Data granulation by the principles of uncertainty

Researches in granular modeling produced a variety of mathematical models, such as intervals, (higher-order) fuzzy sets, rough sets, and shadowed sets, which are all suitable to characterize the so-called information granules. Modeling of the input data uncertainty is recognized as a crucial aspect in information granulation. Moreover, the uncertainty is a well-studied concept in many mathematical settings, such as those of probability theory, fuzzy set theory, and possibility theory. This fact suggests that an appropriate quantification of the uncertainty expressed by the information granule model could be used to define an invariant property, to be exploited in practical situations of information granulation. In this perspective, a procedure of information granulation is effective if the uncertainty conveyed by the synthesized information granule is in a monotonically increasing relation with the uncertainty of the input data. In this paper, we present a data granulation framework that elaborates over the principles of uncertainty introduced by Klir. Being the uncertainty a mesoscopic descriptor of systems and data, it is possible to apply such principles regardless of the input data type and the specific mathematical setting adopted for the information granules. The proposed framework is conceived (i) to offer a guideline for the synthesis of information granules and (ii) to build a groundwork to compare and quantitatively judge over different data granulation procedures. To provide a suitable case study, we introduce a new data granulation technique based on the minimum sum of distances, which is designed to generate type-2 fuzzy sets. We analyze the procedure by performing different experiments on two distinct data types: feature vectors and labeled graphs. Results show that the uncertainty of the input data is suitably conveyed by the generated type-2 fuzzy set models.Comment: 16 pages, 9 figures, 52 reference

Justified granulation aided noninvasive liver fibrosis classification system

According to the World Health Organization 130-150 million (according to WHO) of people globally are chronically infected with hepatitis C virus. The virus is responsible for chronic hepatitis that ultimately may cause liver cirrhosis and death. The disease is progressive, however antiviral treatment may slow down or stop its development. Therefore, it is important to estimate the severity of liver fibrosis for diagnostic, therapeutic and prognostic purposes. Liver biopsy provides a high accuracy diagnosis, however it is painful and invasive procedure. Recently, we witness an outburst of non-invasive tests (biological and physical ones) aiming to define severity of liver fibrosis, but commonly used FibroTest®, according to an independent research, in some cases may have accuracy lower than 50 %. In this paper a data mining and classification technique is proposed to determine the stage of liver fibrosis using easily accessible laboratory data. Methods: Research was carried out on archival records of routine laboratory blood tests (morphology, coagulation, biochemistry, protein electrophoresis) and histopathology records of liver biopsy as a reference value. As a result, the granular model was proposed, that contains a series of intervals representing influence of separate blood attributes on liver fibrosis stage. The model determines final diagnosis for a patient using aggregation method and voting procedure. The proposed solution is robust to missing or corrupted data. Results: The results were obtained on data from 290 patients with hepatitis C virus collected over 6 years. The model has been validated using training and test data. The overall accuracy of the solution is equal to 67.9 %. The intermediate liver fibrosis stages are hard to distinguish, due to effectiveness of biopsy itself. Additionally, the method was verified against dataset obtained from 365 patients with liver disease of various etiologies. The model proved to be robust to new data. What is worth mentioning, the error rate in misclassification of the first stage and the last stage is below 6.5 % for all analyzed datasets. Conclusions: The proposed system supports the physician and defines the stage of liver fibrosis in chronic hepatitis C. The biggest advantage of the solution is a human-centric approach using intervals, which can be verified by a specialist, before giving the final decision. Moreover, it is robust to missing data. The system can be used as a powerful support tool for diagnosis in real treatmen

On Good AI Governance : 14 Priority Actions, a S.M.A.R.T. Model of Governance, and a Regulatory Toolbox

AI4People's second year of activities has focused on applying - concretely, in real world scenarios and through appropriate governance - those ethical principles of AI announced by AI4People in 2018. The 2019 White Paper gives shape to - whilst establishing priorities and critical issues - 14 Priority Actions, a Model of S.M.A.R.T. Governance and a Regulatory Toolbox, to which governments and businesses alike can refer to - immediately and efficiently. To conceive the aforementioned, we examine current initiatives and debates on the governance of AI, and consequently provide: - A definition of the notion of governance and the principles that are at stake in this context - 14 Priority Actions that can be undertaken immediately, existing within three new groups of priority: (i) forms of engagement; (ii) no-regrets actions; and (iii) coordination mechanisms for the governance of AI - A S.M.A.R.T. Model of Governance, for both governments and businesses, adequate for tackling the normative challenges of AI, while being Scalable, Modular, Adaptable, Reflexive, and Technologically-savvy. We call for specific forms of governance that are neither bottom-up, nor top-down, but that are inbetween, and argue that neither co-regulatory models of AI governance - nor forms of self-regulation, nor its variants, such as 'monitored self-regulation' - are adequate - A Regulatory Toolbox, illustrating how the model of S.M.A.R.T. governance works

(Neg)Entropic scenarios affecting the wicked design spaces of knowledge management systems

CITATION: Schmitt, U. 2020. (Neg)Entropic scenarios affecting the wicked design spaces of knowledge management systems. Entropy, 22(2):169, doi:10.3390/e22020169.The original publication is available at https://www.mdpi.comThe envisioned embracing of thriving knowledge societies is increasingly compromised by threatening perceptions of information overload, attention poverty, opportunity divides, and career fears. This paper traces the roots of these symptoms back to causes of information entropy and structural holes, invisible private and undiscoverable public knowledge which characterize the sad state of our current knowledge management and creation practices. As part of an ongoing design science research and prototyping project, the article’s (neg)entropic perspectives complement a succession of prior multi-disciplinary publications. Looking forward, it proposes a novel decentralized generative knowledge management approach that prioritizes the capacity development of autonomous individual knowledge workers not at the expense of traditional organizational knowledge management systems but as a viable means to foster their fruitful co-evolution. The article, thus, informs relevant stakeholders about the current unsustainable status quo inhibiting knowledge workers; it presents viable remedial options (as a prerequisite for creating the respective future generative Knowledge Management (KM) reality) to afford a sustainable solution with the generative potential to evolve into a prospective general-purpose technology.https://www.mdpi.com/1099-4300/22/2/169Publisher's versio

'Metarules, judgment and the algorithmic future of financial regulation in the UK

UK financial regulators are experimenting with the conversion of rulebook content into machine-readable and executable code. A major driver of these initiatives is the belief that the use of algorithms will eliminate the need for human interpretation as a deliberative process, and that this would be a welcome development because it will improve effectiveness while cutting time and costs for regulators and the industry alike. In this article, I set out to explain why human interpretation should be preserved and further harnessed if data-driven governance is to work at all. To support my thesis, I bring attention to the limited translatability of rulebook content into code, and to the difficulties for machines to engage with the full spectrum of tasks of analogical reasoning. I further contend that it would be desirable to preserve human interpretation on procedural grounds pertaining to the legitimacy of financial regulators. I conclude with recommendations about the future design of the financial rulebooks

Proceedings of the 2012 Workshop on Ambient Intelligence Infrastructures (WAmIi)

This is a technical report including the papers presented at the Workshop on Ambient Intelligence Infrastructures (WAmIi) that took place in conjunction with the International Joint Conference on Ambient Intelligence (AmI) in Pisa, Italy on November 13, 2012. The motivation for organizing the workshop was the wish to learn from past experience on Ambient Intelligence systems, and in particular, on the lessons learned on the system architecture of such systems. A significant number of European projects and other research have been performed, often with the goal of developing AmI technology to showcase AmI scenarios. We believe that for AmI to become further successfully accepted the system architecture is essential

Proceedings of the 2012 Workshop on Ambient Intelligence Infrastructures (WAmIi)

This is a technical report including the papers presented at the Workshop on Ambient Intelligence Infrastructures (WAmIi) that took place in conjunction with the International Joint Conference on Ambient Intelligence (AmI) in Pisa, Italy on November 13, 2012. The motivation for organizing the workshop was the wish to learn from past experience on Ambient Intelligence systems, and in particular, on the lessons learned on the system architecture of such systems. A significant number of European projects and other research have been performed, often with the goal of developing AmI technology to showcase AmI scenarios. We believe that for AmI to become further successfully accepted the system architecture is essential

Skilling up for CRM: qualifications for CRM professionals in the Fourth Industrial Revolution

The 4th industrial revolution (4IR) describes a series of innovations in artificial intelligence, ubiquitous internet connectivity, and robotics, along with the subsequent disruption to the means of production. The impact of 4IR on industry reveals a construct called Industry 4.0. Higher education, too, is called to transform to respond to the disruption of 4IR, to meet the needs of industry, and to maximize human flourishing. Education 4.0 describes 4IR’s impact or predicted impact or intended impact on higher education, including prescriptions for HE’s transformation to realize these challenges. Industry 4.0 requires a highly skilled workforce, and a 4IR world raises questions about skills portability, durability, and lifespan. Every vertical within industry will be impacted by 4IR and such impact will manifest in needs for diverse employees possessing distinct competencies. Customer relationship management (CRM) describes the use of information systems to implement a customer-centric strategy and to practice relationship marketing (RM). Salesforce, a market leading CRM vendor, proposes its products alone will generate 9 million new jobs and $1.6 trillion in new revenues for Salesforce customers by 2024. Despite the strong market for CRM skills, a recent paper in a prominent IS journal claims higher education is not preparing students for CRM careers. In order to supply the CRM domain with skilled workers, it is imperative that higher education develop curricula oriented toward the CRM professional. Assessing skills needed for specific industry roles has long been an important task in IS pedagogy, but we did not find a paper in our literature review that explored the Salesforce administrator role. In this paper, we report the background, methodology, and results of a content analysis of Salesforce Administrator job postings retrieved from popular job sites. We further report the results of semi-structured interviews with industry experts, which served to validate, revise, and extend the content analysis framework. Our resulting skills framework serves as a foundation for CRM curriculum development and our resulting analysis incorporates elements of Education 4.0 to provide a roadmap for educating students to be successful with CRM in a 4IR world

Digital Towns

This open access book explores the digital transformation of small and rural towns, in particular, how to measure the evolution and development of digital towns. In addition to access to resources, competition from urban and global markets, and population trends, rural communities present lesser access and use of digital technologies and have lower digital competencies and skills than their urban counterparts. Consequently, they experience less beneficial outcomes from increased digitalisation than urban areas. This book defines what a digital town is and explores digitalisation from the perspective of the four basic economic sectors in towns - individuals and households, businesses, the public sector, and civil society - and three types of enabling infrastructure - digital connectivity, education, and governance. Particular attention is paid to how digitalisation efforts are measured by intergovernmental and international organisations for each sector and enabling infrastructure. The book concludes with a Digital Town Readiness Framework that offers local communities, policymakers, and scholars an initial set of indicators upon which to develop digital town initiatives, and measure progress. For those ready to embrace the opportunity, this book is a pathfinder on the road to a more equitable and impactful digital society and digital economy