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A Tablet-Based Assessment of Rhythmic Ability.
The exponential rise in use of mobile consumer electronics has presented a great potential for research to be conducted remotely, with participants numbering several orders of magnitude greater than a typical research paradigm. Here, we attempt to demonstrate the validity and reliability of using a consumer game-engine to create software presented on a mobile tablet to assess sensorimotor synchronization, a proxy of rhythmic ability. Our goal was to ascertain whether previously observed research results can be replicated, rather than assess whether a mobile tablet achieves comparable performance to a desktop computer. To achieve this, younger (aged 18-35 years) and older (aged 60-80 years) adult musicians and non-musicians were recruited to play a custom-designed sensorimotor synchronization assessment on a mobile tablet in a controlled laboratory environment. To assess reliability, participants performed the assessment twice, separated by a week, and an intra-class correlation coefficient (ICC) was calculated. Results supported the validity of this approach to assessing rhythmic abilities by replicating previously observed results. Specifically, musicians performed better than non-musicians, and younger adults performed better than older adults. Participants also performed best when the tempo was in the range of previously-identified preferred tempos, when the stimuli included both audio and visual information, and when synchronizing on-beat compared to off-beat or continuation (self-paced) synchronization. Additionally, high ICC values (>0.75) suggested excellent test-retest reliability. Together, these results support the notion that consumer electronics running software built with a game engine may serve as a valuable resource for remote, mobile-based data collection of rhythmic abilities
A component-oriented programming framework for developing embedded mobile robot software using PECOS model
A practical framework for component-based software engineering of embedded real-time systems, particularly for autonomous mobile robot embedded software development using PECOS component model is proposed The main features of this framework are: (1) use graphical representation for components definition and composition; (2) target C language for optimal code generation with small micro-controller; and (3) does not requires run-time support except for real-time kernel. Real-time implementation indicates that, the PECOS component model together with the proposed framework is suitable for resource constrained embedded systems
A Compositional Semantics for Stochastic Reo Connectors
In this paper we present a compositional semantics for the channel-based
coordination language Reo which enables the analysis of quality of service
(QoS) properties of service compositions. For this purpose, we annotate Reo
channels with stochastic delay rates and explicitly model data-arrival rates at
the boundary of a connector, to capture its interaction with the services that
comprise its environment. We propose Stochastic Reo automata as an extension of
Reo automata, in order to compositionally derive a QoS-aware semantics for Reo.
We further present a translation of Stochastic Reo automata to Continuous-Time
Markov Chains (CTMCs). This translation enables us to use third-party CTMC
verification tools to do an end-to-end performance analysis of service
compositions.Comment: In Proceedings FOCLASA 2010, arXiv:1007.499
Cooperative Adaptive Control for Cloud-Based Robotics
This paper studies collaboration through the cloud in the context of
cooperative adaptive control for robot manipulators. We first consider the case
of multiple robots manipulating a common object through synchronous centralized
update laws to identify unknown inertial parameters. Through this development,
we introduce a notion of Collective Sufficient Richness, wherein parameter
convergence can be enabled through teamwork in the group. The introduction of
this property and the analysis of stable adaptive controllers that benefit from
it constitute the main new contributions of this work. Building on this
original example, we then consider decentralized update laws, time-varying
network topologies, and the influence of communication delays on this process.
Perhaps surprisingly, these nonidealized networked conditions inherit the same
benefits of convergence being determined through collective effects for the
group. Simple simulations of a planar manipulator identifying an unknown load
are provided to illustrate the central idea and benefits of Collective
Sufficient Richness.Comment: ICRA 201
SCOPE: Scalable Composite Optimization for Learning on Spark
Many machine learning models, such as logistic regression~(LR) and support
vector machine~(SVM), can be formulated as composite optimization problems.
Recently, many distributed stochastic optimization~(DSO) methods have been
proposed to solve the large-scale composite optimization problems, which have
shown better performance than traditional batch methods. However, most of these
DSO methods are not scalable enough. In this paper, we propose a novel DSO
method, called \underline{s}calable \underline{c}omposite
\underline{op}timization for l\underline{e}arning~({SCOPE}), and implement it
on the fault-tolerant distributed platform \mbox{Spark}. SCOPE is both
computation-efficient and communication-efficient. Theoretical analysis shows
that SCOPE is convergent with linear convergence rate when the objective
function is convex. Furthermore, empirical results on real datasets show that
SCOPE can outperform other state-of-the-art distributed learning methods on
Spark, including both batch learning methods and DSO methods
Maintaining consistency in distributed systems
In systems designed as assemblies of independently developed components, concurrent access to data or data structures normally arises within individual programs, and is controlled using mutual exclusion constructs, such as semaphores and monitors. Where data is persistent and/or sets of operation are related to one another, transactions or linearizability may be more appropriate. Systems that incorporate cooperative styles of distributed execution often replicate or distribute data within groups of components. In these cases, group oriented consistency properties must be maintained, and tools based on the virtual synchrony execution model greatly simplify the task confronting an application developer. All three styles of distributed computing are likely to be seen in future systems - often, within the same application. This leads us to propose an integrated approach that permits applications that use virtual synchrony with concurrent objects that respect a linearizability constraint, and vice versa. Transactional subsystems are treated as a special case of linearizability
Wireless Software Synchronization of Multiple Distributed Cameras
We present a method for precisely time-synchronizing the capture of image
sequences from a collection of smartphone cameras connected over WiFi. Our
method is entirely software-based, has only modest hardware requirements, and
achieves an accuracy of less than 250 microseconds on unmodified commodity
hardware. It does not use image content and synchronizes cameras prior to
capture. The algorithm operates in two stages. In the first stage, we designate
one device as the leader and synchronize each client device's clock to it by
estimating network delay. Once clocks are synchronized, the second stage
initiates continuous image streaming, estimates the relative phase of image
timestamps between each client and the leader, and shifts the streams into
alignment. We quantitatively validate our results on a multi-camera rig imaging
a high-precision LED array and qualitatively demonstrate significant
improvements to multi-view stereo depth estimation and stitching of dynamic
scenes. We release as open source 'libsoftwaresync', an Android implementation
of our system, to inspire new types of collective capture applications.Comment: Main: 9 pages, 10 figures. Supplemental: 3 pages, 5 figure
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