Online segmentation of time series based on polynomial least-squares approximations

The paper presents SwiftSeg, a novel technique for online time series segmentation and piecewise polynomial representation. The segmentation approach is based on a least-squares approximation of time series in sliding and/or growing time windows utilizing a basis of orthogonal polynomials. This allows the definition of fast update steps for the approximating polynomial, where the computational effort depends only on the degree of the approximating polynomial and not on the length of the time window. The coefficients of the orthogonal expansion of the approximating polynomial-obtained by means of the update steps-can be interpreted as optimal (in the least-squares sense) estimators for average, slope, curvature, change of curvature, etc., of the signal in the time window considered. These coefficients, as well as the approximation error, may be used in a very intuitive way to define segmentation criteria. The properties of SwiftSeg are evaluated by means of some artificial and real benchmark time series. It is compared to three different offline and online techniques to assess its accuracy and runtime. It is shown that SwiftSeg-which is suitable for many data streaming applications-offers high accuracy at very low computational costs.     

Tests and Proofs

This special issue collects current advances in the ongoing attempt to obtain synergies from the combination of Tests and Proofs.     

The physiological mirror—a system for unconscious control of a virtual environment through physiological activity

This paper introduces a system for real-time physiological measurement, analysis, and metaphorical visualization within a virtual environment (VE). Our goal is to develop a method that allows humans to unconsciously relate to parts of an environment more strongly than to others, purely induced by their own physiological responses to the virtual reality (VR) displays. In particular, we exploit heart rate, respiration, and galvanic skin response in order to control the behavior of virtual characters in the VE. Such unconscious processes may become a useful tool for storytelling or assist guiding participants through a sequence of tasks in order to make the application more interesting, e.g., in rehabilitation. We claim that anchoring of subjective bodily states to a virtual reality (VR) can enhance a person’s sense of realism of the VR and ultimately create a stronger relationship between humans and the VR.     

Integrating cognitive load theory and concepts of human–computer interaction

With the continually increasing complexity of e-learning environments, there is a need for integrating concepts of cognitive load theory (CLT) with concepts of human–computer interaction (HCI). Basic concepts of both fields were reviewed and contrasted. A literature review was conducted within the literature database “The Guide to Computing Literature,” searching for “cognitive load theory” and “Sweller.” Sixty-five publications contained “cognitive load” in their titles or abstracts. Each publication was checked to see whether it contained the concepts of intrinsic, extraneous, or germane cognitive load. The review showed that CLT concepts have been adopted in HCI. However, the concept of germane cognitive load has attracted less attention up to the present time. Two conceptual models are proposed. The first model divides extraneous cognitive load into load induced by the instructional design and load caused by software usage. The model clarifies the focus of traditional usability principles and of existing instructional design principles derived from CLT. The second model fits CLT concepts into the basic components of user-centered design. The concept of germane cognitive load illustrates that an increase of cognitive load can be desirable when designing e-learning environments. Areas for future interdisciplinary research are sketched.     

In vivo interactive visualization of four-dimensional blood flow patterns

In this paper we give an overview over a series of experiments to visualize and measure flow fields in the human vascular system with respect to their diagnostic capabilities. The experiments utilize a selection of GPU-based sparse and dense flow visualization algorithms to show the diagnostic opportunities for volumetric cardiovascular phase contrast magnetic resonance imaging data sets. Besides classical hardware accelerated particle and line-based approaches, an extensible tublet-based visualization, a four-dimensional volumetric line integral convolution and a new two-dimensional cutting plane tool for three-dimensional velocity data sets have been implemented. To evaluate the results, several hearts of human subjects have been investigated and a flow phantom was built to artificially simulate distinctive flow features. Our results demonstrate that we are able to provide an interactive tool for cardiovascular diagnostics with complementary hardware accelerated visualizations. Electronic Supplementary Material  The online version of this article () contains supplementary material, which is available to authorized users.

An investigation of multiphase CFD modelling of a lateral sloshing tank

A near-resonant, sway-induced sloshing flow in a rectangular tank is used to compare a homogeneous and inhomogeneous multiphase approach for fluid density and viscosity in a commercial CFD code. Dimensional analysis of the relative motion between the phases suggests the application of an inhomogeneous multiphase model whereas previous published work has used the computationally cheaper homogeneous (or average property) approach. The comparison between the computational and experimental results shows that the homogeneous model tends to underestimate the experimental peak pressures by up to 50%. The inhomogeneous multiphase model gives good agreement with the experimental pressure data. Examination of the relative velocity at the fluid interface confirms that the inhomogeneous model is the appropriate model to use for the simulation of a violent sloshing flow.     

Robust Cardiac Function Assessment in 4D PC‐MRI Data of the Aorta and Pulmonary Artery

Four‐dimensional phase‐contrast magnetic resonance imaging (4D PC‐MRI) allows the non‐invasive acquisition of time‐resolved, 3D blood flow information. Stroke volumes (SVs) and regurgitation fractions (RFs) are two of the main measures to assess the cardiac function and severity of valvular pathologies. The flow rates in forward and backward direction through a plane above the aortic or pulmonary valve are required for their quantification. Unfortunately, the calculations are highly sensitive towards the plane's angulation since orthogonally passing flow is considered. This often leads to physiologically implausible results. In this work, a robust quantification method is introduced to overcome this problem. Collaborating radiologists and cardiologists were carefully observed while estimating SVs and RFs in various healthy volunteer and patient 4D PC‐MRI data sets with conventional quantification methods, that is, using a single plane above the valve that is freely movable along the centerline. By default it is aligned perpendicular to the vessel's centerline, but free angulation (rotation) is possible. This facilitated the automation of their approach which, in turn, allows to derive statistical information about the plane angulation sensitivity. Moreover, the experts expect a continuous decrease of the blood flow volume along the vessel course. Conventional methods are often unable to produce this behaviour. Thus, we present a procedure to fit a monotonous function that ensures such physiologically plausible results. In addition, this technique was adapted for the usage in branching vessels such as the pulmonary artery. The performed informal evaluation shows the capability of our method to support diagnosis; a parameter evaluation confirms the robustness. Vortex flow was identified as one of the main causes for quantification uncertainties.     

Active learning for extended finite state machines

We present a black-box active learning algorithm for inferring extended finite state machines (EFSM)s by dynamic black-box analysis. EFSMs can be used to model both data flow and control behavior of software and hardware components. Different dialects of EFSMs are widely used in tools for model-based software development, verification, and testing. Our algorithm infers a class of EFSMs called register automata. Register automata have a finite control structure, extended with variables (registers), assignments, and guards. Our algorithm is parameterized on a particular theory, i.e., a set of operations and tests on the data domain that can be used in guards.Key to our learning technique is a novel learning model based on so-called tree queries. The learning algorithm uses tree queries to infer symbolic data constraints on parameters, e.g., sequence numbers, time stamps, identifiers, or even simple arithmetic. We describe sufficient conditions for the properties that the symbolic constraints provided by a tree query in general must have to be usable in our learning model. We also show that, under these conditions, our framework induces a generalization of the classical Nerode equivalence and canonical automata construction to the symbolic setting. We have evaluated our algorithm in a black-box scenario, where tree queries are realized through (black-box) testing. Our case studies include connection establishment in TCP and a priority queue from the Java Class Library.     

Life Cycle of Smart Contracts in Blockchain Ecosystems

This paper discusses the life cycle of decentralized smart contracts, i.e. digital and executable representations of rights and obligations in a multi-party environment. The life cycle relies on blockchain technology, i.e. a distributed digital ledger, to ensure proper implementation and integrity of the smart contracts. The life cycle consists of four subsequent phases: Creation, freezing, execution, and finalization. For each phase actors and technological services are identified and explained in detail. With the life cycle at hand, risks and limitations of smart contracts and the underlying blockchain technology are briefly discussed.