19,478 research outputs found
Using the Workforce Investment Act to Develop and Foster Innovative State Workforce Policies and Programs
Outlines how some states are using Workforce Investment Act (WIA) discretionary funds to help low-wage workers enhance their careers and to help the unemployed find jobs. Highlights innovative programs and recommends focusing and leveraging resources
Workforce Intermediaries: Powering Regional Economies in the New Century
Examines the role of workforce intermediary organizations in developing local strategies and funding, and coordinating the efforts of stakeholders in regional economic development. Outlines the qualities of successful workforce intermediary organizations
The Road to Good Employment Retention: Three Successful Programs From the Jobs Initiative
Looks at long-term job retention by low-skilled individuals. Profiles three job retention initiatives with high success rates -- two in Seattle, and one in St. Louis
From Stimulus to System: Using the ARRA to Serve Disadvantaged Jobseekers
This paper explores models and mechanisms for connecting low-skilled jobseekers to ARRA-related job opportunities--including community-benefit agreements, job linkage/first source hiring, and goals and standards for job creation and job quality--and for subsequently engaging jobseekers in further skill-building and educational programs
Attention gates visual coding in the human pulvinar.
The pulvinar nucleus of the thalamus is suspected to have an important role in visual attention, based on its widespread connectivity with the visual cortex and the fronto-parietal attention network. However, at present, there remain many hypotheses on the pulvinars specific function, with sparse or conflicting evidence for each. Here we characterize how the human pulvinar encodes attended and ignored objects when they appear simultaneously and compete for attentional resources. Using multivoxel pattern analyses on data from two functional magnetic resonance imaging (fMRI) experiments, we show that attention gates both position and orientation information in the pulvinar: attended objects are encoded with high precision, while there is no measurable encoding of ignored objects. These data support a role of the pulvinar in distractor filtering--suppressing information from competing stimuli to isolate behaviourally relevant objects
Self-Directed Learning and the Impact of Leadership: Analyzing Keys for Success from a Covenental Perspective
The current state of education seems to beg for visionary changes to truly impact students and prepare them for the future. Self-directed learning models purport to do just that, by preparing students to be self-motivated, lifelong learners. While many educators seek to apply self-directed practices, research reveals that there are several obstacles that can hinder self-directed learning. Duby’s 2006 study of schools employing self-directed learning investigated how leaders successfully overcome these hindrances via specific leadership attitudes and behaviors that not only effectively overcame these obstacles, but are also reflected in the covenantal perspective of leadership. Using content analysis, this paper further explores the findings of Duby’s study of educational leaders, analyzing them within the covenantal construct developed by Fischer (2003), in order to better understand the relationship between effective leadership practice and the covenantal perspective. This study revealed intriguing similarities between particulars of the CFA model and the leadership practices exhibited in the self-directed learning schools. These similarities also present opportunities for future study, including whether visionary organizations are more apt to be motivated by covenantal principles and examining the type of for-profit organizations that are more apt to embody the tenets of CFA
Definable maximal cofinitary groups of intermediate size
Using almost disjoint coding, we show that for each
consistently ,
where is witnessed by a maximal cofinitary
group.Comment: 22 page
A Real-Time Solver For Time-Optimal Control Of Omnidirectional Robots with Bounded Acceleration
We are interested in the problem of time-optimal control of omnidirectional
robots with bounded acceleration (TOC-ORBA). While there exist approximate
solutions for such robots, and exact solutions with unbounded acceleration,
exact solvers to the TOC-ORBA problem have remained elusive until now. In this
paper, we present a real-time solver for true time-optimal control of
omnidirectional robots with bounded acceleration. We first derive the general
parameterized form of the solution to the TOC-ORBA problem by application of
Pontryagin's maximum principle. We then frame the boundary value problem of
TOC-ORBA as an optimization problem over the parametrized control space. To
overcome local minima and poor initial guesses to the optimization problem, we
introduce a two-stage optimal control solver (TSOCS): The first stage computes
an upper bound to the total time for the TOC-ORBA problem and holds the time
constant while optimizing the parameters of the trajectory to approach the
boundary value conditions. The second stage uses the parameters found by the
first stage, and relaxes the constraint on the total time to solve for the
parameters of the complete TOC-ORBA problem. We further implement TSOCS as a
closed loop controller to overcome actuation errors on real robots in
real-time. We empirically demonstrate the effectiveness of TSOCS in simulation
and on real robots, showing that 1) it runs in real time, generating solutions
in less than 0.5ms on average; 2) it generates faster trajectories compared to
an approximate solver; and 3) it is able to solve TOC-ORBA problems with
non-zero final velocities that were previously unsolvable in real-time
Spectral analysis of two-dimensional Bose-Hubbard models
One-dimensional Bose-Hubbard models are well known to obey a transition from
regular to quantum-chaotic spectral statistics. We are extending this concept
to relatively simple two-dimensional many-body models. Also in two dimensions a
transition from regular to chaotic spectral statistics is found and discussed.
In particular, we analyze the dependence of the spectral properties on the bond
number of the two-dimensional lattices and the applied boundary conditions. For
maximal connectivity, the systems behave most regularly in agreement with the
applicability of mean-field approaches in the limit of many nearest-neighbor
couplings at each site.Comment: 6 pages, 6 figure
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