SleepExplorer: a visualization tool to make sense of correlations between personal sleep data and contextual factors

Getting enough quality sleep is a key part of a healthy lifestyle. Many people are tracking their sleep through mobile and wearable technology, together with contextual information that may influence sleep quality, like exercise, diet, and stress. However, there is limited support to help people make sense of this wealth of data, i.e., to explore the relationship between sleep data and contextual data. We strive to bridge this gap between sleep-tracking and sense-making through the design of SleepExplorer, a web-based tool that helps individuals understand sleep quality through multi-dimensional sleep structure and explore correlations between sleep data and contextual information. Based on a two-week field study with 12 participants, this paper offers a rich understanding on how technology can support sense-making on personal sleep data: SleepExplorer organizes a flux of sleep data into sleep structure, guides sleep-tracking activities, highlights connections between sleep and contributing factors, and supports individuals in taking actions. We discuss challenges and opportunities to inform the work of researchers and designers creating data-driven health and well-being applications.     

A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem

Meta-heuristics are frequently used to tackle NP-hard combinatorial optimization problems. With this paper we contribute to the understanding of the success of 2-opt based local search algorithms for solving the traveling salesperson problem (TSP). Although 2-opt is widely used in practice, it is hard to understand its success from a theoretical perspective. We take a statistical approach and examine the features of TSP instances that make the problem either hard or easy to solve. As a measure of problem difficulty for 2-opt we use the approximation ratio that it achieves on a given instance. Our investigations point out important features that make TSP instances hard or easy to be approximated by 2-opt.     

SEMPA – Ein Ansatz des Semantischen Prozessmanagements zur Planung von Prozessmodellen

Currently process modeling is mostly done manually. Therefore, the initial design of process models as well as changes to process models which are frequently necessary to react to new market developments or new regulations are time-consuming tasks. In this paper we introduce SEMPA, an approach for the partly automatic planning of process models. Using ontologies to semantically describe actions – as envisioned in Semantic Business Process Management –, a process model for a specified problem setting can be created automatically. In comparison to existing planning algorithms our approach creates process models including control structures and is able to cope with complex and numerical input and output parameters of actions. The prototypical implementation as well as an example taken from the financial services domain illustrate the practical benefit of our approach.     

Directed model checking with distance-preserving abstractions

In directed model checking, the traversal of the state space is guided by an estimate of the distance from the current state to the nearest error state. This paper presents a distance-preserving abstraction for concurrent systems that allows one to compute an interesting estimate of the error distance without hitting the state explosion problem. Our experiments show a dramatic reduction both in the number of states explored by the model checker and in the total runtime.     

Thermal modeling in electricity assisted incremental sheet forming

A thermal model was built to account for the effects of geometrical parameters of sheet specimen, process parameters and material parameters on the temperature increase of the sheet specimen in Electricity-Assisted Incremental Sheet Forming (EISF). In the EISF, the local area of sheet specimen contacting with a forming tool is heated by direct current, which flows through the forming tool to the sheet specimen. EISF experiments of two high strength steel sheets were carried out to validate the thermal model. The thermal model can be integrated into the control program of EISF system to achieve more accurate temperature control.     

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Two new control signal approaches for obtaining the MRAS-CDM and a real-time application

The coefficient diagram method (CDM) is one of the most effective control design methods. It creates control systems that are very stable and robust with responses without the overshoot and small settling time. Furthermore, all control parameters of the control systems are changed by varying some adjustment parameters in CDM depending on the demands. The model reference adaptive systems (MRAS) are the systems that follow and change the control parameters according to a given model reference system. There are several methods to combine the CDM with MRAS. One of these is to use the MRAS parameters as a gain of the CDM parameters. Another is to directly use the CDM parameters as the MRAS parameters. In the industrial applications, the system parameters can be changed frequently, but if the controller, by self-tuning, recalculates and develops its own parameters continuously, the system becomes more robust. Also, if the poles of the controlled systems approach the jw axis, the response of the closed-loop MRAS becomes more and more insufficient. In order to obtain better results, CDM is combined with a self-tuning model reference adaptive system. Systems controlled by a model reference adaptive controller give responses with small or without overshoot, have small settling times, and are more robust. Thus, in this paper, a hybrid combination of MRAS and CDM is developed and two different control structures of the control signal are investigated. The two methods are compared with MRAS and applied to real-time process control systems.     

Adaptive isogeometric analysis by local h-refinement with T-splines

Isogeometric analysis based on non-uniform rational B-splines (NURBS) as basis functions preserves the exact geometry but suffers from the drawback of a rectangular grid of control points in the parameter space, which renders a purely local refinement impossible. This paper demonstrates how this difficulty can be overcome by using T-splines instead. T-splines allow the introduction of so-called T-junctions, which are related to hanging nodes in the standard FEM. Obeying a few straightforward rules, rectangular patches in the parameter space of the T-splines can be subdivided and thus a local refinement becomes feasible while still preserving the exact geometry. Furthermore, it is shown how state-of-the-art a posteriori error estimation techniques can be combined with refinement by T-splines. Numerical examples underline the potential of isogeometric analysis with T-splines and give hints for further developments.