AR-based serious game framework for post-stroke rehabilitation

Stroke is considered one of the main causes of death around the world. Survivors often suffer different kinds of disabilities in terms of their cognitive and motor capabilities, and are therefore unable to perform their day-to-day activities. To regain some of their cognitive as well as motor abilities, they require rehabilitation. To this end, we present a serious game framework based on augmented reality technology that may motivate the patients’ involvement in the rehabilitation exercise. Additionally, we analyze the requirements for such a framework and describe the concept and implementation of the proposed approach. Furthermore, we designed a wireless vibrotactile output device that is attached to a tangible object. The tangible object that is connected to the framework can give haptic as well as audio-visual feedback to the patient in a more motivating and entertaining environment for rehabilitation exercises. The suitability and utility of the proposed framework was evaluated with real stroke patients and compared against the performance of a healthy control group, thus facilitating occupational therapists in assessing a patient’s progress. Our evaluations show that the serious games with vibrotactile feedback are well accepted by patients.     

Emulation of complex open quantum systems using superconducting qubits

With quantum computers being out of reach for now, quantum simulators are alternative devices for efficient and accurate simulation of problems that are challenging to tackle using conventional computers. Quantum simulators are classified into analog and digital, with the possibility of constructing “hybrid” simulators by combining both techniques. Here we focus on analog quantum simulators of open quantum systems and address the limit that they can beat classical computers. In particular, as an example, we discuss simulation of the chlorosome light-harvesting antenna from green sulfur bacteria with over 250 phonon modes coupled to each electronic state. Furthermore, we propose physical setups that can be used to reproduce the quantum dynamics of a standard and multiple-mode Holstein model. The proposed scheme is based on currently available technology of superconducting circuits consist of flux qubits and quantum oscillators.     

Probabilistic knowledge representation using the principle of maximum entropy and Gröbner basis theory

An often used methodology for reasoning with probabilistic conditional knowledge bases is provided by the principle of maximum entropy (so-called MaxEnt principle) that realises an idea of least amount of assumed information and thus of being as unbiased as possible. In this paper we exploit the fact that MaxEnt distributions can be computed by solving nonlinear equation systems that reflect the conditional logical structure of these distributions. We apply the theory of Gröbner bases that is well known from computational algebra to the polynomial system which is associated with a MaxEnt distribution, in order to obtain results for reasoning with maximum entropy. We develop a three-phase compilation scheme extracting from a knowledge base consisting of probabilistic conditionals the information which is crucial for MaxEnt reasoning and transforming it to a Gröbner basis. Based on this transformation, a necessary condition for knowledge bases to be consistent is derived. Furthermore, approaches to answering MaxEnt queries are presented by demonstrating how inferring the MaxEnt probability of a single conditional from a given knowledge base is possible. Finally, we discuss computational methods to establish general MaxEnt inference rules.     

Computational performance of a parallelized three-dimensional high-order spectral element toolbox

In this paper, a comprehensive performance review of an MPI-based high-order three-dimensional spectral element method C++ toolbox is presented. The focus is put on the performance evaluation of several aspects with a particular emphasis on the parallel efficiency. The performance evaluation is analyzed with the help of a time prediction model based on a parameterization of the application and the hardware resources. Two tailor-made benchmark cases in computational fluid dynamics (CFD) are introduced and used to carry out this review, stressing the particular interest for clusters with up to thousands of cores. Some problems in the parallel implementation have been detected and corrected. The theoretical complexities with respect to the number of elements, to the polynomial degree, and to communication needs are correctly reproduced. It is concluded that this type of code has a nearly perfect speedup on machines with thousands of cores, and is ready to make the step to next-generation petaFLOP machines.     

Multi-class supervised classification of electrical borehole wall images using texture features

Electrical borehole wall images represent micro-resistivity measurements at the borehole wall. The lithology reconstruction is often based on visual interpretation done by geologists. This analysis is very time-consuming and subjective. Different geologists may interpret the data differently. In this work, linear discriminant analysis (LDA) in combination with texture features is used for an automated lithology reconstruction of ODP (Ocean Drilling Program) borehole 1203A drilled during Leg 197. Six rock groups are identified by their textural properties in resistivity data obtained by a Formation MircoScanner (FMS). Although discriminant analysis can be used for multi-class classification, non-optimal decision criteria for certain groups could emerge. For this reason, we use a combination of 2-class (binary) classifiers to increase the overall classification accuracy. The generalization ability of the combined classifiers is evaluated and optimized on a testing dataset where a classification rate of more than 80% for each of the six rock groups is achieved. The combined, trained classifiers are then applied on the whole dataset obtaining a statistical reconstruction of the logged formation. Compared to a single multi-class classifier the combined binary classifiers show better classification results for certain rock groups and more stable results in larger intervals of equal rock type.     

A comparison of local parametric C Bézier interpolants for triangular meshes

Parametric curved shape surface schemes interpolating vertices and normals of a given triangular mesh with arbitrary topology are widely used in computer graphics for gaming and real-time rendering due to their ability to effectively represent any surface of arbitrary genus. In this context, continuous curved shape surface schemes using only the information related to the triangle corresponding to the patch under construction, emerged as attractive solutions responding to the requirements of resource-limited hardware environments. In this paper we provide a unifying comparison of the local parametric C⁰ curved shape schemes we are aware of, based on a reformulation of their original constructions in terms of polynomial Bézier triangles. With this reformulation we find a geometric interpretation of all the schemes that allows us to analyse their strengths and shortcomings from a geometrical point of view. Further, we compare the four schemes with respect to their computational costs, their reproduction capabilities of analytic surfaces and their response to different surface interrogation methods on arbitrary triangle meshes with a low triangle count that actually occur in their real-world use.     

Finding Total Unimodularity in Optimization Problems Solved by Linear Programs

A popular approach in combinatorial optimization is to model problems as integer linear programs. Ideally, the relaxed linear program would have only integer solutions, which happens for instance when the constraint matrix is totally unimodular. Still, sometimes it is possible to build an integer solution with the same cost from the fractional solution. Examples are two scheduling problems (Baptiste and Schieber, J. Sched. 6(4):395–404, 2003; Brucker and Kravchenko, J. Sched. 11(4):229–237, 2008) and the single disk prefetching/caching problem (Albers et al., J. ACM 47:969–986, 2000). We show that problems such as the three previously mentioned can be separated into two subproblems: (1) finding an optimal feasible set of slots, and (2) assigning the jobs or pages to the slots. It is straigthforward to show that the latter can be solved greedily. We are able to solve the former with a totally unimodular linear program, from which we obtain simple combinatorial algorithms with improved worst case running time.     

Ultrafast thermal processing and nanocalorimetry at heating and cooling rates up to 1 MK/s

To generate artificial materials with advanced physical and chemical properties and to study phase transition kinetics on submillisecond time scale, an ultrafast nonadiabatic membrane nanocalorimeter was constructed. A set of commercially available membrane gauges for ultrafast nanocalorimetry has been developed. The gauges placed in a thermostat with controlled helium gas pressure and temperature can be utilized as devices for thermal processing and calorimetry with resolution of 1 nJ/K. Controlled ultrafast cooling, as well as heating, up to 10(6) K/s can be attained for nanogram samples. The maximum cooling rate is inversely proportional to the radius of the heated region of the gauge, which was in the range of 10-100 microm depending on the gauge. The minimum addenda heat capacity was 3 nJ/K. The dynamic heat-transfer problem for the temperature distribution in the membrane-gas system at ultrafast processing has been solved. The characteristic rate R(0) corresponding to quasistatic limit of the temperature change in the membrane-gas system has been found to be equal to 10(5) K/s for a 1 microm thick silicon nitride membrane in helium gas. Calorimeter performance at ultrafast rates has been verified by a set of test experiments. The method was applied for thermal processing and calorimetric measurements in a set of linear polymers. It has been established that nearly amorphous polyethylene can be obtained at a cooling rate of 10(6) K/s.     

Dimensional reduction of 3D building models using graph theory and its application in building energy simulation

Since the various people involved in the design process for a building project tend to hold conflicting views, this inevitably leads to a range of disparate models for planning and calculation purposes. In order to interpret the relevant geometrical, topological and semantical data for any given building model, we identify a structural component graph, a graph of room faces, a room graph and a relational object graph as aids and explain algorithms to derive these relations. We start with a building model by transferring its geometrical, topological and semantical data into a volume model, decomposing the latter into a so-called connection model and then extracting all air volume bodies and hulls of the model by means of further decomposition into elementary cyclic connection components. The technique is demonstrated within the scope of building energy simulation by deriving both a dimensionally reduced object model required for setting up a thermal multizone model and a geometrical model for defining single or multiple computational fluid dynamic domains in a building together with incidence matrices correlating these models. The algorithm is basically applicable to any building energy simulation tool.

How Convincing is Mr. Data's Smile: Affective Expressions of Machines

Emotions should play an important role in the design of interfaces because people interact with machines as if they were social actors. This paper presents a literature review on affective expressions through speech, music and body language. It summarizes the quality and quantity of their parameters and successful examples of synthesis. Moreover, a model for the convincingness of affective expressions, based on Fogg and Hsiang Tseng (1999), was developed and tested. The empirical data did not support the original model and therefore this paper proposes a new model, which is based on appropriateness and intensity of the expressions. Furthermore, the experiment investigated if the type of emotion (happiness, sadness, anger, surprise, fear and disgust), knowledge about the source (human or machine), the level of abstraction (natural face, computer rendered face and matrix face) and medium of presentation (visual, audio/visual, audio) of an affective expression influences its convincingness and distinctness. Only the type of emotion and multimedia presentations had an effect on convincingness. The distinctness of an expression depends on the abstraction and the media through which it is presented.