Rapid consolidation of powdered materials by induction hot pressing

A rapid hot press system in which the heat is supplied by RF induction to rapidly consolidate thermoelectric materials is described. Use of RF induction heating enables rapid heating and consolidation of powdered materials over a wide temperature range. Such rapid consolidation in nanomaterials is typically performed by spark plasma sintering (SPS) which can be much more expensive. Details of the system design, instrumentation, and performance using a thermoelectric material as an example are reported. The Seebeck coefficient, electrical resistivity, and thermal diffusivity of thermoelectric PbTe material pressed at an optimized temperature and time in this system are shown to agree with material consolidated under typical consolidation parameters.     

A high temperature apparatus for measurement of the Seebeck coefficient

A high temperature Seebeck coefficient measurement apparatus with various features to minimize typical sources of error is designed and built. Common sources of temperature and voltage measurement error are described and principles to overcome these are proposed. With these guiding principles, a high temperature Seebeck measurement apparatus with a uniaxial 4-point contact geometry is designed to operate from room temperature to over 1200 K. This instrument design is simple to operate, and suitable for bulk samples with a broad range of physical types and shapes.     

An Empirical Evaluation of the System Usability Scale

This article presents nearly 10 year's worth of System Usability Scale (SUS) data collected on numerous products in all phases of the development lifecycle. The SUS, developed by Brooke (1996) Brooke, J. 1996. “SUS: A “quick and dirty” usability scale”. In Usability evaluation in industry, Edited by: Jordan, P. W., Thomas, B. A. Weerdmeester and McClelland, I. L. 189–194. London: Taylor & Francis.  [Google Scholar], reflected a strong need in the usability community for a tool that could quickly and easily collect a user's subjective rating of a product's usability. The data in this study indicate that the SUS fulfills that need. Results from the analysis of this large number of SUS scores show that the SUS is a highly robust and versatile tool for usability professionals. The article presents these results and discusses their implications, describes nontraditional uses of the SUS, explains a proposed modification to the SUS to provide an adjective rating that correlates with a given score, and provides details of what constitutes an acceptable SUS score.     

From big smartphone data to worldwide research: The Mobile Data Challenge

This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of mobile data analysis methodologies. First, we review the Lausanne Data Collection Campaign (LDCC), an initiative to collect unique longitudinal smartphone dataset for the MDC. Then, we introduce the Open and Dedicated Tracks of the MDC, describe the specific datasets used in each of them, discuss the key design and implementation aspects introduced in order to generate privacy-preserving and scientifically relevant mobile data resources for wider use by the research community, and summarize the main research trends found among the 100+ challenge submissions. We finalize by discussing the main lessons learned from the participation of several hundred researchers worldwide in the MDC Tracks.     

Human interaction discovery in smartphone proximity networks

Since humans are fundamentally social beings and interact frequently with others in their daily life, understanding social context is of primary importance in building context-aware applications. In this paper, using smartphone Bluetooth as a proximity sensor to create social networks, we present a probabilistic approach to mine human interaction types in real life. Our analysis is conducted on Bluetooth data continuously sensed with smartphones for over one year from 40 individuals who are professionally or personally related. The results show that the model can automatically discover a variety of social contexts. We objectively validated our model by studying its predictive and retrieval performance.     

Nonrigid structure-from-motion: estimating shape and motion with hierarchical Priors

This paper describes methods for recovering time-varying shape and motion of non-rigid 3D objects from uncalibrated 2D point tracks. For example, given a video recording of a talking person, we would like to estimate the 3D shape of the face at each instant, and learn a model of facial deformation. Time-varying shape is modeled as a rigid transformation combined with a non-rigid deformation. Reconstruction is ill-posed if arbitrary deformations are allowed, and thus additional assumptions about deformations are required. We first suggest restricting shapes to lie within a low-dimensional subspace, and describe estimation algorithms. However, this restriction alone is insufficient to constrain reconstruction. To address these problems, we propose a reconstruction method using a Probabilistic Principal Components Analysis (PPCA) shape model, and an estimation algorithm that simultaneously estimates 3D shape and motion for each instant, learns the PPCA model parameters, and robustly fills-in missing data points. We then extend the model to model temporal dynamics in object shape, allowing the algorithm to robustly handle severe cases of missing data.     

Chaotic frequency scaling in a coupled oscillator model for free rhythmic actions

The question of how best to model rhythmic movements at self-selected amplitude-frequency combinations, and their variability, is a long-standing issue. This study presents a systematic analysis of a coupled oscillator system that has successfully accounted for the experimental result that humans' preferred oscillation frequencies closely correspond to the linear resonance frequencies of the biomechanical limb systems, a phenomenon known as resonance tuning or frequency scaling. The dynamics of the coupled oscillator model is explored by numerical integration in different areas of its parameter space, where a period doubling route to chaotic dynamics is discovered. It is shown that even in the regions of the parameter space with chaotic solutions, the model still effectively scales to the biomechanical oscillator's natural frequency. Hence, there is a solution providing for frequency scaling in the presence of chaotic variability. The implications of these results for interpreting variability as fundamentally stochastic or chaotic are discussed.     

Modeling heavy metal mass releases from urban battery litter

Consumer batteries littered on urban pavements release metals of environmental significance (Ag, Cd, Cr, Cu, Hg, Li, Mn, Ni, Pd, Ti, Zn) to stormwater runoff. Predicting the mass loading of any one metal is difficult because of the random composition of battery litter. However, when littering is modeled as a conditional filtered Poisson process, bounds may be estimated for the mean and variance of site mass loading for any metal if the site litter rate and battery product contributions are known. Site-specific data on the battery brand distribution in litter can improve load estimates, but statistics computed from 5500 littered batteries collected in the Cleveland area may be used to approximate the brand distribution. Zinc load calculations based on battery litter size, type and brand discretizations are implemented in a model titled BLML and illustrated for a case-study location. Results indicate that, at some urban sites, zinc released from battery litter can be the largest source of zinc in urban pavement runoff.     

A taxonomy for and analysis of multi-person-display ecosystems

Interactive displays are increasingly being distributed in a broad spectrum of everyday life environments: they have very diverse form factors and portability characteristics, support a variety of interaction techniques, and can be used by a variable number of people. The coupling of multiple displays creates an interactive “ecosystem of displays”. Such an ecosystem is suitable for particular social contexts, which in turn generates novel settings for communication and performance and challenges in ownership. This paper aims at providing a design space that can inform the designers of such ecosystems. To this end, we provide a taxonomy that builds on the size of the ecosystem and on the degree of individual engagement as dimensions. We recognize areas where physical constraints imply certain kinds of social engagement, versus other areas where further work on interaction techniques for coupling displays can open new design spaces.     

Theoretical justification of approximate norm minimization method for intelligent digital redesign

This paper investigates the theoretical justification of intelligent digital redesign (IDR) methods based on the approximate discrete-time models. Its main purpose is to design the digital fuzzy controller achieving the minimum norm distance between the trajectories of the approximate closed-loop systems under the analog and the digital controls. It is verified that, if there exist the digital gains such that the approximate norm distance is sufficiently small, the redesigned controller makes the trajectories of the exact closed-loop systems close, or, at least, asymptotically stabilizes the plant.