Management and control of self-replicating systems: A systems model

In 1980, a conceptual engineering approach to self-replicating systems was achieved. The design was based on von Newmann's kinematic version of self-replicating automata. The systems management and control and the organization of the control elements are reported. After developing the functional requirements of such a system, a hierarchy of three management and control levels is described. These are an autonomous, an external, and an intelligent management and control system. Systems recycling, systems specialization, and information replication are discussed

Digital Ecosystems: Self-Organisation of Evolving Agent Populations

A primary motivation for our research in Digital Ecosystems is the desire to exploit the self-organising properties of biological ecosystems. Ecosystems are thought to be robust, scalable architectures that can automatically solve complex, dynamic problems. Self-organisation is perhaps one of the most desirable features in the systems that we engineer, and it is important for us to be able to measure self-organising behaviour. We investigate the self-organising aspects of Digital Ecosystems, created through the application of evolutionary computing to Multi-Agent Systems (MASs), aiming to determine a macroscopic variable to characterise the self-organisation of the evolving agent populations within. We study a measure for the self-organisation called Physical Complexity; based on statistical physics, automata theory, and information theory, providing a measure of information relative to the randomness in an organism's genome, by calculating the entropy in a population. We investigate an extension to include populations of variable length, and then built upon this to construct an efficiency measure to investigate clustering within evolving agent populations. Overall an insight has been achieved into where and how self-organisation occurs in our Digital Ecosystem, and how it can be quantified.Comment: 5 pages, 5 figures, ACM Management of Emergent Digital EcoSystems (MEDES) 200

Learning roadmap studio : new approaches and strategies for efficient learning and training processes

Learning systems have emerged in a set of different information systems, oriented for different kinds of organizations and institutions, such as learning management systems, knowledge management systems and learning content management systems, which can be integrated or merged with others. From past experience, it has been denoted that strategies and pedagogical processes are tasks that can be created, enriched and boosted by actors who participate in learning and training processes: course managers, teachers and students. The challenge posed to the different actors involved also accelerates the changes that have been happening in education and training, empowering a society based on knowledge. Initiatives such as eLearning (EU Comission 2000), eLearningEurope, eTwinning and Education Observatories are an evidence of this challenge. Platforms, applications, tools and systems must respond to challenges that those actors face nowadays: heterogeneous target audiences, in terms of student profiles, number of participants, differentiated contents and schedules to achieve knowledge, outcomes and competences. Thus, a prototype application, named Learning Roadmap Studio (LRMS), has been developed and deployed at Aveiro Norte Polytechnic School of the University of Aveiro, in order to suppress gaps in learning processes and to power better learning and training. It represents a new challenge for the University of Aveiro for higher education and is already being tested. At its core is the concept of “learning roadmaps” that act upon two fundamental axes: education and learning. For the teachers, it aims at becoming a self-supporting tool that stimulates the organization and management of the course materials (lectures, presentations, multimedia content, and evaluation materials, amongst others). For the students, the learning roadmap aims at promoting self-study and supervised study, endowing the pupil with the capabilities to find the relevant information and to capture the concepts in the study materials. The outcome will be a stimulating learning process together with an organized management of those materials. It is not intended to create new learning management systems. Instead, it is presented as an application that enables the edition and creation of learning processes and strategies, giving primary relevance to teachers, instead of focusing on tools, features and contents

Personalized Decentralized Communication

Search engines, portals and topic-centered web sites are all attempts to create more or less personalized web-services. However, no single service can in general fulfill all needs of a particular user, so users have to search and maintain personal profiles at several locations. We propose an architecture where each person has his own information management environment where all personalization is made locally. Information is exchanged with other’s if it’s of mutual interest that the information is published or received. We assume that users are self-interested, but that there is some overlap in their interests. Our recent work has focused on decentralized dissemination of information, specifically what we call decentralized recommender systems. We are investigating the behavior of such systems and have also done some preliminary work on the users’ information environment

Social networks, work and network-based resources for the management of long-term conditions: a framework and study protocol for developing self-care support

Background: increasing the effective targeting and promotion of self-care support for long-term conditions requires more of a focus on patient contexts and networks. The aim of this paper is to describe how within a programme of research and implementation, social networks are viewed as being centrally involved in the mobilisation and deployment of resources in the management of a chronic condition. This forms the basis of a novel approach to understanding, designing, and implementing new forms of self-management support.Methods: drawing on evidence syntheses about social networks and capital and the role of information in self-management, we build on four conceptual approaches to inform the design of our research on the implementation of self-care support for people with long-term conditions. Our approach takes into consideration the form and content of social networks, notions of chronic illness work, normalisation process theory (NPT), and the whole systems informing self-management engagement (WISE) approach to self-care support.Discussion: the translation and implementation of a self-care agenda in contemporary health and social context needs to acknowledge and incorporate the resources and networks operating in patients' domestic and social environments and everyday lives. The latter compliments the focus on healthcare settings for developing and delivering self-care support by viewing communities and networks, as well as people suffering from long-term conditions, as a key means of support for managing long-term conditions. By focusing on patient work and social-network provision, our aim is to open up a second frontier in implementation research, to translate knowledge into better chronic illness management, and to shift the emphasis towards support that takes place outside formal health services.<br/

How will the Internet of Things enable Augmented Personalized Health?

Internet-of-Things (IoT) is profoundly redefining the way we create, consume, and share information. Health aficionados and citizens are increasingly using IoT technologies to track their sleep, food intake, activity, vital body signals, and other physiological observations. This is complemented by IoT systems that continuously collect health-related data from the environment and inside the living quarters. Together, these have created an opportunity for a new generation of healthcare solutions. However, interpreting data to understand an individual's health is challenging. It is usually necessary to look at that individual's clinical record and behavioral information, as well as social and environmental information affecting that individual. Interpreting how well a patient is doing also requires looking at his adherence to respective health objectives, application of relevant clinical knowledge and the desired outcomes. We resort to the vision of Augmented Personalized Healthcare (APH) to exploit the extensive variety of relevant data and medical knowledge using Artificial Intelligence (AI) techniques to extend and enhance human health to presents various stages of augmented health management strategies: self-monitoring, self-appraisal, self-management, intervention, and disease progress tracking and prediction. kHealth technology, a specific incarnation of APH, and its application to Asthma and other diseases are used to provide illustrations and discuss alternatives for technology-assisted health management. Several prominent efforts involving IoT and patient-generated health data (PGHD) with respect converting multimodal data into actionable information (big data to smart data) are also identified. Roles of three components in an evidence-based semantic perception approach- Contextualization, Abstraction, and Personalization are discussed

Development of an Internet-Based Chronic Disease Self-Management System

Patient self-management programs and information systems that support them can improve the quality of healthcare. Flaws in user experience reduce the willingness of patients to adopt such systems. To explore how emerging technology such as rich Internet applications can be used to address the usability issues of personal health information systems, we developed a health self-management application that is based on an open-source framework. In this work we present the architecture of the system, discuss the issues we faced and lessons we learned while developing it. This work can help researchers and practitioners in evaluating approaches towards developing new generation of personal health solutions. Furthermore, this work serves as a basis for implementing a feature-rich system that can improve chronic disease self-management

New Frontiers of Quantified Self: Finding New Ways for Engaging Users in Collecting and Using Personal Data

In spite of the fast growth in the market of devices and applications that allow people to collect personal information, Quantified Self (QS) tools still present a variety of issues when they are used in everyday lives of common people. In this workshop we aim at exploring new ways for designing QS systems, by gathering different researchers in a unique place for imagining how the tracking, management, interpretation and visualization of personal data could be addressed in the future

On a New Type of Information Processing for Efficient Management of Complex Systems

It is a challenge to manage complex systems efficiently without confronting NP-hard problems. To address the situation we suggest to use self-organization processes of prime integer relations for information processing. Self-organization processes of prime integer relations define correlation structures of a complex system and can be equivalently represented by transformations of two-dimensional geometrical patterns determining the dynamics of the system and revealing its structural complexity. Computational experiments raise the possibility of an optimality condition of complex systems presenting the structural complexity of a system as a key to its optimization. From this perspective the optimization of a system could be all about the control of the structural complexity of the system to make it consistent with the structural complexity of the problem. The experiments also indicate that the performance of a complex system may behave as a concave function of the structural complexity. Therefore, once the structural complexity could be controlled as a single entity, the optimization of a complex system would be potentially reduced to a one-dimensional concave optimization irrespective of the number of variables involved its description. This might open a way to a new type of information processing for efficient management of complex systems.Comment: 5 pages, 2 figures, to be presented at the International Conference on Complex Systems, Boston, October 28 - November 2, 200

Surveillance and the Self: Understanding Privacy and Identity in Digital Environments

The widespread use of internet enabled devices among contemporary US adults has given rise to a series of questions about issues of identity, privacy and group behaviors. The increasing use of algorithmic systems in social media and the attendant privacy concerns among users may also contribute to increased levels of strategic management of identity among users. In order to contribute to this discussion, this project examines perceptions and practices of privacy and self-representation in digital spaces among college age adults 18-24. This project utilizes semi-structured interview data collected with college students in the Eastern United States and focuses on both behavioral and attitudinal patterns. I specifically consider the impact of strategic interventions of corporate media platforms to collect, distribute, manage and utilize individual level data on participants\u27 information consumption, individual identity representation and group affiliation. Preliminary data suggests that participants engage partial and strategic representations of self across diverse media platforms. Patterns of self-representation are shaped by a wide variety of factors including in-group online community norms, perceptions of visibility and privacy, algorithmic distributions of information and individual perceptions of technology. Furthermore, online identity, while partial and strategically created, has the potential to impact self-identity and group affiliation in a diverse set of offline and online contexts