178,222 research outputs found
Responsible Composition and Optimization of Integration Processes under Correctness Preserving Guarantees
Enterprise Application Integration deals with the problem of connecting
heterogeneous applications, and is the centerpiece of current on-premise, cloud
and device integration scenarios. For integration scenarios, structurally
correct composition of patterns into processes and improvements of integration
processes are crucial. In order to achieve this, we formalize compositions of
integration patterns based on their characteristics, and describe optimization
strategies that help to reduce the model complexity, and improve the process
execution efficiency using design time techniques. Using the formalism of timed
DB-nets - a refinement of Petri nets - we model integration logic features such
as control- and data flow, transactional data storage, compensation and
exception handling, and time aspects that are present in reoccurring solutions
as separate integration patterns. We then propose a realization of optimization
strategies using graph rewriting, and prove that the optimizations we consider
preserve both structural and functional correctness. We evaluate the
improvements on a real-world catalog of pattern compositions, containing over
900 integration processes, and illustrate the correctness properties in case
studies based on two of these processes.Comment: 37 page
From piles to tiles: designing for overview and control in case handling systems
Poor overview and control of workload in electronic case handling systems is a potential health risk factor which affects the users. Case handling systems must therefore be designed to give the users a better overview and maximum control over their workload. In an earlier study, we developed a prototype interface for managing cases, based on the piles metaphor. This paper introduces a second prototype, which is designed to incorporate the findings of an evaluation of the piles metaphor prototype. In this second prototype cases are visualized as “tiles”, reflecting the number and complexity of the cases. This paper also describes some the results of the evaluation of the tiles prototype
Physical Representation-based Predicate Optimization for a Visual Analytics Database
Querying the content of images, video, and other non-textual data sources
requires expensive content extraction methods. Modern extraction techniques are
based on deep convolutional neural networks (CNNs) and can classify objects
within images with astounding accuracy. Unfortunately, these methods are slow:
processing a single image can take about 10 milliseconds on modern GPU-based
hardware. As massive video libraries become ubiquitous, running a content-based
query over millions of video frames is prohibitive.
One promising approach to reduce the runtime cost of queries of visual
content is to use a hierarchical model, such as a cascade, where simple cases
are handled by an inexpensive classifier. Prior work has sought to design
cascades that optimize the computational cost of inference by, for example,
using smaller CNNs. However, we observe that there are critical factors besides
the inference time that dramatically impact the overall query time. Notably, by
treating the physical representation of the input image as part of our query
optimization---that is, by including image transforms, such as resolution
scaling or color-depth reduction, within the cascade---we can optimize data
handling costs and enable drastically more efficient classifier cascades.
In this paper, we propose Tahoma, which generates and evaluates many
potential classifier cascades that jointly optimize the CNN architecture and
input data representation. Our experiments on a subset of ImageNet show that
Tahoma's input transformations speed up cascades by up to 35 times. We also
find up to a 98x speedup over the ResNet50 classifier with no loss in accuracy,
and a 280x speedup if some accuracy is sacrificed.Comment: Camera-ready version of the paper submitted to ICDE 2019, In
Proceedings of the 35th IEEE International Conference on Data Engineering
(ICDE 2019
Layout Optimization of a repair facility using discrete event simulation
Technological advancements in the field of simulation have enabled production managers to model and simulate their facilities under various scenarios, in order to optimize system performance. In particular the reconfiguration of factory layouts can be time consuming and expensive; Discrete Event Simulation (DES) can be used to model and assess various scenarios to assist production managers with layout planning. Significant benefits can be achieved through the use of DES for factory layout optimization including: decreased lead times, reduced manufacturing costs, efficient materials handling and increased profit. This paper presents the development of a DES model in WITNESS for the analysis and factory layout optimization of a repair facility. The aim of the model is to allow decision makers to assess various layouts and configurations with a view to optimize production. The model has been built with a link to an Excel spreadsheet to enable data input and the visualization of Key Performance Indicators (KPIs). Specific functions have been built into the simulation model to set and save new layouts within Excel to facilitate layout optimization. The model will be used to optimize the factory configuration
Alternative line delivery strategies support a forklift free transition in a high product variety environment
Forklift transport fails when it comes to efficiency. As a result, more and more attention is going to alternative transport systems that automate or further structure the material flow; such as line deliveries by train and conveyor technology. Only substituting the transport system itself is not cost-effective. The resulting improvements are rather low compared to the high investment cost. Therefore, in this paper alternative material flow and line delivery strategies are taken into consideration. Within a high product variety environment a combination of materials kitting and line stocking is proposed. This approach has some important benefits on top of the pure forklift free transition. A basic model is constructed to calculate the kitting area and transport system requirements. A truck assembly company is used as case study. A feasibility study is carried out, to give a rough indication of the cost-effectiveness of the model
Shipboard Crisis Management: A Case Study.
The loss of the "Green Lily" in 1997 is used as a case study to highlight the characteristics of escalating crises. As in similar safety critical industries, these situations are unpredictable events that may require co-ordinated but flexible and creative responses from individuals and teams working in stressful conditions. Fundamental skill requirements for crisis management are situational awareness and decision making. This paper reviews the naturalistic decision making (NDM) model for insights into the nature of these skills and considers the optimal training regimes to cultivate them. The paper concludes with a review of the issues regarding the assessment of crisis management skills and current research into the determination of behavioural markers for measuring competence
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