Metrics for Measuring Data Quality - Foundations for an Economic Oriented Management of Data Quality

The article develops metrics for an economic oriented management of data quality. Two data quality dimensions are focussed: consistency and timeliness. For deriving adequate metrics several requirements are stated (e. g. normalisation, cardinality, adaptivity, interpretability). Then the authors discuss existing approaches for measuring data quality and illustrate their weaknesses. Based upon these considerations, new metrics are developed for the data quality dimensions consistency and timeliness. These metrics are applied in practice and the results are illustrated in the case of a major German mobile services provider

Layered evaluation of interactive adaptive systems : framework and formative methods

Peer reviewedPostprin

MAC protocols for low-latency and energy-efficient WSN applications

Most of medium access control (MAC) protocols proposed for wireless sensor networks (WSN) are targeted only for single main objective, the energy efficiency. Other critical parameters such as low-latency, adaptivity to traffic conditions, scalability, system fairness, and bandwidth utilization are mostly overleaped or dealt as secondary objectives. The demand to address those issues increases with the growing interest in cheap, low-power, low- distance, and embedded WSNs. In this report, along with other vital parameters, we discuss suitability and limitations of different WSN MAC protocols for time critical and energy-efficient applications. As an example, we discuss the working of IEEE 802.15.4 in detail, explore its limitations, and derive efficient application-specific network parameter settings for time, energy, and bandwidth critical applications. Eventually, a new WSN MAC protocol Asynchronous Real-time Energy-efficient and Adaptive MAC (AREA-MAC) is proposed, which is intended to deal efficiently with time critical applications, and at the same time, to provide a better trade-off between other vital parameters, such as energy-efficiency, system fairness, throughput, scalability, and adaptivity to traffic conditions. On the other hand, two different optimization problems have been formulated using application-based traffic generating scenario to minimize network latency and maximize its lifetime

Production process stability - Core assumption of INDUSTRY 4.0 concept

Today's industrial enterprises are confronted by implementation of INDUSTRY 4.0 concept with basic problem - stabilised manufacturing and supporting processes. Through this phenomenon of stabilisation, they will achieve positive digital management of both processes and continuously throughput. There is required structural stability of horizontal (business) and vertical (digitized) manufacturing processes, supported through digitalised technologies of INDUSTRY 4.0 concept. Results presented in this paper based on the research results and survey realised in more industrial companies. Following will described basic model for structural process stabilisation in manufacturing environment. © Published under licence by IOP Publishing Ltd

A Survey of Quality of Service in Mobile Computing Environments

Accepted versio

An information adaptive system study report and development plan

The purpose of the information adaptive system (IAS) study was to determine how some selected Earth resource applications may be processed onboard a spacecraft and to provide a detailed preliminary IAS design for these applications. Detailed investigations of a number of applications were conducted with regard to IAS and three were selected for further analysis. Areas of future research and development include algorithmic specifications, system design specifications, and IAS recommended time lines

Learning and Management for Internet-of-Things: Accounting for Adaptivity and Scalability

Internet-of-Things (IoT) envisions an intelligent infrastructure of networked smart devices offering task-specific monitoring and control services. The unique features of IoT include extreme heterogeneity, massive number of devices, and unpredictable dynamics partially due to human interaction. These call for foundational innovations in network design and management. Ideally, it should allow efficient adaptation to changing environments, and low-cost implementation scalable to massive number of devices, subject to stringent latency constraints. To this end, the overarching goal of this paper is to outline a unified framework for online learning and management policies in IoT through joint advances in communication, networking, learning, and optimization. From the network architecture vantage point, the unified framework leverages a promising fog architecture that enables smart devices to have proximity access to cloud functionalities at the network edge, along the cloud-to-things continuum. From the algorithmic perspective, key innovations target online approaches adaptive to different degrees of nonstationarity in IoT dynamics, and their scalable model-free implementation under limited feedback that motivates blind or bandit approaches. The proposed framework aspires to offer a stepping stone that leads to systematic designs and analysis of task-specific learning and management schemes for IoT, along with a host of new research directions to build on.Comment: Submitted on June 15 to Proceeding of IEEE Special Issue on Adaptive and Scalable Communication Network

Adaptive User Interfaces for Intelligent E-Learning: Issues and Trends

Adaptive User Interfaces have a long history rooted in the emergence of such eminent technologies as Artificial Intelligence, Soft Computing, Graphical User Interface, JAVA, Internet, and Mobile Services. More specifically, the advent and advancement of the Web and Mobile Learning Services has brought forward adaptivity as an immensely important issue for both efficacy and acceptability of such services. The success of such a learning process depends on the intelligent context-oriented presentation of the domain knowledge and its adaptivity in terms of complexity and granularity consistent to the learner’s cognitive level/progress. Researchers have always deemed adaptive user interfaces as a promising solution in this regard. However, the richness in the human behavior, technological opportunities, and contextual nature of information offers daunting challenges. These require creativity, cross-domain synergy, cross-cultural and cross-demographic understanding, and an adequate representation of mission and conception of the task. This paper provides a review of state-of-the-art in adaptive user interface research in Intelligent Multimedia Educational Systems and related areas with an emphasis on core issues and future directions