High-Temperature Creep Behavior of Mixed Conducting La0.5Sr0.5Fe1−xCoxO3-δ (0.5≤x≤1) Materials

Steady-state compressive creep rate of La_0.5Sr_0.5Fe_0.5Co_0.5O_3−δ (LSFC) and La_0.5Sr_0.5CoO_3−δ (LSC) is reported in the temperature region 900°–1050°C and stress range 5–28 MPa. The stress exponents for the two materials were 1.71±0.18 and 1.24±0.15, respectively. The activation energy for creep was considerably higher for LSC (619±56 kJ/mol) than for LSFC (392±28 kJ/mol). The grain size exponent for LSC was 1.28±0.14. Considerably higher creep rates were observed for both materials in N₂ compared with air. Relaxation by creep of chemical-induced stresses in oxygen-permeable membranes is addressed, especially at low partial pressure of oxygen.     

Exploiting Ontology for Software License Agreements

Software end-users need to sign licenses to seal an agreement with the product providers. Habitually, users agree with the license (i.e. terms and conditions) without fully understanding the agreement. To address this issue, an ontological model is developed to formulate the user requirements and license agreements formally. This paper, introduces ontological model that includes the abstract license ontology of common features found in di?erent license agreements. The abstract license ontology is then extended to a few real world license agreements. The resulting model can be used for di?erent purposes such as querying the appropriate licenses for a speciˉc requirement or checking the license terms and conditions with user requirements.     

A scalable solution to the nearest neighbor search problem through local-search methods on neighbor graphs

Pattern Analysis and Applications - Nearest neighbor search is a powerful abstraction for data access; however, data indexing is troublesome even for approximate indexes. For intrinsically...     

Assessing task understanding in remote ultrasound diagnosis via gesture analysis

Pattern Analysis and Applications - This work presents a gesture-based approach to estimate task understanding and performance during remote ultrasound tasks. Our approach is comprised of...     

Tensor Clustering for Rendering Many‐Light Animations

Rendering animations of scenes with deformable objects, camera motion, and complex illumination, including indirect lighting and arbitrary shading, is a long‐standing challenge. Prior work has shown that complex lighting can be accurately approximated by a large collection of point lights. In this formulation, rendering of animation sequences becomes the problem of efficiently shading many surface samples from many lights across several frames. This paper presents a tensor formulation of the animated many‐light problem, where each element of the tensor expresses the contribution of one light to one pixel in one frame. We sparsely sample rows and columns of the tensor, and introduce a clustering algorithm to select a small number of representative lights to efficiently approximate the animation. Our algorithm achieves efficiency by reusing representatives across frames, while minimizing temporal flicker. We demonstrate our algorithm in a variety of scenes that include deformable objects, complex illumination and arbitrary shading and show that a surprisingly small number of representative lights is sufficient for high quality rendering. We believe out algorithm will find practical use in applications that require fast previews of complex animation.     

Technologies and logistics for phosphorus recovery from livestock waste

Phosphorus (P) runoff from livestock waste can trigger algal blooms that adversely affect aquatic life and human health. One strategy to mitigate this problem is to install nutrient recovery technologies that concentrate and mobilize nutrients from nutrient-rich regions to nutrient-deficient ones. We present supply chain design formulations to identify optimal types and locations for P recovery technologies. The formulations capture trade-offs in transportation costs, technology efficiency, investment/operational costs, revenue collected from different recovered products (struvite and nutrient cakes), and environmental impact. Our computational framework is used to analyze the impact of different scenarios for market prices of recovered products, recovery yields, and remediation costs. We find that transportation of waste alone (without any processing) can achieve significant reductions in environmental impact at low cost, but cannot achieve economic sustainability in the long run due to the lack of direct revenue streams. Mechanical separation technologies that recover P in the form of nutrient cakes are low-cost solutions that can achieve high environmental benefits and reduced transportation costs, but revenues are also limited due to low values of the cakes. Struvite crystallization in fluidized beds is found to be a highly attractive option under current struvite prices, but economic sustainability is strongly dependent on yield recoveries (which are currently highly uncertain).     

An Improved Hybrid Indoor Positioning Algorithm via QPSO and MLP Signal Weighting

Accurate location or positioning of people and self-driven devices in large indoor environments has become an important necessity The application of increasingly automated self-operating moving transportation units, in large indoor spaces demands a precise knowledge of their positions. Technologies like WiFi and Bluetooth, despite their low-cost and availability, are sensitive to signal noise and fading effects. For these reasons, a hybrid approach, which uses two different signal sources, has proven to be more resilient and accurate for the positioning determination in indoor environments. Hence, this paper proposes an improved hybrid technique to implement a fingerprinting based indoor positioning, using Received Signal Strength information from available Wireless Local Area Network access points, together with the Wireless Sensor Networks technology. Six signals were recorded on a regular grid of anchor points, covering the research space. An optimization was performed by relative signal weighting, to minimize the average positioning error over the research space. The optimization process was conducted using a standard Quantum Particle Swarm Optimization, while the position error estimate for all given sets of weighted signals was performed using a Multilayer Perceptron (MLP) neural network. Compared to our previous research works, the MLP architecture was improved to three hidden layers and its learning parameters were finely tuned. These experimental results led to the 20% reduction of the positioning error when a suitable set of signal weights was calculated in the optimization process. Our final achieved value of 0.725 m of the location incertitude shows a sensible improvement compared to our previous results.     

A quality culture for health promotion!

Circulating platelets are susceptible to various stimuli in vessels, and a certain portion of platelets may thereby form native microaggregates (NMAs), which can be visualized by a bother scanning electron microscopy (SEM). We developed an easy method to evaluate the existence and extent of NMAs and the subsequent spontaneous platelet aggregation (SPA) induced by not any agonist but stirring force with a novel platelet aggregometer (PA-200; Kowa, Tsukuba, Japan) employing a particle-counting method based on laser light scattering. In this system, platelet-rich plasma obtained by a delicate centrifugation was infused in a cuvette to replace the content and to avoid stirring shear. An insertion attachment was designed in a coaxial shape to maintain a constant sample volume. Our data indicated that NMAs, tentatively defined as a "small" division by their light scattering (25-400 of the intensity threshold), could be detected by not only a complicated SEM but also by our simple system with the PA-200 in a few minutes. No correlation was found in the comparison of the existence of NMAs and the SPA generation, in aliquot platelets, respectively. These results suggested that NMAs and SPA might be mutually different cluster and have meanings as representations of platelet status.     

Industrial implementation of controller performance analysis technology

In this paper, a controller performance monitoring technology is introduced with a focus on its industrial implementation and applications. The technology to be introduced in this paper is known as Performance Analysis Toolbox and Solutions (PATS). The main components are discussed, which include data collection, closed-loop systems identification, control valve stiction monitoring, univariate control performance monitoring, multivariate control performance monitoring, model predictive control performance monitoring, etc. It is shown, through a thorough industry case study with various components of PATS, that the integration of the technology provides more convincing diagnosis results and facilitates identification of control improvement opportunities. Some components of the developed technology can be downloaded from the website http://www.ualberta.ca/～bhuang/research/research.htm.