1,099 research outputs found
Towards Vision-Based Smart Hospitals: A System for Tracking and Monitoring Hand Hygiene Compliance
One in twenty-five patients admitted to a hospital will suffer from a
hospital acquired infection. If we can intelligently track healthcare staff,
patients, and visitors, we can better understand the sources of such
infections. We envision a smart hospital capable of increasing operational
efficiency and improving patient care with less spending. In this paper, we
propose a non-intrusive vision-based system for tracking people's activity in
hospitals. We evaluate our method for the problem of measuring hand hygiene
compliance. Empirically, our method outperforms existing solutions such as
proximity-based techniques and covert in-person observational studies. We
present intuitive, qualitative results that analyze human movement patterns and
conduct spatial analytics which convey our method's interpretability. This work
is a step towards a computer-vision based smart hospital and demonstrates
promising results for reducing hospital acquired infections.Comment: Machine Learning for Healthcare Conference (MLHC
Architecture of Environmental Risk Modelling: for a faster and more robust response to natural disasters
Demands on the disaster response capacity of the European Union are likely to
increase, as the impacts of disasters continue to grow both in size and
frequency. This has resulted in intensive research on issues concerning
spatially-explicit information and modelling and their multiple sources of
uncertainty. Geospatial support is one of the forms of assistance frequently
required by emergency response centres along with hazard forecast and event
management assessment. Robust modelling of natural hazards requires dynamic
simulations under an array of multiple inputs from different sources.
Uncertainty is associated with meteorological forecast and calibration of the
model parameters. Software uncertainty also derives from the data
transformation models (D-TM) needed for predicting hazard behaviour and its
consequences. On the other hand, social contributions have recently been
recognized as valuable in raw-data collection and mapping efforts traditionally
dominated by professional organizations. Here an architecture overview is
proposed for adaptive and robust modelling of natural hazards, following the
Semantic Array Programming paradigm to also include the distributed array of
social contributors called Citizen Sensor in a semantically-enhanced strategy
for D-TM modelling. The modelling architecture proposes a multicriteria
approach for assessing the array of potential impacts with qualitative rapid
assessment methods based on a Partial Open Loop Feedback Control (POLFC) schema
and complementing more traditional and accurate a-posteriori assessment. We
discuss the computational aspect of environmental risk modelling using
array-based parallel paradigms on High Performance Computing (HPC) platforms,
in order for the implications of urgency to be introduced into the systems
(Urgent-HPC).Comment: 12 pages, 1 figure, 1 text box, presented at the 3rd Conference of
Computational Interdisciplinary Sciences (CCIS 2014), Asuncion, Paragua
Toward Semantics-aware Representation of Digital Business Processes
An extended enterprise (EE) can be described by a set of models each representing a specific aspect of the EE.
Aspects can for example be the process flow or the value description. However, different models are done by different
people, which may use different terminology, which prevents relating the models. Therefore, we propose a framework
consisting of process flow and value aspects and in addition a static domain model with structural and relational
components. Further, we outline the usage of the static domain model to enable relating the different aspects
Enabling Multi-Perspective Business Process Compliance
A particular challenge for any enterprise is to ensure that its business processes conform with compliance rules, i.e., semantic constraints on the multiple perspectives of the business processes. Compliance rules stem, for example, from legal regulations, corporate best practices, domain-specific guidelines, and industrial standards. In general, compliance rules are multi-perspective, i.e., they not only restrict the process behavior (i.e. control flow), but may refer to other process perspectives (e.g. time, data, and resources) and the interactions (i.e. message exchanges) of a business process with other processes as well.
The aim of this thesis is to improve the specification and verification of multi-perspective process compliance based on three contributions:
1. The extended Compliance Rule Graph (eCRG) language, which enables the visual modeling of multi-perspective compliance rules. Besides control flow, the latter may refer to the time, data, resource, and interaction perspectives of a business process.
2. A framework for multi-perspective monitoring of the compliance of running processes with a given set of eCRG compliance rules.
3. Techniques for verifying business process compliance with respect to the interaction perspective. In particular, we consider compliance verification for cross-organizational
business processes, for which solely incomplete process knowledge is available.
All contributions were thoroughly evaluated through proof-of-concept prototypes, case studies, empirical studies, and systematic comparisons with related works
Enabling Flexibility in Process-Aware Information Systems: Challenges, Methods, Technologies
In today’s dynamic business world, the success of a company increasingly depends on its ability to react to changes in its environment in a quick and flexible way. Companies have therefore identified process agility as a competitive advantage to address business trends like increasing product and service variability or faster time to market, and to ensure business IT alignment. Along this trend, a new generation of information systems has emerged—so-called process-aware information systems (PAIS), like workflow management systems, case handling tools, and service orchestration engines.
With this book, Reichert and Weber address these flexibility needs and provide an overview of PAIS with a strong focus on methods and technologies fostering flexibility for all phases of the process lifecycle (i.e., modeling, configuration, execution and evolution). Their presentation is divided into six parts. Part I starts with an introduction of fundamental PAIS concepts and establishes the context of process flexibility in the light of practical scenarios. Part II focuses on flexibility support for pre-specified processes, the currently predominant paradigm in the field of business process management (BPM). Part III details flexibility support for loosely specified processes, which only partially specify the process model at build-time, while decisions regarding the exact specification of certain model parts are deferred to the run-time. Part IV deals with user- and data-driven processes, which aim at a tight integration of processes and data, and hence enable an increased flexibility compared to traditional PAIS. Part V introduces existing technologies and systems for the realization of a flexible PAIS. Finally, Part VI summarizes the main ideas of this book and gives an outlook on advanced flexibility issues.
The attached pdf file gives a preview on Chapter 3 of the book which explains the book's overall structure
Estimating productivity gains in digital automation
This paper proposes a novel productivity estimation model to evaluate the
effects of adopting Artificial Intelligence (AI) components in a production
chain. Our model provides evidence to address the "AI's" Solow's Paradox. We
provide (i) theoretical and empirical evidence to explain Solow's dichotomy;
(ii) a data-driven model to estimate and asses productivity variations; (iii) a
methodology underpinned on process mining datasets to determine the business
process, BP, and productivity; (iv) a set of computer simulation parameters;
(v) and empirical analysis on labour-distribution. These provide data on why we
consider AI Solow's paradox a consequence of metric mismeasurement.Comment: 11 pages and 9 figure
04451 Abstracts Collection -- Future Generation Grids
The Dagstuhl Seminar 04451 "Future Generation Grid" was held in the International
Conference and Research Center (IBFI), Schloss Dagstuhl from 1st
to 5th November 2004. The focus of the seminar was on open problems and
future challenges in the design of next generation Grid systems. A total of 45
participants presented their current projects, research plans, and new ideas in
the area of Grid technologies. Several evening sessions with vivid discussions
on future trends complemented the talks. This report gives an overview of the
background and the findings of the seminar
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