBI
Glocal News: An Attempt to Visualize the Discovery of Localized Top Local News, Globally
No full textUnderstanding the Use of Emerging Technologies in the Public Sector: A Review of Horizon 2020 Projects
No full textThe main purpose of this article is to provide an up-to-date understanding of the utilization and deployment of emerging technologies in the public sector, as this is reflected through 19 recently funded Horizon 2020 research projects. For the needs of this study, we have adopted a well-known literature review method that enables a concept-centric analysis of the accumulated knowledge in the field under consideration, and accordingly proposed a conceptual framework that facilitates such an analysis. Through a detailed consideration of these projects and their pilot case implementations, a series of insights about recent research development and applications in the public sector are extracted and discussed. To the best of our knowledge, this is the first attempt to gain such insights from a research projects perspective, which may reveal useful information about the utilization and deployment of these technologies in real-life pilots. The findings of this study are also justified or challenged by referring to recent review articles that investigate the use of emerging technologies in the public sector.4112
Artificial Intelligence and Blockchain Technologies in the Public Sector: A Research Projects Perspective
No full text13391323335Electronic Governmen
